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BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210708T150000
DTEND;TZID=America/Toronto:20210708T160000
DTSTAMP:20260423T033046
CREATED:20210525T165425Z
LAST-MODIFIED:20210809T205411Z
UID:10000417-1625756400-1625760000@www.ieeetoronto.ca
SUMMARY:From an Idea to a Startup
DESCRIPTION:We are living in the age of innovation. Every day\, innovators are solving many problems that people are facing in life. In the process of innovation\, there are many questions about how we can find problems. What is innovation exactly? How can we find solutions? And how can we learn the innovation process? \nI am Masoud Valinejad\, CEO-Director of technology in NovoSolTech Company\, and innovation mentor with more than five-year experience\, with 10 USA patents\, and more than five national and international special prizes in innovation competitions. In this webinar\, I want to show you how you can become an innovator and entrepreneur through some steps and practices. \nContact: Ayda Naserialiabadi
URL:https://www.ieeetoronto.ca/event/from-an-idea-to-a-startup/
LOCATION:Virtual – Zoom
CATEGORIES:Instrumentation & Measurement,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210628T180000
DTEND;TZID=UTC:20210628T193000
DTSTAMP:20260423T033046
CREATED:20210617T220318Z
LAST-MODIFIED:20210809T205400Z
UID:10000434-1624903200-1624908600@www.ieeetoronto.ca
SUMMARY:IEEE VDL: Machine Learning for Wireless Communications and Networking: Motivations\, Case Studies\, and Open Problems
DESCRIPTION:On Monday\, June 28\, 2021\, come listen to Dr. Shiwen Mao present the IEEE ComSoc VDL: Machine Learning for Wireless Communications and Networking: Motivations\, Case Studies\, and Open Problems. \nZOOM link will be provided to attendees. \nContact: IEEE Denver ComSoc \nAbstract: \nWhile 5G deployment is being carried out in many places of the world\, there has been great interest in the prospects of 5G beyond and the next generation. Among the various visions\, a common theme is that artificial intelligence will play a key role\, as evidenced by the great interest and advances in machine learning enabled wireless communications and networking. In this talk\, we will discuss the motivation\, potential\, and challenges of incorporating machine learning in wireless communications and networking for 5G and beyond systems. \nWe will start with two motivating examples\, i.e.\, channel estimation and mobile edge computing\, to show why machine learning could be helpful. We will share our experience of several case studies\, including (i) a hybrid approach to the classical energy efficiency maximization problem\, where traditional models could be used to train a deep learning model; (ii) data augmentation for convolutional neural network (CNN) based automatic modulation classification (AMC)\, where a conditional generative adversarial network (CGAN) is utilized to generate synthesized training data; and (iii) and an adaptive model for RFID-based 3D human skeleton tracking\, which utilizes meta-learning and few-shot fine-tuning to achieve high adaptability to new environments. We will conclude this talk with a discussion of challenges and open problems. \nSpeaker(s): Dr. Shiwen Mao \nBiography: \n \nShiwen Mao [S’99-M’04-SM’09-F’19] received his Ph.D. in electrical engineering from Polytechnic University\, Brooklyn\, NY in 2004. He was a postdoc at Virginia Tech from 2004 to 2006\, and joined Auburn University\, Auburn\, AL as an assistant professor of Electrical and Computer Engineering in 2006. He held the McWane Endowed Professorship from 2012 to 2015 and the Samuel Ginn Endowed Professorship from 2015 to 2020. Currently\, he is a professor and Earle C. Williams Eminent Scholar Chair\, and Director of the Wireless Engineering Research and Education Center at Auburn University. His research interest includes wireless networks\, multimedia communications\, and smart grid. He is on the editorial board of several IEEE and ACM journals. He is a Distinguished Lecturer of IEEE Communications Society and IEEE Council of RFID\, and a Distinguished Speaker of IEEE Vehicular Technology Society. He received the IEEE ComSoc TC-CSR Distinguished Technical Achievement Award in 2019 and NSF CAREER Award in 2010. He is a co-recipient of the 2021 IEEE Communications Society Outstanding Paper Award and the IEEE Vehicular Technology Society 2020 Jack Neubauer Memorial Award. \nAgenda: \n6pm (MT) – Introductions \n6:10-7:15 – VDL Presentation \n7:15-7:30 – Q&A
URL:https://www.ieeetoronto.ca/event/machine-learning-for-wireless-communications-and-networking-motivations-case-studies-and-open-problems/
LOCATION:Virtual – Zoom
CATEGORIES:Communications
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210624T110000
DTEND;TZID=UTC:20210624T123000
DTSTAMP:20260423T033046
CREATED:20210617T220318Z
LAST-MODIFIED:20210809T205348Z
UID:10000432-1624532400-1624537800@www.ieeetoronto.ca
SUMMARY:IEEE VDL: Learning to Learn to Communicate
DESCRIPTION:Join us on Thursday\, June 24\, 2021 for the IEEE VDL: Learning to Learn to Communicate\, presented by Prof. Osvaldo Simeone. \nContact: IEEE Kingston ComSoc \nAbstract: \nThe application of supervised learning techniques for the design of the physical layer of a communication link is often impaired by the limited amount of pilot data available for each device; while the use of unsupervised learning is typically limited by the need to carry out a large number of training iterations. In this talk\, meta-learning\, or learning-to-learn\, is introduced as a tool to alleviate these problems. The talk will consider an Internet-of-Things (IoT) scenario in which devices transmit sporadically using short packets with few pilot symbols over a fading channel. The number of pilots is generally insufficient to obtain an accurate estimate of the end-to-end channel\, which includes the effects of fading and of the transmission-side distortion. To tackle this problem\, pilots from previous IoT transmissions are used as meta-training data in order to train a demodulator that is able to quickly adapt to new end-to-end channel conditions from few pilots. Various state-of-the-art meta-learning schemes are adapted to the problem at hand and evaluated\, including MAML\, FOMAML\, REPTILE\, and CAVIA. Both offline and online solutions are developed. \nSpeaker(s): Prof. Osvaldo Simeone \nBiography: \nOsvaldo Simeone is a Professor of Information Engineering with the Centre for Telecommunications Research at the Department of Engineering of King’s College London\, where he directs the King’s Communications\, Learning and Information Processing lab. He received an M.Sc. degree (with honors) and a Ph.D. degree in information engineering from Politecnico di Milano\, Milan\, Italy\, in 2001 and 2005\, respectively. From 2006 to 2017\, he was a faculty member of the Electrical and Computer Engineering (ECE) Department at New Jersey Institute of Technology (NJIT)\, where he was affiliated with the Center for Wireless Information Processing (CWiP). His research interests include information theory\, machine learning\, wireless communications\, and neuromorphic computing. Dr Simeone is a co-recipient of the 2019 IEEE Communication Society Best Tutorial Paper Award\, the 2018 IEEE Signal Processing Best Paper Award\, the 2017 JCN Best Paper Award\, the 2015 IEEE Communication Society Best Tutorial Paper Award and of the Best Paper Awards of IEEE SPAWC 2007 and IEEE WRECOM 2007. He was awarded a Consolidator grant by the European Research Council (ERC) in 2016. His research has been supported by the U.S. NSF\, the ERC\, the Vienna Science and Technology Fund\, as well as by a number of industrial collaborations. He currently serves in the editorial board of the IEEE Signal Processing Magazine and is the vice-chair of the Signal Processing for Communications and Networking Technical Committee of the IEEE Signal Processing Society. He was a Distinguished Lecturer of the IEEE Information Theory Society in 2017 and 2018. Dr Simeone is a co-author of two monographs\, two edited books published by Cambridge University Press\, and more than one hundred research journal papers. He is a Fellow of the IET and of the IEEE.
URL:https://www.ieeetoronto.ca/event/ieee-vdl-learning-to-learn-to-communicate/
LOCATION:Virtual – Zoom
CATEGORIES:Communications
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210622T180000
DTEND;TZID=UTC:20210622T190000
DTSTAMP:20260423T033046
CREATED:20210614T213828Z
LAST-MODIFIED:20210809T205336Z
UID:10000428-1624384800-1624388400@www.ieeetoronto.ca
SUMMARY:Overview of Secondary Surveillance Radar (SSR) and Identification Friend/Foe (IFF) Systems - Part I - Virtual Lecture - CEU/PDH Available
DESCRIPTION:The lecture is composed of two one-hour parts. \nIn Part I a general overview of SSR/IFF is presented which includes a review of terms and definitions. From there\, a historical timeline of SSR/IFF is summarized beginning with early implementations and ending with modern day systems. Then system architectures are reviewed starting with block diagrams and the challenges of scanning airspace. System-level features discussed include sidelobe suppression\, antenna dwell time\, azimuth determination and RF link budgets. In addition\, the trade-offs between 2-channel and 3-channel systems are reviewed. \nLink to virtual event will be provided after registration. \nContact: IEEE Long Island CAS Society \nSpeaker(s): Frank Messina \nBiography: \nFrank Messina is the Chief Engineer of the SSR and IFF products for Telephonics. Frank has 50 years of experience in the design\, development\, and fielding of innovative IFF and SSR products for Military and Civil use. Frank is the lead IFF Interrogator Systems Engineer for the world’s fleet of AWACS aircraft\, US Navy P8-A Multi-Mission Aircraft (MMA)\, US Navy MH-60R aircraft\, Canadian Maritime Patrol Aircraft (CP140)\, Canadian Maritime Helicopter (MHP)\, Canadian Frigate Upgrade\, USMC G/ATOR\, USAF D-RAPCON\, Mode 5 Operational Autonomous Surveillance (M5 OAS)\, SAAB Giraffe Mobile Platforms and other ground\, shipboard and airborne based products at Telephonics. \nEarlier in his career\, Frank was the lead engineer for the FAA Common Digitizer 2 (CD-2) SSR Beacon Extractor System. Frank was also instrumental in adding full Mode S interrogator capability to the NATO AWACS\, which represents the first military IFF interrogator system to integrate the high-priority AEW Military IFF Modes with Mode S. He was also the IFF team leader for the design and development of the AN/APS-147 and AN/APS-153 IFF interrogator system – the first integrated and tightly-coupled Multi-Mode Radar and IFF interrogator fusion system. More recently\, Frank lead the design and development of the AN/UPR-4(V) Passive Detection and Reporting System (PDRS) and Small Form Factor SFF-44 All-Mode Active and Passive IFF system.
