IEEE Toronto Section

Integrated Access and Backhaul for 5G and Beyond
2021-07-30 12:00 - 13:30 (America/Toronto) | Virtual – Zoom
Note: Virtual platform will be delivered to registrants a couple of hours before starting the event.
Contact: IEEE Montreal Section Young Professionals
Abstract: The number of devices requesting for wireless communications is growing exponentially. Network densification via the deployment of many base stations (BSs) of different types is one of the mechanisms that can be employed to satisfy the ever-increasing demand for bandwidth/capacity in wireless networks. However, deploying fiber to the small cells may be expensive and impractical when the number of small cells increases. For this reason, as well as because of the traffic jams and infrastructure displacements caused by fiber optic installation, millimeter wave (mmw)-based wireless backhaul is currently considered as an alternative, providing (almost) the same rate as fiber optic with significantly less price and no digging. With this background, integrated access and backhaul (IAB) networks, where the operator can utilize part of the radio resources for wireless backhauling, has recently received considerable attention. The purpose of IAB is to replace existing backhaul systems with flexible wireless backhaul using the existing 3GPP bands providing not only backhaul but also existing cellular services in the same node. This creates more flexibility and reduces the implementation cost. For 5G NR, IAB is currently considered as a work item in 3GPP, and it is known as one of the main novelties of 5G. In this talk, we review the main backhauling techniques, and present the main motivations/standardization agreements on IAB. Moreover, We present comparisons between the IAB networks and the cases where all or part of the small access points are fiber-connected. Finally, we study the robustness of IAB networks to environmental effects and verify the effect of the blockage, the tree foliage, the rain as well as the antenna height/gain on the coverage rate of IAB setups, as the key differences between the fiber-connected and IAB networks. As we show, IAB is an attractive setup enabling 5G and beyond.

Flexible Radio Access Beyond 5G: A Future Projection
2021-07-26 12:00 - 13:30 UTC | Atlanta, Georgia, United States, Virtual: https://events.vtools.ieee.org/m/277084
Dr Arslan has graciously offered to continue the discussion on 5G technologies. The topic is Flexible Radio Access Beyond 5G: A Future Projection.
Abstract:
Today’s wireless services and systems have come a long way since the rollout of the conventional voice-centric cellular systems. The demand for wireless access in voice and multi-media applications has increased tremendously. The trend on the variety and the number of mobile devices along with the mobile applications will certainly continue beyond 5G, creating a wide range of technical challenges. One of the biggest challenges is the security of the communication beyond the classical crypto based approaches which secure the information. In this talk, security aspects of the physical communication and also physical signal which is called Physical Layer Security (PHY Security) will be discussed. Latest trends, threats, and techniques to improve the security of the physical signal will be discussed. The tentative outline of the talk will be as follows:

Wireless Communication trends, requirements
Importance of secure communication
Classification of communication security
PHY security: Communication and REM
PHY security: Eavesdropping, Spoofing & Jamming
Anti-jamming capable communication
Cross-layer security – Secure communication & other advanced radio access technologies

Case- studies
a- Security in URLLC (URLL & Secure communication)
b- Security in vehicular network (V2V and V2I)
c- Security in NOMA d- Security in LIS
Speaker(s): Dr. Arslan Arslan

