• ComSoc Industry Visit: Siemens RUGGEDCOM

    Siemens Ruggedcom, 300 Applewood Crescent, Concord, ON L4K 4E5, Canada

    IEEE Toronto ComSoc Chapter in partnership with IEEE Toronto Industrial Relations are inviting all interested to a unique opportunity to visit Siemens RUGGEDCOM Facility at 300 Applewood Crescent, Concord, ON L4K 4E5. RUGGEDCOM is a Canadian based company that is a subsidiary of Siemens. RUGGEDCOM networking products are designed to meet, even surpass internationally recognized industry standards for fast, reliable, standardized communications in numerous mission-critical industrial applications around the world. During the visit we will get to take a factory tour, meet with an R&D engineer and tour the R&D lab. RUGGEDCOM will host us for a lunch afterwards. Day & Time: Thursday May 23rd, 2019 10:00 a.m. ‐ 1:00 p.m. Organizers: IEEE Toronto ComSoc Transportation: The location is not far from Vaughan Metropolitan Centre (TTC). registered individuals are welcome to coordinate their own transportation to the location. Meeting point: We plan to meet inside the building entrance at 10am. Register: https://events.vtools.ieee.org/m/198904 Location: Siemens Ruggedcom, 300 Applewood Crescent Concord, Ontario, Canada L4K 4E5 Contact: Toronto_Chapter@comsoc.org

  • MIMO Signalling: Knowing the Classics Can Make a Difference

    Room BA-2135, University of Toronto

    Thursday June 6th, 2019 at 10:00 a.m. Prof. Wing-Kin (Ken) Ma, Chinese University of Hong Kong, will be presenting an IEEE Signal Processing Society Distinguished Lecture “MIMO Signalling: Knowing the Classics Can Make a Difference”. Day & Time: Thursday June 6th, 2019 10:00 a.m. ‐ 11:00 a.m. Speaker: Prof. Wing-Kin (Ken) Ma Chinese University of Hong Kong Organizers: IEEE Signal Processing Chapter Toronto Section IEEE Communications Chapter Toronto Section Location: Room BA-2135, University of Toronto http://map.utoronto.ca/building/080 Contact: Mehrnaz Shokrollahi, Yashodhan Athavale, Michael Zara, Abstract: In this talk the speaker will share two stories of how his research was benefitted by learning from the basics. The first story concerns physical-layer multicasting, a topic that has been dominated bybeamforming and optimization techniques. We will see how the classical concept of using channel coding to fight fast fading effects gives spark to rethink multicasting, and how that leads to a stochastic beamforming approach that goes beyond what beamforming achieves. The second story considers one-bit massive MIMO precoding, an emerging and challengingtopic. Current research on this topic mostly focuses on optimization, often in a sophisticated, if not complicated, manner. We will see how the traditional idea of Sigma-Delta modulation for DAC of temporal signals can be transferred to the spatial case, leading to one-bit massive MIMO precoding solutions that are simple and have quantization error well under control. Biography: Wing-Kin (Ken) Ma is a Professor with the Department of Electronic Engineering, The Chinese University of Hong Kong. His research interests lie in signal processing, optimization and communications. His mostrecent research focuses on two distinct topics, namely, structured matrix factorization for data science and remote sensing, and MIMO transceiver design and optimization. Dr. Ma is active in the Signal Processing Society. He served as editors of several journals, e.g.,Senior Area Editor of IEEE Transactions on Signal Processing, Lead Guest Editor of a special issue in IEEE Signal Processing Magazine, to name a few. He is currently a member of the Signal Processing for Communications and Networking (SPCOM) Technical Committee. He received Research Excellence Award 2013– 2014 by CUHK, the 2015 IEEE Signal Processing Magazine Best Paper Award, the 2016 IEEE Signal Processing Letters Best Paper Award, and the 2018 IEEE Signal Processing Best Paper Award. He is an IEEE Fellow and is currently an IEEE SPS Distinguished Lecturer.