URL:https://www.ieeetoronto.ca/event/overview-of-secondary-surveillance-radar-ssr-and-identification-friend-foe-iff-systems-part-i-virtual-lecture-ceu-pdh-available/
LOCATION:Virtual
CATEGORIES:Circuits & Devices
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210621T110000
DTEND;TZID=UTC:20210621T123000
DTSTAMP:20260423T033046
CREATED:20210617T220317Z
LAST-MODIFIED:20210809T205324Z
UID:10000430-1624273200-1624278600@www.ieeetoronto.ca
SUMMARY:IEEE VDL: Intelligent Reflected Surfaces for Future Wireless Systems
DESCRIPTION:Join the IEEE Kingston ComSoc and IEEE Toronto ComSoc for the Virtual Distinguished Lecture “Intelligent Reflected Surfaces for Future Wireless Systems”\, presented by Dr. Shahid Mumtaz. \nContact: IEEE Kingston ComSoc \nAbstract:  \nAs we have finalized the research for 5G\, now there is a race for technologies that will conquer 6G. The 6G  technologies will achieve much better latency and computation efficiency as compared to 5G. From 1G to 5G\, almost all research and standardization randomly model the wireless channel between transmitter and receiver. There is no control of humans over a wireless medium\, as it is given by nature. In 6G\, we will break this assumption and go from random wireless channels to controllable wireless. Thanks to Intelligent Reflected Surfaces for Future Wireless System(IRS). This talk will explain in detail the physics of metasurface and the progress of IRS till today. This talk will also present different use case\, study cases\, signal processing and communication techniques for IRS\, standardization\, Prototype and testbed\, and the open research challenges. \nSpeaker(s): Dr. Shahid Mumtaz \nBiography: \nShahid Mumtaz is an IET Fellow\, IEEE ComSoc and ACM Distinguished speaker\, recipient of IEEE ComSoC Young Researcher Award (2020)\, IEEE Senior member\, founder and EiC of IET “Journal of Quantum communication”\, Vice-Chair: Europe/Africa Region- IEEE ComSoc: Green Communications & Computing society and Vice-chair for IEEE standard on P1932.1: Standard for Licensed/Unlicensed Spectrum Interoperability in Wireless Mobile Networks. \nHe has more than 15 years of wireless industry/academic experience. He has received his Master’s and Ph.D. degrees in Electrical & Electronic Engineering from Blekinge Institute of Technology\, Sweden\, and University of Aveiro\, Portugal in 2006 and 2011\, respectively. From 2002 to 2003\, he worked for Pak Telecom as System Engineer and from 2005 to 2006 for Ericsson and Huawei at Research Labs in Sweden. He has been with Instituto de Telecomunicações since 2011 where he currently holds the position of Auxiliary Researcher and adjunct positions with several universities across the Europe-Asian Region. \nHe is the author of 4 technical books\, 12 book chapters\, 250+ technical papers (170+ Journal/transaction\, 90+ conference\, 2 IEEE best paper award- in the area of mobile communications. He had/has supervised/co-supervising several Ph.D. and Master Students. He uses mathematical and system-level tools to model and analyze emerging wireless communication architectures\, leading to innovative theoretically optimal new communication techniques. He is working closely with leading R&D groups in the industry to transition these ideas to practice. He secures the funding of around 2M Euro.
URL:https://www.ieeetoronto.ca/event/ieee-vdl-intelligent-reflected-surfaces-for-future-wireless-systems/
LOCATION:Virtual – Zoom
CATEGORIES:Communications
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210618T130000
DTEND;TZID=UTC:20210618T140000
DTSTAMP:20260423T033046
CREATED:20210614T213827Z
LAST-MODIFIED:20210809T205307Z
UID:10000427-1624021200-1624024800@www.ieeetoronto.ca
SUMMARY:AI against COVID-19 Competition: Closing Ceremony
DESCRIPTION:IEEE SIGHT (Special Interest Group on Humanitarian Technology) of Montreal Section\, Vision and Image Processing Research Group of the University of Waterloo and DarwinAI Corp. invite you to the closing ceremony of the virtual competition on AI for COVID-19 diagnosis with chest X-ray images. In the First Phase\, the challenge consisted of designing robust machine learning algorithms to predict if the subjects of study are either COVID-19 positive or COVID-19 negative. Join us to celebrate the amazing work done by all the teams and know who will be participating in the Second Phase. Then\, you are also invited to a networking session with everybody! \nAll the information will be sent to the registrants.
URL:https://www.ieeetoronto.ca/event/ai-against-covid-19-competition-closing-ceremony/
LOCATION:Virtual
CATEGORIES:SIGHT
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210617T130000
DTEND;TZID=UTC:20210617T143000
DTSTAMP:20260423T033046
CREATED:20210614T213826Z
LAST-MODIFIED:20210809T205253Z
UID:10000426-1623934800-1623940200@www.ieeetoronto.ca
SUMMARY:IEEE VDL: Localization in Drone Assisted and Vehicular Networks
DESCRIPTION:Join the IEEE Kingston Communications Society Chapter for the Virtual Distinguished Lecture: Localization in Drone Assisted and Vehicular Networks\, presented by Shahrokh Valaee. \nContact: IEEE Kingston ComSoc \nAbstract: \nThe next generation of wireless systems will employ networking equipment mounted on mobile platforms\, unmanned air vehicles (UAV)\, and low orbit satellites. As a result\, the topology of 6G wireless technology will extend to 3D vertical networking. With its extended service\, 6G will also give rise to new challenges which include\, the introduction of intelligent reflective surfaces (IRS)\, the mmWave spectrum\, the employment of massive MIMO systems\, and the agility of networks. Along with the advancement in networking technology\, user devices are also evolving rapidly\, with the emergence of highly capable cellphones\, smart IoT equipment\, and wearable devices. One of the key elements of 6G technology is the need for accurate positioning information. The accuracy of today’s positioning systems is not acceptable for many applications of future\, especially in smart environments. In this talk\, we will discuss how positioning can be a key enabler of 6G\, and what challenges the next generation of localization technology will face when integrated within the new wireless networks. \nSpeaker(s): Shahrokh Valaee \nBiography: Shahrokh Valaee is a Professor with the Edward S. Rogers Sr. Department of Electrical and Computer Engineering\, University of Toronto\, and the holder of Nortel Chair of Network Architectures and Services. He is the Founder and the Director of the Wireless and Internet Research Laboratory (WIRLab) at the University of Toronto. Professor Valaee was the TPC Co-Chair and the Local Organization Chair of the IEEE Personal Mobile Indoor Radio Communication (PIMRC) Symposium 2011. He was the TCP Chair of PIMRC2017\, the Track Co-Chair of WCNC 2014\, the TPC Co-Chair of ICT 2015. He has been the guest editor for various journals. He was a Track Co-chair for PIMRC 2020 and VTC Fall 2020. From December 2010 to December 2012\, he was the Associate Editor of the IEEE Signal Processing Letters. From 2010 to 2015\, he served as an Editor of IEEE Transactions on Wireless Communications. Currently\, he is an Editor of Journal of Computer and System Science. Professor Valaee is a Fellow of the Engineering Institute of Canada\, and a Fellow of IEEE.
URL:https://www.ieeetoronto.ca/event/ieee-vdl-localization-in-drone-assisted-and-vehicular-networks/
LOCATION:Virtual – Zoom
CATEGORIES:Communications
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210611T143000
DTEND;TZID=UTC:20210611T153000
DTSTAMP:20260423T033046
CREATED:20210614T213826Z
LAST-MODIFIED:20210809T205239Z
UID:10000425-1623421800-1623425400@www.ieeetoronto.ca
SUMMARY:Protect the Privacy\, Security\, and Integrity of APIs
DESCRIPTION:TeejLab’s mission: \nProtect the privacy\, security\, and integrity of APIs at a global scale by building Data Science and Artificial Intelligence driven API management solutions to help enterprises with API Governance.  Learn more about TeejLab: https://apidiscovery.teejlab.com. \nContact: Mehrdad Tirandazian \nAbstract: \nSoftware development is becoming increasingly reliant on using third-party services accessed through APIs. These APIs connect various IT systems and processes with people to offer useful services that help us run our businesses and personal lives.  API integration may be simple\, but APIs may directly or indirectly expose your IT assets and Databases to unofficial or illegitimate use. This talk aims to help students understand the overall implications of API\, including information security\, data management\, legal risk management\, and licensing costs. \nSpeaker(s): Dr. Baljeet Baljeet of TeejLab \nBiography: \nDr. Malhotra is an award-winning researcher known for his work in Open Source and API data management. He conceptualized the world’s first “API Composition Analysis” based on source code static analysis. He founded TeejLab in 2017 and steered the team to build\, API Discovery™\, world’s first comprehensive end-to-end API Management platform. He also established R&D unit of Black Duck Software in 2016 (acquired for US $565M by Synopsys). Previously\, he was Research Director at SAP (2011-2016)\, Computational Scientist at the EOS Lab (2009) and Software Engineer at Satyam Computers (1999). He received a PhD in Computing Science from the University of Alberta. He was awarded NSERC (Canada) scholar in 2005\, and Global Young Scientist (Singapore) in 2011. He concurrently holds Adjunct Professor positions at the University of British Columbia\, University of Victoria and University of Northern BC.
URL:https://www.ieeetoronto.ca/event/protect-the-privacy-security-and-integrity-of-apis/
LOCATION:Virtual – Zoom
CATEGORIES:Systems
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210610T120000
DTEND;TZID=UTC:20210610T133000
DTSTAMP:20260423T033046
CREATED:20210614T213825Z
LAST-MODIFIED:20210809T204954Z
UID:10000424-1623326400-1623331800@www.ieeetoronto.ca
SUMMARY:Rate-Splitting Multiple Access for 6G
DESCRIPTION:Virtual platform will be delivered to registrants a couple of hours before starting the event.  \nContact: IEEE Montreal Young Professionals \nAbstract: \nRate Splitting Multiple Access (RSMA)\, based on (linearly or nonlinearly) precoded Rate-Splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at the receivers\, has emerged as a novel\, general and powerful framework for the design and optimization of non-orthogonal transmission\, multiple access\, and interference management strategies in future MIMO wireless networks. RSMA relies on the split of messages and the non-orthogonal transmission of common messages decoded by multiple users\, and private messages decoded by their corresponding users. This enables RSMA to softly bridge and therefore reconcile the two extreme strategies of fully decode interference and treat interference as noise. RSMA has been shown to generalize\, and subsume as special cases\, four seemingly different strategies\, namely Space Division Multiple Access (SDMA) based on linear precoding (currently used in 5G)\, Orthogonal Multiple Access (OMA)\, Non-Orthogonal Multiple Access (NOMA) based on linearly precoded superposition coding with SIC\, and physical-layer multicasting. RSMA boils down to those strategies in some specific conditions\, but outperforms them all in general. Through information and communication theoretic analysis\, RSMA is shown to be optimal (from a Degrees-of-Freedom region perspective) in a number of scenarios and provides significant room for spectral efficiency\, energy efficiency\, fairness\, reliability\, QoS enhancements in a wide range of network loads and user deployments\, robustness against imperfect Channel State Information at the Transmitter (CSIT)\, as well as feedback overhead and complexity reduction over conventional strategies used in 5G. The benefits of RSMA have been demonstrated in a wide range of scenarios (MU-MIMO\, massive MIMO\, multi-cell MIMO/CoMP\, overloaded systems\, NOMA\, multigroup multicasting\, mmwave communications\, communications in the presence of RF impairments and superimposed unicast and multicast transmission\, relay\,…) and systems (terrestrial\, cellular\, satellite\, …). Thanks to its versatility\, RSMA has the potential to tackle challenges of modern communication systems and is a gold mine of research problems for academia and industry\, spanning fundamental limits\, optimization\, PHY and MAC layers\, and standardization. \nThis lecture will share key principles of RSMA\, recent developments\, emerging applications and opportunities of RSMA for 6G networks and will cover many of the topics currently investigated as part of the new IEEE special interest group on RSMA https://sites.google.com/view/ieee-comsoc-wtc-sig-rsma/home. \nSpeaker(s): Bruno Clerckx \nBiography: \nBruno Clerckx is a (Full) Professor\, the Head of the Wireless Communications and Signal Processing Lab\, and the Deputy Head of the Communications and Signal Processing Group\, within the Electrical and Electronic Engineering Department\, Imperial College London\, London\, U.K. He received the M.S. and Ph.D. degrees in applied science from the Université Catholique de Louvain\, Louvain-la-Neuve\, Belgium\, in 2000 and 2005\, respectively. From 2006 to 2011\, he was with Samsung Electronics\, Suwon\, South Korea\, where he actively contributed to 4G (3GPP LTE/LTE-A and IEEE 802.16m) and acted as the Rapporteur for the 3GPP Coordinated Multi-Point (CoMP) Study Item. Since 2011\, he has been with Imperial College London\, first as a Lecturer from 2011 to 2015\, Senior Lecturer from 2015 to 2017\, Reader from 2017 to 2020\, and now as a Full Professor. From 2014 to 2016\, he also was an Associate Professor with Korea University\, Seoul\, South Korea. He also held various long or short-term visiting research appointments at Stanford University\, EURECOM\, National University of Singapore\, The University of Hong Kong\, Princeton University\, The University of Edinburgh\, The University of New South Wales\, and Tsinghua University.