Sustainable Service Pricing in Cloud Ecosystems
2021-07-26 12:00 - 13:00 UTC | Toronto, Ontario, Canada, Virtual: https://events.vtools.ieee.org/m/276942
Energy efficiency, which has emerged as a top priority in cloud ecosystems, is the outcome of appropriate pricing mechanisms and resource allocations. Static pricing mechanisms are the most dominant approach among all the others. They are simple to implement for the service providers and easy to understand for the service users. Inaccurate price calculation and low efficient resource allocation in static pricing mechanisms made researchers discover other solutions to overcome these issues. Double auction mechanisms are among the most appropriate dynamic models. The main challenge of conventional double auction mechanisms is not considering the cloud ecosystems’ specifications, such as dynamic online features. The term dynamic refers to the many variable parameters in cloud ecosystems, and they constantly change. Conventional static offline pricing solutions are set based on a series of parameters before running the process. In dynamic online methods, we customize our pricing models based on dynamic and current parameters. Also, we continuously optimize these methods to attain optimal results. In this seminar, firstly, we define a Dynamic Online Double Auction Mechanism (DODAM) for the IaaS environment, which covers a broader range of IaaS parameters by considering the dynamic online features of such markets. Considering the features of cloud dynamic online ecosystems, DODAM provides an appropriate price scheduling for service providers and service users. Cloud secondary market is a new paradigm in IaaS ecosystems. In these markets, brokers and reseller buyers have attained their resources from service providers of the cloud primary markets in the form of timed packages and repackage them into smaller chunks. As unsold packages do not transfer to the next intervals, brokers and reseller buyers need to sell their packages as much as possible. We develop a mechanical design that includes a market-based pricing model and a resource allocation algorithm in such markets as our second contribution. Next, by formulating the inherent competitive features in cloud secondary markets, we improve the pricing and resource allocation mechanisms in such competitive ecosystems. In the last contribution, we proposed a Priority-based Dynamic Online Double Auction Model (PB-DODAM), considering the perishability and time constraints of traded resources in IaaS secondary markets. The provided experimental results show that all proposed mechanisms drastically increase resource utilization and the overall utility.
Speaker(s): Dr. Reza Dibaj
Virtual: https://events.vtools.ieee.org/m/276942

Product Lifecycle Management
2021-07-19 18:00 - 20:00 UTC | Virtual: https://events.vtools.ieee.org/m/275555
Product Lifecycle Management is a process used to manage all of the business and technical aspects in the life of a product business, from early stage concept to product retirement. It is used extensively by most Global MultiNational Corporations but it serves small startup businesses very well also. It deals with and includes participation from all of the important business organisations. As such it is very relevant to engineers involved in any aspect of product development. Marto Hoary has worked with a number of multinationals in the USA and Europe where in he has observed and learned the use of this process first hand.
Speaker(s): Marto J Hoary, Sr MIEEE, M. Eng.
Virtual: https://events.vtools.ieee.org/m/275555

Distributed Machine Learning 101
2021-07-19 12:00 - 13:00 UTC | Toronto, Ontario, Canada, Virtual: https://events.vtools.ieee.org/m/276938
Machine Learning is an indispensable part of data science, and there is no need to have a thorough programming background to benefit from it. Machine Learning (ML) and statistical techniques have provided a new era that enables us to convert the data into information and transform it into actionable knowledge. SciKit and TensorFlow are two states of the art libraries that can be used in Python, and this seminar will open the gate to know their bases. The first seminar is about “Hello World!” Machine Learning program, using the python language and SciKit learn library.
Speaker(s): Dr. Reza Dibaj
Virtual: https://events.vtools.ieee.org/m/276938

FRDM-K64 & MBED Workshop
2021-07-17 13:00 - 14:00 UTC | Virtual: https://events.vtools.ieee.org/m/276197
The FRDM-K64 board is a development board designed around the Kinetis K64 MCU. This IEEE Seneca workshop is intended to demonstrate some of the basic functionality of the ARM Mbed platform and to offer assistance with Seneca course content related to microcontrollers and embedded systems. Bring your code, design ideas, or technical problems and discuss the best path forward with the workshop host and your fellow students.
Speaker(s): John Hooper, Adi Malihi
Virtual: https://events.vtools.ieee.org/m/276197