URL:https://www.ieeetoronto.ca/event/rate-splitting-multiple-access-for-6g/
LOCATION:Virtual
CATEGORIES:Young Professionals
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210608T180000
DTEND;TZID=America/Toronto:20210608T190000
DTSTAMP:20260423T033046
CREATED:20210601T191940Z
LAST-MODIFIED:20210809T205005Z
UID:10000423-1623175200-1623178800@www.ieeetoronto.ca
SUMMARY:Advanced OrCad Workshop
DESCRIPTION:IEEE Seneca is offering an advanced OrCad Workshop.\nWe will be reinforcing ETD555 concepts and learn about following topics: \n\nTransistor circuits (PNP\, NPN\, Darlington and MOSFETS)\nComponents such as IRF840\, IRF9510\, TIP122\, TIP127\, 2N3904\, and 2N3906\n\nTo amplify the experience\, please have OrCad installed or using virual commons to follow through the instructions. \nContact: IEEE Seneca \nSpeakers: Gabriel Chen\, Adi Malihi
URL:https://www.ieeetoronto.ca/event/advanced-orcad-workshop/
LOCATION:Virtual – Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210607T180000
DTEND;TZID=America/New_York:20210611T210000
DTSTAMP:20260423T033046
CREATED:20210430T222549Z
LAST-MODIFIED:20210809T205016Z
UID:10000377-1623088800-1623445200@www.ieeetoronto.ca
SUMMARY:Introduction to Python Programming
DESCRIPTION:This is an introduction to Python programming for students without any prior programming knowledge or experience. The proposed 5-day course covers the fundamental aspects of programming\, which include data types\, various operators\, input/output\, conditions\, control flow\, functions\, and algorithms. The learning experience is enhanced by a number of examples and problem sets (data\, strings\, file processing and simple graphics) that will be solved interactively during the lecture with the participation of the students. The course format includes 3 hours of daily lectures. \nCourse Objective: Attendees will gain a solid understanding of principles of programing using Python; they can progress to more advanced programming topics and explores algorithms that are integral parts of more sophisticated methodologies\, e.g.\, Artificial Intelligence. Attendees will have the knowledge to write various Python programs\, and to design algorithms manipulating files and different types of data including numbers\, and text. \nNote: This course is designed to be offered online\, and it requires the attendees to use their personal computers/laptops. Details to Join in will be forwarded to Registered Attendees \nWho should attend: Students\, second career trainees\, engineers\, scientists\, clinicians\, and in general specialists in variety of non-STEM fields. \nWhat will you receive after completion: A certificate of completion will be given to the students who successfully complete the course and pass a short exam. Electronic copies of the course materials. Attendees will also be provided with career\, and skills development advice. \nSpeaker\nDr. Alireza Sadeghian \nDr. Alireza Sadeghian has been with the Department of Computer Science at Ryerson University since 1999\, where he holds the position of the Professor. He is also an Affiliate Scientist at the Li Ka Shing Knowledge Institute\, St. Michael’s Hospital\, and serves as the AI research Theme Lead in Healthcare and Analytics at the Institute for Biomedical Engineering\, Science\, and Technology. \nDr. Sadeghian was the Chair of the Department of Computer Science from 2005 to 2015. He is the founding Director of the Advanced Artificial Intelligence Initiative (AI2) Laboratory and has extensive expertise in the areas of AI\, machine learning\, and Deep Learning particularly related to industrial and medical applications. He has supervised 9 postdoctoral fellows\, 8 PhD\, and 24 Master’s students\, as well as 60 research assistants. He has published over 150 journal manuscripts\, refereed conference papers\, and book chapters\, as well as two edited books. He has 2 invention disclosures and 2 patents. \nDr. Sadeghian has been actively involved with a number of international professional and academic boards including IEEE Education Activity Board. Presently\, he is the Chair of IEEE Computational Intelligence Technical Society Chapter\, Toronto Section. Dr. Sadeghian is also on the Editorial Board of Applied Soft Computing Journal and serves as an Associate Editor of IEEE Access\, Information Sciences\, and Expert Systems Journal. \nEmail: dr.alireza.sadeghian@ieee.org \nAgenda\nDay 1 – June 7\, 2021\, 6:00-9:00 pm: Introduction to computer systems\, hardware architecture\, CPU\, memory\, compilation\, high level vs. low-level programming language\, data representation\, Python and PyCharm interactive IDE installation\, writing/editing/saving/retrieving and running a simple program\, basic data types\, variables\, assignments\, comments\, and expressions. The material learned will be reinforced through examples provided during the lecture. \nDay 2 – June 8\, 2021\, 6:00-9:00 pm: The following topics will be discussed: conditions\, operators (arithmetic\, logic\, and comparison)\, control statements (if and if-else)\, and loops (for and while). The material learned will be reinforced through examples provided during the lecture. \nDay 3 – June 9\, 2021\, 6:00-9:00 pm: Students will be introduced to Strings and text files in Python. They will learn how to work with files\, reading/writing text and numbers from/to a file\, string manipulation\, indexing\, and string slicing. The material learned will be reinforced through examples provided during the lecture. \nDay 4 – June 10\, 2021\, 6:00-9:00 pm: Functions\, arguments\, and return values will be discussed. The material learned will be reinforced through examples provided during the lecture. \nDay 5 – June 11\, 2021\, 6:00-9:00 pm: The topics of lists and dictionaries will be discussed. Students will learn about the basic operators\, creating\, accessing\, slicing\, adding\, removing\, replacing\, and iteration methods for lists and dictionaries. The material learned will be reinforced through examples provided during the lecture.
URL:https://www.ieeetoronto.ca/event/introduction-to-python-programming/
LOCATION:Virtual
CATEGORIES:Signals & Computational Intelligence,Women in Engineering,Young Professionals
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210607T180000
DTEND;TZID=America/Toronto:20210607T190000
DTSTAMP:20260423T033046
CREATED:20210601T191549Z
LAST-MODIFIED:20210809T205028Z
UID:10000422-1623088800-1623092400@www.ieeetoronto.ca
SUMMARY:Basic OrCad Workshop
DESCRIPTION:IEEE Seneca is offering a basic OrCad Workshop.\nWe will be reinforcing ETY155 concepts and learn about following topics: \n– Simple resistor circuits\n– Voltage divider\n– Current divider concepts\n– Parallel circuits vs series circuits \nTo amplify the experience\, please have OrCad installed or use virual commons by Seneca to follow through the instruction. \nContact: IEEE Seneca \nSpeakers: Gabriel Chen\, Adi Malihi
URL:https://www.ieeetoronto.ca/event/basic-orcad-workshop/
LOCATION:Virtual – Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210604T160000
DTEND;TZID=America/Toronto:20210604T170000
DTSTAMP:20260423T033046
CREATED:20210520T163231Z
LAST-MODIFIED:20210809T205042Z
UID:10000416-1622822400-1622826000@www.ieeetoronto.ca
SUMMARY:[AP-S Seminar Series] Low Profile Antennas for Chip-to-Chip Data Communications: A Research Story\, Prof. Kathleen Melde
DESCRIPTION:Abstract: In this talk\, we present our recent research involving the development of low profile antennas that are used to replace wired interconnects in multi-chip modules in electronic packaging. This presentation will discuss the evolution of chip-compatible pattern adaptable mm-wave antenna modules to be used in massively multicore computers. The result is an enabling technology that overcomes technology bottlenecks that are prevalent when wired lines are used in interconnect busses. While device technologies have scaled\, the interconnection layers have not. The limits are in the pitch of the input and output (I/O) for chip-to-chip communications and losses due to physical transmission lines. This is a unique type of pattern adaptable antenna array in that the antenna patterns are in the same plane as the antenna elements. This is quite a departure from many other types of reconfigurable antennas where the patterns are broadside (90 degree angle) to the antennas. The approach is new in that it leverages mm-wave technology (60GHz) so that the antenna size is small. 60GHz allows the work to leverage the already-developed transceiver work done for WPAN technologies. 60GHz also has a natural attenuation at large transmission distances\, which means sufficient isolation and elimination of interference outside of the MCMC system. The research impacts antenna technology\, packaging technology (circuit stacking and advanced packaging)\, and wireless systems testing on an experimental testbed. The talk will focus on the story behind how the technology progresses and how the research unfolded along the way. \nContact: UofT AP-S Student Chapter
URL:https://www.ieeetoronto.ca/event/ap-s-seminar-series-low-profile-antennas-for-chip-to-chip-data-communications-a-research-story-prof-kathleen-melde/
LOCATION:Virtual – Zoom
CATEGORIES:Electromagnetics & Radiation
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210601T130000
DTEND;TZID=America/Toronto:20210601T140000
DTSTAMP:20260423T033046
CREATED:20210601T191120Z
LAST-MODIFIED:20210809T204834Z
UID:10000421-1622552400-1622556000@www.ieeetoronto.ca
SUMMARY:Ubiquitous Machines Learning for Design and Implementation of Energy-Efficient Electrical Systems: A Wide Range of Uses and Applications
DESCRIPTION:IEEE Industry Relations Committee (on behalf of IEEE Canada) would like to invite you to attend the Webinar “Ubiquitous Machines Learning for Design and Implementation of Energy-Efficient Electrical Systems: A Wide Range of Uses and Applications” \nThe objective of this webinar is to discuss how Artificial Intelligence (AI) can play a significant role in several applications in electrical engineering. The webinar intends to provide an update/overview of the recent trends and advances of AI research and to open a dialog on how to address the challenges faced in the design of energy-efficient electrical systems. Several pathways to innovate through electronic systems design will be discussed through a series of ongoing projects. \nSpeakers: \nProf. Yvon Savaria \nYvon Savaria FIEEE (S’ 77\, M’ 86\, SM’ 97\, F’08) received the B.Ing. and M.Sc.A in electrical engineering from Polytechnique Montreal in 1980 and 1982 respectively. He also received the Ph.D. in electrical engineering in 1985 from McGill University. Since 1985\, he has been with Polytechnique Montreal\, where he is currently professor in the department of electrical engineering. He is also affiliated with Hangzhou Innovation Institute of Beihang University. He has carried work in several areas related to microelectronic circuits and microsystems such as testing\, verification\, validation\, clocking methods\, defect and fault tolerance\, effects of radiation on electronics\, high-speed interconnects and circuit design techniques\, CAD methods\, reconfigurable computing and applications of microelectronics to telecommunications\, networking\, aerospace\, image processing\, video processing\, radar signal processing\, and digital signal processing acceleration. He is currently involved in several projects that relate to aircraft embedded systems\, asynchronous circuits design and test\, virtual networks\, software defined networks\, machine learning\, computational efficiency and application specific architecture design. He holds 16 patents\, has published 180 journal papers and 470 conference papers\, and he was the thesis advisor of 175 graduate students who completed their studies. \nDr. Ahmed Ragab \nAhmed Ragab is an AI research scientist working for CanmetENERGY\, an energy innovation center of Natural Resources Canada (NRCan). He received a Ph.D. degree in Industrial Engineering from Polytechnique Montréal in 2014. His research interests include AI\, Image Processing\, Data Fusion\, Causality Analysis\, Operations Research\, Discrete Event Systems\, and Process Mining. He has a bunch of experience in developing advanced algorithms and tools in the manufacturing industry\, aiming at reducing energy consumption\, Greenhouse gas (GHG) emissions\, and operational and maintenance costs while improving operations’ performance. His main thematic activities focus on the practical challenges of Big Data and AI in a number of applications including Abnormal Events Diagnosis & Prognosis\, Predictive Maintenance\, Supervisory Control\, Real-Time Optimization and Systems Design.
URL:https://www.ieeetoronto.ca/event/ubiquitous-machines-learning-for-design-and-implementation-of-energy-efficient-electrical-systems-a-wide-range-of-uses-and-applications/
LOCATION:Virtual
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210531T000000
DTEND;TZID=America/Toronto:20210531T235500
DTSTAMP:20260423T033046
CREATED:20210520T162352Z
LAST-MODIFIED:20210809T204824Z
UID:10000415-1622419200-1622505300@www.ieeetoronto.ca
SUMMARY:AI against COVID-19: Screening X-ray Images for COVID-19 Infections
DESCRIPTION:Join the virtual competition on AI for COVID diagnosis\, thanks to Microsoft Canada\, the exclusive technology and cloud platform sponsor! \n\n\n\nThe coronavirus disease 2019 (COVID-19) pandemic\, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus\, has generated an unprecedented global health crisis\, with more than 2.7 million deaths worldwide. Do you want to contribute to the fight against this pandemic? \nIEEE SIGHT (Special Interest Group on Humanitarian Technology) of Montreal Section\, Vision and Image Processing Research Group of the University of Waterloo and DarwinAI Corp. invite data scientists\, students and professionals working on Artificial Intelligence (AI) to participate in a virtual competition to help medical researchers diagnose COVID-19 with chest X-ray (CXR) images. The ultimate goal is to contribute to the development of highly accurate yet practical AI solutions for detecting COVID-19 cases and\, hopefully\, accelerating the treatment of those who need it the most. Moreover\, this AI for Good initiative will also allow us to take action on at least one of the United Nations Sustainable Development Goals (SDGs)\, Good Health and Well-being. \nIn the First Phase of the competition\, the challenge consists of designing robust machine learning algorithms to predict if the subjects of study are either COVID-19 positive or COVID-19 negative. The dataset for this competition is the dataset curated by COVID-Net\, a global open-source initiative launched by DarwinAI Corp.\, Canada\, and Vision and Image Processing Research Group\, University of Waterloo\, Canada\, for accelerating advancements in machine learning to aid healthcare workers around the world in the fight against the COVID-19 pandemic. More about the COVID-Net initiative and available open-source resources are available here. In the Second Phase\, the 10 top teams of the first phase will have the opportunity to refine their solution and submit a proposal for a follow-up project to positively impact society or the academic community. \nThis competition is organized in collaboration with the National Research Council Canada and is co-hosted by the IEEE Young Professionals Affinity Groups of Montreal\, Ottawa\, Toronto and Vancouver Sections\, Vancouver Circuit and Systems (CAS) Technical Chapter\, the Student Branches of INRS (Institut National de la Recherche Scientifique)\, University of Toronto and Vancouver Simon Fraser University\, WIE (Women In Engineering) Ottawa. It is largely sponsored by Microsoft\, and partially by the IEEE Canada Humanitarian Initiatives Committee and the IEEE Montreal Section. \nHow to participate \nNote: This competition only accepts participants living in Canada\, due to restrictions on funds transfer. \nNO PURCHASE NECESSARY TO ENTER OR WIN. \nThe competition is hosted on the Eval.ai online platform. To participate\, you or your team will need to perform the following steps: \n\nRegister individually at the link provided below in the current webpage (vTools).\nRegister yourself or your team at the link on Eval.ai: https://eval.ai/web/challenges/challenge-page/925/participate. Follow the instructions here: https://evalai.readthedocs.io/en/latest/participate.html#.\nDownload the dataset from https://www.kaggle.com/andyczhao/covidx-cxr2.\nDesign an AI algorithm that gets CXR images as inputs and predicts the labels of the images in the output (COVID or non-COVID).\nTrain your AI algorithm using the training dataset.\nSubmit your AI algorithm through Eval.ai for evaluation against the test dataset for the competition.\n\nPrizes \nFor the First Phase\, the first five best solutions will be awarded monetary prizes and Azure credits: \n\nFirst place: 1\,000 CAD + 500 CAD in Azure.\nSecond place: 800 CAD + 300 CAD in Azure.\nThird place: 600 CAD + 300 CAD in Azure.\nFourth place: 400 CAD + 300 CAD in Azure.\nFifth place: 300 CAD + 300 CAD in Azure.\n\nThe top 10 teams on the leaderboard will also have the following opportunities: \n\nParticipate in the 2nd phase to refine their solution and receive funding for a project.\nWrite a scientific paper with the Vision and Image Processing Research Group\, from the University of Waterloo\, to explain their approach.\n\nFor the Second Phase\, the best three projects can receive funds up to the following amounts: \n\nProject 1: 5\,000 CAD.\nProject 2: 5\,000 CAD.\nProject 3: 4\,000 CAD.\n\nTerm of funding: Up to 4 months following the announcement of the selected teams. The deadline is December 31st\, 2021. \n\nFor more information\, visit IEEE SIGHT Montreal website. \n 
URL:https://www.ieeetoronto.ca/event/ai-against-covid-19-screening-x-ray-images-for-covid-19-infections/
LOCATION:Virtual
CATEGORIES:SIGHT,Young Professionals
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210527T120000
DTEND;TZID=America/Toronto:20210527T130000
DTSTAMP:20260423T033046
CREATED:20210601T190546Z
LAST-MODIFIED:20210809T204803Z
UID:10000420-1622116800-1622120400@www.ieeetoronto.ca
SUMMARY:Integrated Terrestrial-Aerial-Satellite Networks: Key Enabler for the Super Smart Cities of the Future
DESCRIPTION:There have been rapid and exciting developments in recent years in satellite networks\, in particular\, in LEO mega-constellations such as SpaceX’s Starlink. Although less visible\, exciting developments have also been taking place in a certain type of aerial networks known as the high-altitude platform station (HAPS) systems\, such as the formation of HAPS Alliance which brings together the connectivity and aerospace industries. It is worth noting that the satellite and aerial networks discussions have been occurring exclusively in the context of remote and rural connectivity. A major concern in this context is the rather questionable business case; there is limited revenue in rural and remote regions. In this talk\, a novel vision will be presented for an integrated terrestrial-aerial-satellite networks architecture as a key enabler for the super smart cities of 2030s and beyond \nSpeaker: Dr. Halim Yanikomeroglu \nBiography: Dr. Halim Yanikomeroglu is a Professor at Carleton University\, Canada. He received his Ph.D. from the University of Toronto in 1998. He contributed to 4G/5G technologies and standards; his research focus in recent years has been on 6G and non-terrestrial networks (NTN). His extensive collaboration with industry resulted in 37 granted patents. He supervised or hosted in his lab around 140 postgraduate researchers. He co-authored IEEE papers with faculty members in 80+ universities in 25 countries. He is a Fellow of IEEE\, Engineering Institute of Canada\, and Canadian Academy of Engineering\, and an IEEE Distinguished Speaker for Communications Society (ComSoc) and Vehicular Technology Society (VTS). He is currently chairing the IEEE WCNC (Wireless Communications and Networking Conference) Steering Committee; he is also a member of PIMRC Steering Committee and ComSoc Emerging Technologies Committee. He served as the General Chair of two VTCs and Technical Program Chair/Co-Chair of three WCNCs. He chaired ComSoc Technical Committee on Personal Communications. He received several awards for his research\, teaching\, and service including IEEE ComSoc Fred W. Ellersick Prize (2021)\, IEEE VTS Stuart Meyer Memorial Award (2020)\, and IEEE ComSoc Wireless Communications Technical Committee Recognition Award (2018).
URL:https://www.ieeetoronto.ca/event/integrated-terrestrial-aerial-satellite-networks-key-enabler-for-the-super-smart-cities-of-the-future/
LOCATION:Virtual – Zoom
CATEGORIES:Communications
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210526T200000
DTEND;TZID=America/Toronto:20210526T210000
DTSTAMP:20260423T033046
CREATED:20210506T165447Z
LAST-MODIFIED:20210809T204752Z
UID:10000413-1622059200-1622062800@www.ieeetoronto.ca
SUMMARY:Enriching Public Speaking and Networking
DESCRIPTION:Having good communication and networking skills are essential to succeed in any industry\, especially for engineering students. \nJoin our workshop to improve public speaking and gain networking skills from IEEE\, our special guest\, Ana Acioli. Ana has great experiences networking with other engineers in her field while being a student. She will share how she overcame the fear of public speaking\, her techniques\, and the resources she has been using to improve her communication skills. Furthermore\, take the chance to join our community IEEE\, an engineering student organization where we share our passion as potential engineering students. \nSpeakers: Ana Acioli\, Adi Malihi
URL:https://www.ieeetoronto.ca/event/enriching-public-speaking-and-networking/
LOCATION:Virtual – Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210525T080000
DTEND;TZID=America/Toronto:20210525T150000
DTSTAMP:20260423T033046
CREATED:20210601T190345Z
LAST-MODIFIED:20210809T204741Z
UID:10000419-1621929600-1621954800@www.ieeetoronto.ca
SUMMARY:PD Course - e-lesson #1 - Basics of partial discharges
DESCRIPTION:The course is intended for utility engineers\, both young and senior\, especially those responsible for condition assessment and maintenance of power transformers\, manufacturers of transformers\, transformer components\, monitoring systems\, sensors\, etc.\, students and anyone wishing to understand the scientific foundation of PD measurement\, anyone interested in a deeper awareness of partial discharge measurement and interpretation and staff who are responsible for transformers and want them to be more operational and efficient. \nContact: Ali Naderian \nRegister: Please Register Directly Using Link: https://lnkd.in/dnDybDc \nSpeaker: Stefan Tenbohlen of Stuttgart University \nTopic: Partial Discharge Measurement for Power Transformers- Basics \nBiography: Stefan Tenbohlen (M’04\, S’14) received his Diploma and Dr.-Ing. degrees from the Technical University of Aachen\, Germany\, in 1992 and 1997\, respectively. 1997 he joined ALSTOM Schorch Transformatoren GmbH\, Mönchengladbach\, Germany\, where he was responsible for basic research and product development. From 2002 to 2004\, he was the head of the electrical and mechanical design department. 2004 he was appointed to a professorship and head of the institute of Power Transmission and High Voltage Technology of the University of Stuttgart\, Germany. In this position his main research fields are high voltage technique\, power transmission and electromagnetic compatibility (EMC). Prof. Tenbohlen holds several patents and published more than 400 papers.