Introduction to Python programming - Registration
2021-07-12 18:00 - 2021-07-16 21:00 UTC | Virtual
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 (2 hours of lecture and 1 hour of lab). A certificate of completions will be given to the student who successfully complete the course and pass a short exam at the end of the course to evaluate their knowledge. Electronic copies of the course materials will be provided to the students. The students will also be provided with career advice, and skills development.
The course is delivered online and limited space (25 spots) is available. Please register by July 11. After the registration, applicants will be contacted with the virtual meeting information and course material prior to the start of the course.
Fees:
– $250 CAD (IEEE or OSPE Members)
– $350 CAD (Non-members)
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Course 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.
Note: 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
Who should attend: Students, second career trainees, engineers, scientists, clinicians, and in general specialists in variety of non-STEM fields.
What 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.
Speaker
Dr. Alireza Sadeghian
Dr. 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.
Dr. 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.
Dr. 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.
Email: dr.alireza.sadeghian@ieee.org
Agenda
Day 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.
Day 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.
Day 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.
Day 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.
Day 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.

From an Idea to a Startup
2021-07-08 15:00 - 16:00 (America/Toronto) | Virtual – Zoom
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?
I 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.
Contact: Ayda Naserialiabadi

IEEE VDL: Machine Learning for Wireless Communications and Networking: Motivations, Case Studies, and Open Problems
2021-06-28 18:00 - 19:30 UTC | Virtual – Zoom
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.
ZOOM link will be provided to attendees.
Contact: IEEE Denver ComSoc
Abstract:
While 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.
We 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.
Speaker(s): Dr. Shiwen Mao
Biography:

Shiwen 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.
Agenda:
6pm (MT) – Introductions
6:10-7:15 – VDL Presentation
7:15-7:30 – Q&A

IEEE VDL: Learning to Learn to Communicate
2021-06-24 11:00 - 12:30 UTC | Virtual – Zoom
Join us on Thursday, June 24, 2021 for the IEEE VDL: Learning to Learn to Communicate, presented by Prof. Osvaldo Simeone.
Contact: IEEE Kingston ComSoc
Abstract:
The 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.
Speaker(s): Prof. Osvaldo Simeone
Biography:
Osvaldo 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.

Overview of Secondary Surveillance Radar (SSR) and Identification Friend/Foe (IFF) Systems - Part I - Virtual Lecture - CEU/PDH Available
2021-06-22 18:00 - 19:00 UTC | Virtual
The lecture is composed of two one-hour parts.
In 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.
Link to virtual event will be provided after registration.
Contact: IEEE Long Island CAS Society
Speaker(s): Frank Messina
Biography:
Frank 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.
Earlier 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.

IEEE VDL: Intelligent Reflected Surfaces for Future Wireless Systems
2021-06-21 11:00 - 12:30 UTC | Virtual – Zoom
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.
Contact: IEEE Kingston ComSoc
Abstract:
As 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.
Speaker(s): Dr. Shahid Mumtaz
Biography:
Shahid 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.
He 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.
He 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.

AI against COVID-19 Competition: Closing Ceremony
2021-06-18 13:00 - 14:00 UTC | Virtual
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!
All the information will be sent to the registrants.

IEEE VDL: Localization in Drone Assisted and Vehicular Networks
2021-06-17 13:00 - 14:30 UTC | Virtual – Zoom
Join the IEEE Kingston Communications Society Chapter for the Virtual Distinguished Lecture: Localization in Drone Assisted and Vehicular Networks, presented by Shahrokh Valaee.
Contact: IEEE Kingston ComSoc
Abstract:
The 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.
Speaker(s): Shahrokh Valaee
Biography: 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.

Protect the Privacy, Security, and Integrity of APIs
2021-06-11 14:30 - 15:30 UTC | Virtual – Zoom
TeejLab’s mission:
Protect 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.
Contact: Mehrdad Tirandazian
Abstract:
Software 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.
Speaker(s): Dr. Baljeet Baljeet of TeejLab
Biography:
Dr. 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.