URL:https://www.ieeetoronto.ca/event/pd-course-e-lesson-1-basics-of-partial-discharges/
CATEGORIES:Dielectrics & Electrical Insulation
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210521T150000
DTEND;TZID=America/Toronto:20210521T160000
DTSTAMP:20260423T033046
CREATED:20210504T165404Z
LAST-MODIFIED:20210809T204727Z
UID:10000410-1621609200-1621612800@www.ieeetoronto.ca
SUMMARY:The Analog Designer's Toolbox (ADT): Towards A New Paradigm for Analog IC Design
DESCRIPTION:The Circuits & Devices Chapter of IEEE Toronto is pleased to invite you to join us for a virtual talk by Dr. Hesham Omran of Ain Shams University. \nThis event will be a virtual talk held on Zoom. The invitation will be sent to registerants. \nTopic: The Analog Designer’s Toolbox (ADT): Towards A New Paradigm for Analog IC Design \nAbstract: \nThe integrated circuit (IC) technology has witnessed an exponential advancement in the last decades and has changed every aspect in our life. On the other hand\, the analog IC design flow did not experience any major change since the introduction of Berkeley SPICE in the 1970s\, posing significant challenges to the design of complex systems and to the transfer of analog design expertise and knowledge. The Analog Designer’s Toolbox (ADT) is an analog EDA tool that addresses this problem by defining a new paradigm in analog IC design. ADT provides a turnkey solution that enables everyone to reap the benefits of the gm/ID design methodology powered by precomputed lookup tables (LUTs). At the device level\, ADT Device Xplore gives an easy interface to plot arbitrary design charts involving complex expressions. The designer can explore devices from different technologies at different corners and temperatures\, and extract simulator-accurate design points while taking second-order effects into consideration. At the block level\, ADT Design Xplore gives the designer the power of design space exploration\, constraints management\, live tuning\, and optimization\, all in a single cockpit without invoking the simulator. Moreover\, with a single click\, ADT can build the testbenches in the background and report the results from your favorite simulator. The aim of ADT is to boost productivity\, restore designer’s intuition\, and make the design process systematic\, optimized\, and fun! \nSpeaker: Hesham Omran \nBiography: \nDr. Hesham Omran received the B.Sc. (with honors) and M.Sc. degrees from Ain Shams University\, Cairo\, Egypt\, in 2007 and 2010\, respectively\, and the Ph.D. degree from King Abdullah University of Science and Technology (KAUST)\, Saudi Arabia\, in 2015\, all in Electrical Engineering. From 2008 to 2011\, he was a Design Engineer with Si-Ware Systems (SWS)\, Cairo\, Egypt\, where he worked on the circuit and system design of the first miniaturized FT-IR MEMS spectrometer (NeoSpectra)\, and a Research and Teaching Assistant with the Integrated Circuits Lab (ICL)\, Ain Shams University. From 2011 to 2016 he was a Researcher with the Sensors Lab\, KAUST. He held internships with Bosch Research and Technology Center\, CA\, USA\, and with Mentor Graphics\, Cairo\, Egypt. In 2016\, he rejoined the ICL\, Ain Shams University\, as an Assistant Professor. He developed and taught several advanced courses on different topics in the field of IC Design. Most of these courses are available on the Mastering Microelectronics YouTube channel with 4k+ subscribers. He co-founded Master Micro in 2020 to develop the Analog Designer’s Toolbox (ADT)\, a winner of the Egyptian ITIDA-TIEC startup incubation program. \nDr. Hesham has received several awards including the Egyptian State Encouragement Award for Engineering Sciences in 2019\, best paper award from the IEEE International Design and Test Conference in 2009\, and Academic Excellence Awards from KAUST and Ain Shams University in 2011 and 2002\, respectively. He has published 40+ papers in international journals and conferences. He serves as a reviewer for several international journals and conferences including IEEE Transactions on Circuits and Systems (TCAS) I & II\, IEEE Transactions on Instrumentation and Measurement\, and IEEE Transactions on Very Large Scale Integration Systems (TVLSI). His research interests are in the design of analog and mixed-signal integrated circuits\, and especially in analog and mixed-signal CAD tools and design automation. \nEmail: hesham.omran@master-micro.com
URL:https://www.ieeetoronto.ca/event/the-analog-designers-toolbox-adt-towards-a-new-paradigm-for-analog-ic-design/
LOCATION:Virtual – Zoom
CATEGORIES:Circuits & Devices
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210518T200000
DTEND;TZID=America/Toronto:20210518T213000
DTSTAMP:20260423T033046
CREATED:20210506T165446Z
LAST-MODIFIED:20210809T204704Z
UID:10000412-1621368000-1621373400@www.ieeetoronto.ca
SUMMARY:IEEE VDL: Deep Learning for Physical Layer Communications: An Attempt towards 6G
DESCRIPTION:Join us for the IEEE Virtual Distinguished Lecture “Deep Learning for Physical Layer Communications: An Attempt towards 6G” presented by Prof. Feifei Gao of Tsinghua University\, China. \nContact: IEEE Kingston ComSoc Chapter \nAbstract: \nMerging artificial intelligence into the system design has appeared as a new trend in wireless communications areas and has been deemed as one of the 6G technologies. In this talk\, we will present how to apply the deep neural network (DNN) for various aspects of physical layer communications design\, including the channel estimation\, channel prediction\, channel feedback\, data detection\, and beamforming\, etc. We will also present a promising new approach that is driven by both the communications data and the communication models. It will be seen that the DNN can be used to enhance the performance of the existing technologies once there is model mismatch. More interestingly\, we will show that applying DNN can deal with the conventionally unsolvable problems\, thanks to the universal approximation capability of DNN. With the well-defined propagation model in communication areas\, we also attempt to explain the DNN under the scenario of channel estimation and reach a strong conclusion that DNN can always provide the asymptotically optimal channel estimations. We have also build test-bed to show the effectiveness of the AI aided wireless communications. In all\, DNN is shown to be a very powerful tool for communications and would make the communications protocols more intelligently. Nevertheless\, as a new born stuff\, one should carefully select suitable scenarios for applying DNN rather than simply spreading it everywhere. \nBiography: \nProf. Gao’s research interest include signal processing for communications\, array signal processing\, convex optimizations\, and artificial intelligence assisted communications. He has authored/ coauthored more than 150 refereed IEEE journal papers and more than 150 IEEE conference proceeding papers that are cited more than 10000 times in Google Scholar. Prof. Gao has served as an Editor of IEEE Transactions on Wireless Communications\, IEEE Journal of Selected Topics in Signal Processing (Lead Guest Editor)\, IEEE Transactions on Cognitive Communications and Networking\, IEEE Signal Processing Letters\, IEEE Communications Letters\, IEEE Wireless Communications Letters\, and China Communications. He has also serves as the symposium co-chair for 2019 IEEE Conference on Communications (ICC)\, 2018 IEEE Vehicular Technology Conference Spring (VTC)\, 2015 IEEE Conference on Communications (ICC)\, 2014 IEEE Global Communications Conference (GLOBECOM)\, 2014 IEEE Vehicular Technology Conference Fall (VTC)\, as well as Technical Committee Members for more than 50 IEEE conferences.
URL:https://www.ieeetoronto.ca/event/ieee-vdl-deep-learning-for-physical-layer-communications-an-attempt-towards-6g/
LOCATION:Kingston\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org\, Kingston\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org
CATEGORIES:Communications
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210517T010000
DTEND;TZID=America/Toronto:20210517T143000
DTSTAMP:20260423T033046
CREATED:20210430T023731Z
LAST-MODIFIED:20210809T204646Z
UID:10000375-1621213200-1621261800@www.ieeetoronto.ca
SUMMARY:Reconfigurable Intelligent Surfaces: A Signal Processing Perspective
DESCRIPTION:Wireless connectivity is becoming as essential as electricity in our modern world. Although we would like to deliver wireless broadband services everywhere\, the underlying physics makes it inherently complicated: the signal power vanishes very quickly with the propagation distance and is absorbed or scattered when interacting with objects in the way. Even when we have a “strong” signal\, only one in a million parts of the signal energy is being received\, thus\, there is a huge room for improvements! \nWhat if we could tune the propagation environment to our needs? This is the main goal of reconfigurable intelligent surfaces\, which is an emerging concept for beyond-5G communications. The idea is to support the transmission from a source to a destination by deploying so-called metasurfaces that can reconfigure how incident signal waves are scattered. These surfaces can be electronically configured to interact with the wireless signals as if they had different shapes. For example\, it can be configured to behave as a parabolic reflector that is rotated to gather signal energy and re-radiates it as a beam focused on the receiver. This feature makes use of a new design dimension: we can not only optimize the transmitter and receiver but also control the channel. This might be a game-changer when communicating at mmWave and THz frequencies\, where the traditional propagation conditions are particularly cumbersome. \nThis might sound like science fiction but is theoretically possible. In this talk\, Dr. Emil will explain the fundamentals of this new technology from a signal processing perspective. By deriving a signals-and-systems description\, we can look beyond the initial hype and understand what is actually happening when using reconfigurable intelligent surfaces. Dr. Emil will also describe recent experimental validations of the fundamentals. The talk will culminate in a description of the main research challenges that need to be tackled in the coming years. \nThe virtual platform information will be sent to registrants a couple of hours ahead of starting the event. \nContact: IEEE Young Professionals Montreal \nSpeaker: Emil Björnson \nBiography: \nEmil Björnson received the M.S. degree in engineering mathematics from Lund University\, Sweden\, in 2007\, and the Ph.D. degree in telecommunications from the KTH Royal Institute of Technology\, Sweden\, in 2011. From 2012 to 2014\, he held a joint post-doctoral position at the Alcatel-Lucent Chair on Flexible Radio\, SUPELEC\, France\, and the KTH Royal Institute of Technology. He joined Linköping University\, Sweden\, in 2014\, where he is currently an Associate Professor. In September 2020\, he became a part-time Visiting Full Professor at the KTH Royal Institute of Technology. \nHe has authored the textbooks Optimal Resource Allocation in Coordinated Multi-Cell Systems (2013)\, Massive MIMO Networks: Spectral\, Energy\, and Hardware Efficiency (2017)\, and Foundations of User-Centric Cell-Free Massive MIMO (2021). He is dedicated to reproducible research and has made a large amount of simulation code publicly available. He performs research on MIMO communications\, radio resource allocation\, machine learning for communications\, and energy efficiency. He has been on the Editorial Board of the IEEE Transactions on Communications since 2017. He has been a member of the Online Editorial Team of the IEEE Transactions on Wireless Communications since 2020. He has been an Area Editor in IEEE Signal Processing Magazine since 2021. \nHe has performed MIMO research for over 14 years\, his papers have received more than 12000 citations\, and he has filed more than twenty patent applications. He is a host of the podcast Wireless Future and has a popular YouTube channel. He has received the 2014 Outstanding Young Researcher Award from IEEE ComSoc EMEA\, the 2015 Ingvar Carlsson Award\, the 2016 Best Ph.D. Award from EURASIP\, the 2018 IEEE Marconi Prize Paper Award in Wireless Communications\, the 2019 EURASIP Early Career Award\, the 2019 IEEE Communications Society Fred W. Ellersick Prize\, the 2019 IEEE Signal Processing Magazine Best Column Award\, the 2020 Pierre-Simon Laplace Early Career Technical Achievement Award\, and the 2020 CTTC Early Achievement Award. He also co-authored papers that received Best Paper Awards at the conferences\, including WCSP 2009\, the IEEE CAMSAP 2011\, the IEEE SAM 2014\, the IEEE WCNC 2014\, the IEEE ICC 2015\, and WCSP 2017.
URL:https://www.ieeetoronto.ca/event/reconfigurable-intelligent-surfaces-a-signal-processing-perspective/
LOCATION:Montreal\, Quebec Canada
CATEGORIES:Young Professionals
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210514T110000
DTEND;TZID=America/Toronto:20210514T120000
DTSTAMP:20260423T033046
CREATED:20210504T165404Z
LAST-MODIFIED:20210809T204633Z
UID:10000279-1620990000-1620993600@www.ieeetoronto.ca
SUMMARY:ComSoc Distinguished Lecture: AI to Enable Digital Medicine and Detect COVID-19
DESCRIPTION:The IEEE Ottawa Joint Chapter of Communications Society\, Consumer Electronics Society\, and Broadcast Technology Society (ComSoc/CESoc/BTS)\, IEEE Toronto Chapter (ComSoc/BTS)\, IEEE ComSoc Montreal Chapter (ComSoc)\, IEEE Ottawa Educational Activities (EA)\, IEEE Ottawa Women In Engineering (WIE)\, IEEE Ottawa Young Professionals (YP)\, and Algonquin College Student Branch (ACSB) in conjunction with School of Advanced Technology\, Algonquin College are inviting all interested IEEE members and other engineers\, technologists\, and students to ComSoc Distinguished Lecture (webinar) on AI to Enable Digital Medicine and Detect COVID-19. \nFor any additional information please contact: Wahab Almuhtadi or Eman Hammad \nAbstract: \nDigitalize human beings using biosensors to track our complex physiologic system\, process the large amount of data generated with artificial intelligence (AI) and change clinical practice towards individualized medicine: these are the goals of digital medicine. In this talk\, we discuss how to design AI solutions in the clinical space and what are the key aspects to make a difference. We focus on two critical clinical topics that need AI: 1) atrial fibrillation (AF)\, and 2) viral illnesses (COVID-19). AF is the most common sustained cardiac arrhythmia\, associated with stroke\, heart failure and coronary artery disease. AF detection from single-lead electrocardiography (ECG) recordings is still an open problem\, as AF events may be episodic and the signal noisy. We conduct a thoughtful analysis of recent convolutional neural network architectures developed in the computer vision field\, redesigned to be suitable for a one-dimensional signal\, and we evaluate their performance in the detection of AF using 200 thousand seconds of ECG\, highlighting the potential and pitfall of this technology. We also discuss how to explain (global and local post hoc explanations) this AI model for AF detection using features that are commonly used by a cardiologist. \nTo tackle the problem of COVID-19\, we start with an overview of continuous\, passively monitored vital signs from 200\,000 individuals wearing a Fitbit wearable device for 2 years. This large study provides the baseline for DETECT\, our app-based\, nationwide clinical study enrolling individuals who routinely use a smartwatch or other wireless devices to determine if individualized tracking of changes in heart rate\, activity and sleep can provide early diagnosis and self-monitoring for COVID-19. We analyze data from more than 36\,000 individuals\, showing how we can discriminate (on an individual level) between COVID-19 and other types of infections. We discuss how this can impact both the individual and public health\, and how the use of AI can be a game changer in this fight against the virus. \nSpeaker: Giorgio Quer \nGiorgio Quer is the Director of Artificial Intelligence at the Scripps Research Translational Institute\, where he is leading the Data Science and Analytics team within the All of Us Research Program’s Participant Center (NIH). \nHis research focuses on artificial intelligence and probabilistic modeling applied to heterogeneous data signals\, in order to extract key information and make predictions on future occurrences based on past data. He is involved in several digital medicine initiatives within the Scripps Research Digital Trials Center. For the DETECT study\, he is developing algorithms to predict COVID-19 and other viral infections from wearable sensor data. He is responsible for collaborations with several industry partners\, studying changes in heart rate and sleep data monitored by commercial wearable devices. He is also interested in the detection and modeling of atrial fibrillation from single-lead ECG signals. He is leading the collaboration with the Halicioglu Data Science Institute at UC San Diego towards the development of new AI models for health data. \nHe received his Ph.D. degree in Information Engineering from the University of Padova\, Italy\, and he continued his studies as a Postdoctoral researcher with the Qualcomm Institute at the University of California San Diego. He is a Senior Member of the IEEE and a Distinguished Lecturer for the IEEE Communications society.
URL:https://www.ieeetoronto.ca/event/comsoc-distinguished-lecture-ai-to-enable-digital-medicine-and-detect-covid-19/
LOCATION:Virtual – Zoom
CATEGORIES:Communications
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210513T160000
DTEND;TZID=America/Toronto:20210513T180000
DTSTAMP:20260423T033046
CREATED:20210506T165445Z
LAST-MODIFIED:20210809T204621Z
UID:10000411-1620921600-1620928800@www.ieeetoronto.ca
SUMMARY:Electromagnetics Alumni Event
DESCRIPTION:We are inviting several alumni members from the electromagnetics group\, University of Toronto\, Canada who are working in industry at senior positions and in academia as Professors to provide an insight on career choices after graduation. We are planning it as a semi-formal event where the speakers would share their experiences and the attendees could ask them questions. \nZoom link will be provided to the registered participants. \nContact: IEEE UofT AP-S Student Chapter \nPanelists: \n\nDr. Michael Selvanayagam\, IBM T.J. Watson Research Center\, NY\nDr. Rubaiyat Islam\, AMD\, Canada\nDr. Marco Antoniades\, Ryerson University\, Canada\nDr. Loic Markley\, University of British Columbia\, Canada\nDr. Utkarsh Patel\, AMD Canada
URL:https://www.ieeetoronto.ca/event/electromagnetics-alumni-event/
LOCATION:Virtual – Zoom
CATEGORIES:Electromagnetics & Radiation
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210510T130000
DTEND;TZID=America/Toronto:20210510T150000
DTSTAMP:20260423T033046
CREATED:20210430T023731Z
LAST-MODIFIED:20210809T204608Z
UID:10000374-1620651600-1620658800@www.ieeetoronto.ca
SUMMARY:The Role of AI in 5G/6G and IoT-Enabled Smart Grids
DESCRIPTION:IEEE Young Professionals brings speakers from Canadian research groups to give the community technical talks in AI-Powered Wireless Communications and Intelligent Cyber Physical Analysis in IoT-Enabled Smart Grids. \nThe virtual platform information will be sent to registrants a couple of hours ahead of starting the event. \nContact: IEEE Young Professionals Montreal \nSpeakers: \nDr. Melike Erol-Kantarci of University of Ottawa\nTopic: AI-Enabled Wireless Networks: A Bridge from 5G to 6G \nAbstract: \nFuture wireless networks are expected to support a multitude of services demanded by Enhanced Mobile Broadband (eMBB)\, Ultra-Reliable and Low-latency Communications (uRLLC)\, and massive Machine Type Communications (mMTC) users. Heterogeneous devices with different quality of service (QoS) demands will require intelligent and flexible allocation of network resources in response to network dynamics. For instance\, a highly reliable and low-latency network is needed to enable rapid transfer of messages between connected autonomous vehicles. At the same time\, the same physical infrastructure is expected to serve users with high-quality video demand or even mobile Augmented/Virtual Reality entertainment applications. Next-generation wireless networks are expected to accommodate such diverse use cases. In addition\, resource efficiency\, reliability\, and robustness are becoming more stringent for 5G and beyond networks. To meet this\, future wireless networks must incorporate a paradigm shift in network resource optimization\, in which efficient and intelligent resource management techniques are employed. Artificial intelligence\, or more specifically machine learning algorithms stand as promising tools to intelligently manage the networks such that network efficiency\, reliability\, robustness goals are achieved and quality of service demands are satisfied. The opportunities that arise from learning the environment parameters under varying behavior of the wireless channel\, positions AI-enabled 5G and 6G\, superior to preceding generations of wireless networks. In this keynote\, we will provide an overview of the state-of-art in machine learning algorithms and their applications to wireless networks\, in addition to their challenges and the open issues in terms of their applicability to various functions of future wireless networks. \nBiography: \nMelike Erol-Kantarci is Canada Research Chair in AI-enabled Next-Generation Wireless Networks and Associate Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa. She is the founding director of the Networked Systems and Communications Research (NETCORE) laboratory. She is a Faculty Affiliate at the Vector Institute\, Toronto\, and the Institute for Science\, Society and Policy at University of Ottawa. She has over 150 peer-reviewed publications which have been cited over 5500 times and she has an h-index of 38. She has received numerous awards and recognitions. Recently\, she received the 2020 Distinguished Service Award of the IEEE ComSoc Technical Committee on Green Communications and Computing. She was named as N2Women Stars in Computer Networking and Communications in 2019. Dr. Erol-Kantarci has delivered 50+ keynotes\, tutorials and panels around the globe and has acted as the general chair and technical program chair for many international conferences and workshops. Her main research interests are AI-enabled wireless networks\, 5G and 6G wireless communications\, smart grid and Internet of things. She is an IEEE ComSoc Distinguished Lecturer\, IEEE Senior member and ACM Senior Member \nHadis Karimipour \nTopic: Intelligent Cyber Security Analysis in IoT-Enabled Smart Grids \nAbstract: \nToday’s smart grids are complex Cyber-physical Systems (CPSs) that integrate computational and physical capabilities for controlling and managing the ever-growing number of cyber-connected devices. \nAside from a fault in the physical domain\, CPS also suffer from cyber-attacks in both cyber and physical domain e.g.\, an industrial controller can be manipulated to launch various attacks such as the device state inference attack\, leading to system instability. Therefore\, any effort to secure the emerging critical CPSs is of paramount importance.  Nowadays\, a cyber-security specialist must detect\, analyze\, and defend against many cyber threats in almost real-time conditions. Without the employment of artificial intelligence and machine learning techniques\, dealing with a huge number of attacks in a timely manner is not possible. Intelligent\, big-data analytical techniques are necessary to mine\, interpret and extract knowledge of data when there is a significant amount collected from or generated by different security monitoring solutions. This talk will go through the CPS security challenges and AI-enabled state of the art solution in the literature. \nBiography: \nDr. Hadis Karimipour is the director of the Smart Cyber-physical System (SCPS) Lab and an Assistant Professor in the School of Engineering at the University of Guelph. She is among the pioneers of using Machine Learning (ML) for security analysis of critical infrastructure. She has published more than 80 journal articles\, conference papers and book chapters in top IEEE journals and conferences. She has been a keynote/invited speaker for more than 20 different IEEE/International Conference. She was the chair of the IEEE workshop on AI for Securing Cyber-Physical System (AI4SCPS) at IEEE CCECE 2019 and IEEE CyberSciTech 2020 conferences and chair of the special session on the AI for Security of IoT-Enabled Critical Infrastructures at the IEEE SMC 2020 conference. She was the technical committee member of numerous IEEE conferences\, including IEEE SEGE 2018\, 2019\, 2020\, IEEE DSAA 2020\, PST 2020\, IEEE EPEC 2018\, 2020\, and IEEE SMC 2020.\nDr. Karimipour is the Associate Editor of the Frontiers in Communications and Networks Journal\, Editor of American Journal of Electrical and Electronic Engineering\, and Editor of Journal of Electrical Engineering. She has also served as Guest Editor for Elsevier Journal of Computer and Electrical Engineering. She was the Editor of the Springer book on Security of Cyber-physical System. Dr. Karimipour is a Senior Member of IEEE member\, chair of IEEE Women in Engineering and chapter chair of the IEEE Information Theory Kitchener-Waterloo Section\, and an active member of Society for Canadian Women in Science and Technology.