Rate-Splitting Multiple Access for 6G
2021-06-10 12:00 - 13:30 UTC | Virtual
Virtual platform will be delivered to registrants a couple of hours before starting the event.
Contact: IEEE Montreal Young Professionals
Abstract:
Rate 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.
This 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.
Speaker(s): Bruno Clerckx
Biography:
Bruno 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.

Advanced OrCad Workshop
2021-06-08 18:00 - 19:00 (America/Toronto) | Virtual – Zoom
IEEE Seneca is offering an advanced OrCad Workshop.
We will be reinforcing ETD555 concepts and learn about following topics:

Transistor circuits (PNP, NPN, Darlington and MOSFETS)
Components such as IRF840, IRF9510, TIP122, TIP127, 2N3904, and 2N3906

To amplify the experience, please have OrCad installed or using virual commons to follow through the instructions.
Contact: IEEE Seneca
Speakers: Gabriel Chen, Adi Malihi

Introduction to Python Programming
2021-06-07 18:00 - 2021-06-11 21:00 (America/New_York) | Virtual
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.
Course 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.
Note: 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
Who should attend: Students, second career trainees, engineers, scientists, clinicians, and in general specialists in variety of non-STEM fields.
What 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.
Speaker
Dr. Alireza Sadeghian
Dr. 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.
Dr. 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.
Dr. 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.
Email: dr.alireza.sadeghian@ieee.org
Agenda
Day 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.
Day 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.
Day 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.
Day 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.
Day 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.

Basic OrCad Workshop
2021-06-07 18:00 - 19:00 (America/Toronto) | Virtual – Zoom
IEEE Seneca is offering a basic OrCad Workshop.
We will be reinforcing ETY155 concepts and learn about following topics:
– Simple resistor circuits
– Voltage divider
– Current divider concepts
– Parallel circuits vs series circuits
To amplify the experience, please have OrCad installed or use virual commons by Seneca to follow through the instruction.
Contact: IEEE Seneca
Speakers: Gabriel Chen, Adi Malihi

[AP-S Seminar Series] Low Profile Antennas for Chip-to-Chip Data Communications: A Research Story, Prof. Kathleen Melde
2021-06-04 16:00 - 17:00 (America/Toronto) | Virtual – Zoom
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.
Contact: UofT AP-S Student Chapter

Ubiquitous Machines Learning for Design and Implementation of Energy-Efficient Electrical Systems: A Wide Range of Uses and Applications
2021-06-01 13:00 - 14:00 (America/Toronto) | Virtual
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”
The 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.
Speakers:
Prof. Yvon Savaria
Yvon 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.
Dr. Ahmed Ragab
Ahmed 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.

AI against COVID-19: Screening X-ray Images for COVID-19 Infections
2021-05-31 00:00 - 23:55 (America/Toronto) | Virtual
Join the virtual competition on AI for COVID diagnosis, thanks to Microsoft Canada, the exclusive technology and cloud platform sponsor!

The 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?
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 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.
In 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.
This 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.
How to participate
Note: This competition only accepts participants living in Canada, due to restrictions on funds transfer.
NO PURCHASE NECESSARY TO ENTER OR WIN.
The competition is hosted on the Eval.ai online platform. To participate, you or your team will need to perform the following steps:

Register individually at the link provided below in the current webpage (vTools).
Register 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#.
Download the dataset from https://www.kaggle.com/andyczhao/covidx-cxr2.
Design an AI algorithm that gets CXR images as inputs and predicts the labels of the images in the output (COVID or non-COVID).
Train your AI algorithm using the training dataset.
Submit your AI algorithm through Eval.ai for evaluation against the test dataset for the competition.

Prizes
For the First Phase, the first five best solutions will be awarded monetary prizes and Azure credits:

First place: 1,000 CAD + 500 CAD in Azure.
Second place: 800 CAD + 300 CAD in Azure.
Third place: 600 CAD + 300 CAD in Azure.
Fourth place: 400 CAD + 300 CAD in Azure.
Fifth place: 300 CAD + 300 CAD in Azure.