URL:https://www.ieeetoronto.ca/event/the-role-of-ai-in-5g-6g-and-iot-enabled-smart-grids/
LOCATION:Montreal\, Quebec Canada
CATEGORIES:Women in Engineering,Young Professionals
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210508T100000
DTEND;TZID=America/Toronto:20210508T140000
DTSTAMP:20260423T033046
CREATED:20210520T161919Z
LAST-MODIFIED:20210809T204512Z
UID:10000414-1620468000-1620482400@www.ieeetoronto.ca
SUMMARY:IEEE AESS Chapter Summit - Regions 1-7
DESCRIPTION:Growth through engagement and teamwork \n\n\n \nThe IEEE AESS Chapter Summit brings together IEEE Aerospace & Electronic Systems Society chapter officers from across the US and Canada. Local volunteer leaders play a key role in engaging and serving our local members and advancing our technical interests in the complex systems of air\, space\, ocean and ground environments. \nTraining\, motivation\, and inspiration from sharing best practices are all on the agenda. \nPlease contact k.kramer@ieee.org for registration and connection information.
URL:https://www.ieeetoronto.ca/event/ieee-aess-chapter-summit-regions-1-7/
CATEGORIES:Aerospace & Electronic Systems
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210426T180000
DTEND;TZID=America/Toronto:20210430T210000
DTSTAMP:20260423T033046
CREATED:20210430T023730Z
LAST-MODIFIED:20210615T004303Z
UID:10000373-1619460000-1619816400@www.ieeetoronto.ca
SUMMARY:A Short Course in “Electrical Power Substations- Planning\, Design\, Construction & Project Management”
DESCRIPTION:The Education Committee of the IEEE Toronto Section is offering a short course in “Electrical Power Substations- Planning\, Design\, Construction & Project Management” in April 2021 to develop an understanding of the practical applications of Power Substations Planning process\, Design aspects\, Substation Components\, Construction practices\, Commissioning & testing procedures and relevant Project Management techniques. This is the 2nd series after successful completion of earlier course delivered on “Power System Engineering\, Operation and Management” to develop an overall understanding of power system engineering and technologies in the fields of generation\, transmission and distribution. \nWhat will you receive after completion:  “Certificate of Completion” along with CEUs and PDH (After completing & passing a short exam and evaluation); Course Materials in electronic Format; Continuous support on career advice\, resume building and skills development. \nCourse Timetable: \n\nMonday\, April 26\, 2021: 6.00 PM to 9.00 PM\nTuesday\, April 27\, 2021: 6.00 PM to 9.00 PM\nWednesday\, April 28\, 2021: 6.00 PM to 9.00 PM\nThursday\, April 29\, 2021: 6.00 PM to 9.00 PM\nFriday\, April 30\, 2021: 6.00 PM to 9.00 PM\n\nSpeaker(s): \n\nSatish Saini\, Topic: Opening & Overall Course Introduction & Course Chair)\nHemant Barot\, Topic: Electrical Power Substations- Planning\, Design\, Construction & Project Management\n\nLocation: Due to current COVID-19 restrictions- This course will be delivered On-Line (Virtual). Link and relevant details to join will be provided to all registered attendees / participants before the course. \nOrganizer(s): Education Committee\, IEEE Toronto Section \nContact: Satish Saini \nRegister: Please visit https://events.vtools.ieee.org/m/261750 to register and for more information. \nAdmission Fees: \n\nNon-IEEE Members: $300 CAD + GST/HST\nIEEE Members: $250 CAD + GST/HST\n\nCourse Outline: \n\nDay 1: Power system overview & segments; Ontario’s power system\, supply mix & energy market\nDay 2: Power System Planning process & Design concepts\nDay 3: Power Sub-stations Components\, layout & functionalities\nDay 4: Substations Bus Bar layout\, configuration & categories\nDay 5: Electrical Substations construction\, Project Management\, actual case study & substations visuals (in place of site visit which has to be canceled due to COVID-19 restrictions)\nCourse Test/Exam\n\nBiographies: \nSatish Saini \nSatish is a Licensed Professional Engineer registered with Professional Engineers Ontario with 35 years of accomplished management experience in various fields of energy and power. Electrical utility operations and management\, business development and project management related to DS grid modernisation\, renewable energy\, smart metering / AMI\, Advanced Distribution System (ADS) / Smart Grid\, DSM and DMS. Actively participated in the development of various energy policies with ministries\, regulatory authorities\, utilities and local distribution companies. He is an active member of IEEE in various committees\, Task Forces and Working Groups related to Smart Distribution\, Smart Grid\, MicroGrids and Smart Cities. Current Chair of IEEE Smart Grid Technical Activities Committee and Chair of Education Committee IEEE Toronto Section. Has a strong vision of developing the aging DS Grid with latest innovative technologies and solutions along with transforming utilities through smart grid programs \nEmail: s.saini@ieee.org \nHemant Barot \nHemant Barot has a PhD in Power System Operation & Planning and is a certified Professional Engineer licensed in the Province of Ontario Canada and a Project Management Professional. His diverse work experience includes working with Utility\, Research and Academic Institutes and Original Power Equipment Manufacturers. His experience includes working as a Senior Engineer in Transmission system Planning\, Project Planning and Estimation as well as roles in Project Management\, Conceptual Engineering and Academics.
URL:https://www.ieeetoronto.ca/event/a-short-course-in-electrical-power-substations-planning-design-construction-project-management/
LOCATION:Toronto\, Canada
CATEGORIES:Education
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210416T120000
DTEND;TZID=America/Toronto:20210416T130000
DTSTAMP:20260423T033046
CREATED:20210430T023730Z
LAST-MODIFIED:20210809T204407Z
UID:10000372-1618574400-1618578000@www.ieeetoronto.ca
SUMMARY:CAS Distinguished Lecture - Augmented Perception: Next Generation Wearables and Human-Machine Interfaces
DESCRIPTION:The Circuits & Devices Chapter of IEEE Toronto is pleased to invite you to join us for a virtual talk by Distinguished Lecturer Dr. Andrew Mason of the Michigan State University. \nTopic: Augmented Perception: Next Generation Wearables and Human-Machine Interfaces \nAbstract: \nProducts like Fitbit and the Apple Watch have brought to the public decades of foundational work on wearable technologies achieved by researchers in the IEEE CAS Society and related groups. Similarly\, research into brain- and human-machine interface is starting to enter the public domain in applications including deep brain stimulation\, prosthetic limb control\, and human assistive devices. While researchers continue to explore new wearable sensing and human-interface paradigms\, it is vital that we also explore what applications the next generation of wearable human-machine interfaces can and should enable. This talk will review key challenges and approaches within wearable assistive device and brain/human interface technologies. Aspects of physiological\, environmental\, and behavioral sensing within wearable platforms will be discussed\, and technical challenges will be highlighted. Finally\, the next generation concept of augmented human perception\, real time machine-enhanced awareness that expands natural human senses\, will be introduced. Utilizing wearable sensing and real-time feedback through visual\, audio and tactile mechanism\, augmented perception is poised to revolutionize the human experience\, enhance daily performance\, and enable new pathways to address mental and physical health concerns. \nSpeaker: Andrew Mason of Michigan State University \nBiography: \nAndrew J. Mason received the BS in Physics with highest distinction from Western Kentucky University in 1991\, the BSEE with honors from the Georgia Institute of Technology in 1992\, and the MS and Ph.D. in Electrical Engineering from The University of Michigan\, Ann Arbor in 1994 and 2000\, respectively. From 1999 to 2001 he was an Assistant Professor at the University of Kentucky.  In 2001 he joined the Department of Electrical and Computer Engineering at Michigan State University in East Lansing\, Michigan\, where he is currently a Professor.  His research explores mixed-signal circuits\, microfabricated structures and machine learning algorithms for integrated microsystems in biomedical\, environmental monitoring and sustainable lifestyle applications.  Current projects are focused on design of augmented human awareness systems including signal processing algorithms and hardware for brain-machine interface\, wearable/implantable biochemical and neural sensors\, and lab-on-CMOS integration of sensing\, instrumentation\, and microfluidics. \nDr. Mason is a Senior Member of the Institute of Electrical and Electronic Engineers (IEEE) and serves on the Sensory Systems and Biomedical Circuits and Systems Technical Committees of the IEEE Circuits and Systems Society. He is an Associate Editor for the IEEE Trans. Biomedical Circuits and Systems and regularly serves on the technical and review committees for several IEEE conferences. Dr. Mason was co-General Chair of the 2011 IEEE Biomedical Circuits and Systems Conference. He is a recipient of the 2006 Michigan State University Teacher-Scholar Award and the 2010 Withrow Award for Teaching Excellence. \nEmail: mason@msu.edu
URL:https://www.ieeetoronto.ca/event/cas-distinguished-lecture-augmented-perception-next-generation-wearables-and-human-machine-interfaces/
LOCATION:Virtual – Zoom
CATEGORIES:Circuits & Devices
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210413T190000
DTEND;TZID=America/Toronto:20210413T200000
DTSTAMP:20260423T033046
CREATED:20210430T023729Z
LAST-MODIFIED:20210504T201634Z
UID:10000371-1618340400-1618344000@www.ieeetoronto.ca
SUMMARY:IEEE VT Chapter Women in Engineering Series
DESCRIPTION:On April 13\, 2021 at 7:00 p.m.\, Dr. Fatima Hussain will present the talk “Insider Threat and Behaviour Modelling/Professional Career Development Discussions”. \nDate: Tuesday\, April 13\, 2021 \nTime: 7:00-8:00pm \nSpeaker(s): Dr. Fatima Hussain\, Senior Member\, IEEE\,\nManager\, Event Management and Analytics\, User Behaviour Analytics and Insider Threat\, Global Cyber Security\, Royal Bank of Canada\, Toronto\nAdjunct Professor\, Ryerson University\, Toronto \nLocation: All events are held with Zoom Meeting\nhttps://ryerson.zoom.us/j/96808290854\nMeeting ID: 968 0829 0854 \nOrganizer(s): IEEE VT Chapter \nContact: Lian Zhao \nAbstract: In the first half of the talk\, discussion about behaviour modelling and insider threat is done. Insider threat classification and related threat vectors are discussed in detail. Afterwards\, various methods used for identification and remediation of insider threat are presented\, along with cutting edge enterprise level tools and frameworks.In the second half of the talk\, we will have on-live discussions for professional caree rdevelopment\, through experience sharing and opinion sharing\, to encourage and guide young researchers career development plan\, and to motivate women career development in engineering. \nBiography: Fatima Hussain received the Ph.D. and M.A.Sc. degrees in Electrical and Computer engineering from Ryerson University\, Toronto\, ON\, Canada. Upon graduation\, she was a Postdoctoral Fellow with the Network-Centric Applied Research Team (N-CART)\, where she worked on various NSERC-funded projects in the realm of the Internet of Things. Currently\, she is part of User Behaviour and Insider Threat team \,working as a Manager\, Event Management and Analytics in Royal Bank of Canada (RBC)\, Toronto.She is responsible foremployee profiling and detection of insider threats\, by establishing baseline behaviours. She is working as an editor for IEEE Newsletter (Toronto)\, and associate editor for various journals. She is also an Adjunct Professor with Ryerson University and her role includes supervision of graduate research projects. Her research interests include cyber security\,insider threat\, XAI etc. Her background includes a number of distinguished professorships with Ryerson University and University of Guelph\, where she has been awarded for her research\, teaching\, and course development accomplishments within wireless telecommunication and Internet of Things.
URL:https://www.ieeetoronto.ca/event/ieee-vt-chapter-women-in-engineering-series/
CATEGORIES:Vehicular Technology,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210331T193000
DTEND;TZID=America/Toronto:20210331T210000
DTSTAMP:20260423T033046
CREATED:20210430T023728Z
LAST-MODIFIED:20210809T204329Z
UID:10000370-1617219000-1617224400@www.ieeetoronto.ca
SUMMARY:EDS Distinguished Lecture - Self-Heating in FinFETs: Characterization\, Reliability and Impact on Logic Circuits
DESCRIPTION:The Circuits & Devices Chapter of IEEE Toronto is pleased to invite you to join us for a virtual talk by Distinguished Lecturer Dr. Durga Misra of the New Jersey Institute of Technology. \nPlease see below for schedule and details. \nTopic: Self-Heating in FinFETs: Characterization\, Reliability and Impact on Logic Circuits \nAbstract: \nDevice scaling for sub-10 nm CMOS technology has introduced bulk/SOI FinFETs This talk will outline the self-heating (SH) in FinFETs and its characterization. Local self-heating can potentially affect device performance and exacerbate the effects of some reliability mechanisms. Three different measurement methodologies for the electrical characterization of FinFET self-heating at wafer-level will be described. Also\, the impact of self-heating on reliability testing at DC conditions as well as realistic CMOS logic operating (AC) conditions will be discussed. Front-end-of-line (FEOL) reliability mechanisms\, such as hot carrier injection (HCI) and non-uniform time dependent dielectric breakdown (TDDB) will also be outlined. Self-heating is also studied at more realistic device switching conditions in logic circuits by utilizing ring oscillators with several densities and stage counts. The measurements indicate that self-heating is considerably lower in logic circuits compared to constant voltage stress conditions and degradation is not distinguishable. \nSpeaker: Prof. Durga Misra\, Department of Electrical and Computer Engineering\, New Jersey Institute of Technology \nBiography: \nProf. Durga Misra is a Professor in the Department of Electrical and Computer Engineering\, New Jersey Institute of Technology\, Newark\, USA. His current research interests are in the areas of nanoelectronic/optoelectronic devices and circuits; especially in the area of nanometer CMOS gate stacks and device reliability. He is a Fellow of IEEE and is currently a Distinguished Lecturer of IEEE Electron Devices Society (EDS) and served in the IEEE EDS Board of Governors. He is a Fellow of the Electrochemical Society (ECS). He received the Thomas Collinan Award from the Dielectric Science & Technology Division of ECS. He is also the winner of the Electronic and Photonic Division Award from ECS. He edited and co-edited more than 45 books and conference proceedings in his field of research. He has published more than 200 technical articles in peer reviewed Journals and in International Conference proceedings including 95 Invited Talks. He has graduated 19 PhD students and 40 MS students. He received the M.S. and Ph.D. degrees in electrical engineering from the University of Waterloo\, Waterloo\, ON\, Canada\, in 1985 and 1988\, respectively.
URL:https://www.ieeetoronto.ca/event/eds-distinguished-lecture-self-heating-in-finfets-characterization-reliability-and-impact-on-logic-circuits/
LOCATION:Toronto\, Ontario Canada
CATEGORIES:Circuits & Devices
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210330T190000
DTEND;TZID=America/Toronto:20210330T200000
DTSTAMP:20260423T033046
CREATED:20210430T023728Z
LAST-MODIFIED:20210504T203914Z
UID:10000369-1617130800-1617134400@www.ieeetoronto.ca
SUMMARY:VT Chapter Rising Star Talks: Content Caching and Delivery in Heterogeneous Vehicular Networks
DESCRIPTION:The IEEE Toronto Vehicular Technology Chapter is hosting two talks as part of their Rising Star Series! Haixia Peng and Huaqing Wu are at their final stages of their PhD studies at the University of Waterloo. They will share their research on mobile edge computing/caching/ communication\, network slicing\, Artificial Intelligence (AI) enabled IoV networks\, and integrated space-air-ground vehicular networks during their PhD studies. \nLocation: All events are held with Zoom Meeting\nhttps://ryerson.zoom.us/j/96808290854\nMeeting ID: 968 0829 0854 \nContact: Please contact Lian Zhao at l5zhao@ryerson.ca for any questions \nThe details of each talk are below. \nIntelligent Multi-Dimensional Resource Slicing in MEC-Assisted Vehicular Networks\nDate & Time: Tuesday\, March 16\, 2021\n7:00 p.m. – 8:00 p.m. \nSpeaker: Haixia Peng\, University of Waterloo \nAbstract: Benefiting from advances in the automobile industry and wireless communication  technologies\, the vehicular network has been emerged as a key enabler of intelligent  transportation services. However\, with more and more services and applications\, mobile data  traffic generated by vehicles has been increasing and the issue of the overloaded computing task  has been getting worse. Because of the limitation of spectrum resources and vehicles’ onboard  computing/caching resources\, it is challenging to promote vehicular networking technologies to  support the emerged services and applications\, especially those requiring sensitive delay and  diverse resources. To effectively address the above challenges\, two potential technologies\, multi access edge computing (MEC) and unmanned aerial vehicle (UAV)\, can be exploited in  vehicular networks. In this presentation\, I will introduce how to adopt optimization and AI technologies for efficient resource slicing\, and therefore supporting various applications with  satisfied quality of service (QoS) requirements in MEC- and/or UAV-assisted vehicular  networks. For a relatively simple vehicular network scenario with only terrestrial MEC servers\, a  model-based method is applied for dynamic spectrum management\, including spectrum slicing\,  spectrum allocating\, and transmit power controlling. For a vehicular network supported by both  terrestrial and aerial MEC servers\, an AI-based method is applied to effectively manage the  spectrum\, computing\, and caching resources while satisfying the QoS requirements of different  applications. \nBiography: \n\nHaixia Peng received her M.S. and Ph.D. degrees in Electronics and  Communication Engineering and Computer Science from Northeastern University\, Shenyang\,  China\, in 2013 and 2017\, respectively. She is currently a Ph.D. student in the Department of  Electrical and Computer Engineering at the University of Waterloo\, Canada. Her current  research focuses on Internet of vehicles\, resource management\, multi-access edge computing\,  and reinforcement learning. She has authored or co-authored more than 30 technical papers.  She serves/served as a reviewer for IEEE Journals on Selected Areas in Communications (JSAC)\,  IEEE Transactions on Communications\, IEEE Transactions on Vehicular Technologies\, etc. more  than 20 prestigious journals\, and as a TPC member in IEEE ICC\, Globecom\, VTC\, etc.  conferences. \nContent Caching and Delivery in Heterogeneous Vehicular Networks\nDate & Time: Tuesday\, March 30\, 2021\n7:00 p.m. – 8:00 p.m. \nSpeaker: Huaqing Wu\, University of Waterloo \nAbstract: Connected and automated vehicles (CAVs)\, which enable information exchange and  content delivery in real time\, are expected to revolutionize current transportation systems.  However\, the emerging CAV applications such as content delivery pose stringent requirements on  latency\, throughput\, and global connectivity. To empower multifarious CAV content delivery\,  heterogeneous vehicular networks (HetVNets)\, which integrate the terrestrial networks with aerial  networks and space networks\, can guarantee reliable\, flexible\, and globally seamless service  provisioning. In addition\, edge caching can facilitate content delivery by caching popular files in  the HetVNet access points (APs) to relieve the backhaul traffic with a lower delivery delay. In this  talk\, we investigate the content caching and delivery schemes in the caching-enabled HetVNet.  First\, we study the content caching in terrestrial HetVNets with intermittent network connections.  A coding-based caching scheme is designed and a matching-based content placement algorithm is  proposed to minimize the content delivery delay. Second\, UAV-aided caching is considered to  assist vehicular content delivery in aerial-ground vehicular networks (AGVN) and a joint caching  and trajectory optimization (JCTO) problem is investigated to jointly optimize content caching\,  content delivery\, and UAV trajectory. To enable real-time decision-making in highly dynamic  vehicular networks\, we propose a deep supervised learning scheme to solve the JCTO problem.  Third\, we investigate caching-assisted cooperative content delivery in space-air-ground integrated  vehicular networks (SAGVNs)\, where the vehicle-to-AP association\, bandwidth allocation\, and  content delivery ratio are jointly optimized. To address the tightly coupled optimization variables\,  we propose a load- and mobility-aware cooperative delivery scheme to solve the joint optimization  problem with the consideration of user fairness\, load balancing\, and vehicle mobility. \nBiography: \n\nHuaqing Wu received the B.E. and M.E. degrees in Electrical Engineering  from Beijing University of Posts and Telecommunications\, Beijing\, China\, in 2014 and 2017\,  respectively. She is currently working toward the Ph.D. degree at the Department of Electrical and  Computer Engineering\, University of Waterloo\, Waterloo\, ON\, Canada. Her current research  interests include vehicular networks with emphasis on edge caching\, wireless resource  management\, space-air-ground integrated networks\, and application of artificial intelligence (AI)  for wireless networks. She has authored/co-authored more than 30 technical papers which are  published in prestigious refereed journals (IEEE JSAC\, TWC\, WCM\, etc.) and conferences (IEEE  ICC\, Globecom\, VTC\, etc.).
URL:https://www.ieeetoronto.ca/event/vt-chapter-rising-star-talks-content-caching-and-delivery-in-heterogeneous-vehicular-networks/
CATEGORIES:Vehicular Technology
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