The top 10 teams on the leaderboard will also have the following opportunities:

Participate in the 2nd phase to refine their solution and receive funding for a project.
Write a scientific paper with the Vision and Image Processing Research Group, from the University of Waterloo, to explain their approach.

For the Second Phase, the best three projects can receive funds up to the following amounts:

Project 1: 5,000 CAD.
Project 2: 5,000 CAD.
Project 3: 4,000 CAD.

Term of funding: Up to 4 months following the announcement of the selected teams. The deadline is December 31st, 2021.

For more information, visit IEEE SIGHT Montreal website.

Integrated Terrestrial-Aerial-Satellite Networks: Key Enabler for the Super Smart Cities of the Future
2021-05-27 12:00 - 13:00 (America/Toronto) | Virtual – Zoom
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
Speaker: Dr. Halim Yanikomeroglu
Biography: 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).

Enriching Public Speaking and Networking
2021-05-26 20:00 - 21:00 (America/Toronto) | Virtual – Zoom
Having good communication and networking skills are essential to succeed in any industry, especially for engineering students.
Join 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.
Speakers: Ana Acioli, Adi Malihi

PD Course - e-lesson #1 - Basics of partial discharges
2021-05-25 08:00 - 15:00 (America/Toronto)
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.
Contact: Ali Naderian
Register: Please Register Directly Using Link: https://lnkd.in/dnDybDc
Speaker: Stefan Tenbohlen of Stuttgart University
Topic: Partial Discharge Measurement for Power Transformers- Basics
Biography: 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.

The Analog Designer's Toolbox (ADT): Towards A New Paradigm for Analog IC Design
2021-05-21 15:00 - 16:00 (America/Toronto) | Virtual – Zoom
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.
This event will be a virtual talk held on Zoom. The invitation will be sent to registerants.
Topic: The Analog Designer’s Toolbox (ADT): Towards A New Paradigm for Analog IC Design
Abstract:
The 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!
Speaker: Hesham Omran
Biography:
Dr. 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.
Dr. 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.
Email: hesham.omran@master-micro.com

IEEE VDL: Deep Learning for Physical Layer Communications: An Attempt towards 6G
2021-05-18 20:00 - 21:30 (America/Toronto) | Kingston, Ontario, Canada, Virtual: https://events.vtools.ieee.org, Kingston, Ontario, Canada, Virtual: https://events.vtools.ieee.org
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.
Contact: IEEE Kingston ComSoc Chapter
Abstract:
Merging 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.
Biography:
Prof. 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.

Reconfigurable Intelligent Surfaces: A Signal Processing Perspective
2021-05-17 01:00 - 14:30 (America/Toronto) | Montreal, Quebec Canada
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!
What 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.
This 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.
The virtual platform information will be sent to registrants a couple of hours ahead of starting the event.
Contact: IEEE Young Professionals Montreal
Speaker: Emil Björnson
Biography:
Emil 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.
He 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.
He 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.

ComSoc Distinguished Lecture: AI to Enable Digital Medicine and Detect COVID-19
2021-05-14 11:00 - 12:00 (America/Toronto) | Virtual – Zoom
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.
For any additional information please contact: Wahab Almuhtadi or Eman Hammad
Abstract:
Digitalize 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.
To 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.
Speaker: Giorgio Quer
Giorgio 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).
His 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.
He 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.

Electromagnetics Alumni Event
2021-05-13 16:00 - 18:00 (America/Toronto) | Virtual – Zoom
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.
Zoom link will be provided to the registered participants.
Contact: IEEE UofT AP-S Student Chapter
Panelists:

Dr. Michael Selvanayagam, IBM T.J. Watson Research Center, NY
Dr. Rubaiyat Islam, AMD, Canada
Dr. Marco Antoniades, Ryerson University, Canada
Dr. Loic Markley, University of British Columbia, Canada
Dr. Utkarsh Patel, AMD Canada