  • Toronto ComSoc Summer Talks: A Career in Engineering, Past & Future Reflections

    On Thursday, June 18, 2020 at 6:00 p.m., Dr. Thamir (Tom) Murad will be presenting  “Toronto ComSoc Summer Talks: A Career in Engineering, Past & Future Reflections”. Day & Time: Thursday, June 18, 2020 6:00 p.m. ‐ 7:00 p.m. Speaker: Dr. Thamir (Tom) Murad, Ph.D., P.Eng. Organizers: IEEE Toronto ComSoc Chapter Location: Virtual – Zoom Contact: IEEE Toronto ComSoc Chapter Abstract: The IEEE Toronto ComSoc Chapter is thrilled to kick-off its Summer Talks Series hosting Dr. Tom Murad, the Vice Chair, Ontario Society of Professional Engineers “OSPE“ ‘s Board of Directors. Dr. Murad currently is the Country Lead for Engineering and Technology for Siemens Mobility. In this talk, we look forward to Dr. Murad as he shares his reflections on his career in engineering with insights into the future on how to remain relvant and combine passion with leadership. Register: Please visit https://events.vtools.ieee.org/m/232207 for more details and to register. Biography: Dr. Thamir (Tom) Murad, Ph.D., P.Eng. Vice Chair, Ontario Society of Professional Engineers “OSPE“ ‘s Board of Directors Tom has been a licensed engineer since 1998 and has extensive years of experience in the profession. He currently is the Country Lead for Engineering and Technology for Siemens Mobility, previously the founder and Head of Siemens Canada Engineering & Technology Academy (SCETA), as well as the Country Lead for Engineering, Technology and Academics for Siemens. Tom has been a great advocate for the Engineering profession by sharing his experience and expertise with many committees and organizations’ Boards. He is a member of the Ontario Government’s Post Secondary Education Quality Assessment board “ PEAQB “, the Ryerson University Faculty of Engineering Advisory Council, Humber College Applied Technologies Dean’s Board, PEO’s Experience Review Committee, Past chair of the IEEE -Toronto Section’s Executive Committee, and the Past Chair of Halton Champions of Innovation Round Table. Dr. Murad also has been a member of the Board of Directors for IEEE Canada, the German Canadian Centre for Innovation & Research, the Green Centre Canada, and Fielding Environmental. His contributions to the profession have been recognized by PEO, which gave him the Order of Honour, and he was also named a Fellow of Engineers Canada. Most Recently, He has been awarded the IEEE Canada J.M. Ham Outstanding Engineering Educator Award in 2019, OPEA (Joint PEO and OSPE) Best Engineering Achievement Award in 2017, and the Ontario Chamber of Commerce Golden Award for Best Skill Enhancement Project in 2016 . Tom has a Bachelor of Science in Electrical and Electronic Engineering, as well as a Ph.D. of Engineering, specializing in Power Electronics & Industrial Controls from Loughborough University of Technology in the U.K. Tom’s Passion has been always in Engineering Skills development , and he is Nationally recognised and awarded as a visionary and an Advocate for Innovative approach to work Integrated Learning and Education programs.

  • Introduction to NLP for Classification Task – Session 1

    Recorded Material: Video: https://drive.google.com/file/d/1gBUK_NtU3kSNblsGaYouLHyfDHlxr1tt/view?usp=sharing PowerPoint: 1-Intro to Python, Data Science Libraries, and Pytorch On Wednesday, July 8, 2020 at 6:00 p.m., IEEE Toronto WIE and Computational Intelligence Society will be hosting “Introduction to Natural Language Processing (NLP) for Classification Task – Session 1”. Day & Time: Wednesday, July 8, 2020 6:00 p.m. ‐ 7:30 p.m. Organizers: IEEE Toronto WIE, Computational Intelligence Society Location: Virtual – Zoom Contact: Ayda Naserialiabadi, Younes Sadat Nejad Abstract: Introduction to Natural Language Processing (NLP) for Classification Task is a series of workshops hosted by IEEE Toronto Section, WIE, Computational Intelligence Society, Instrumentation Measurement/Robotics Automation Chapter and Ryerson Advanced AI lab. Our main goal is to get started on NLP classification tasks for competition and explore duplicate question detection and sentiment analysis tasks. In session 1, we will be covering the introduction to Python, Data Science Libraries and Pytorch. Register: Please visit https://events.vtools.ieee.org/m/233944 or https://events.vtools.ieee.org/m/233942 for more details and to register.

  • TORONTO COMSOC SUMMER TALKS: Integrated Access and Backhaul for 5G and Beyond

    The IEEE Toronto ComSoc Chapter is thrilled to continue its Summer Talks Series hosting Dr. Behrooz Makki, a Senior Researcher in Ericsson Research, Gothenburg, Sweden. In his talk, Dr. Makki will discuss integrated access and backhaul for 5G and beyond. Day & Time: Thursday, July 9, 2020 12:00 p.m. ‐ 1:00 p.m. Speaker: Dr. Behrooz Makki Organizers: IEEE Communications Society Toronto Chapter Location: Virtual – Zoom Contact: IEEE ComSoc Toronto Chapter 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. Biography: Behrooz Makki received his PhD degree in Communication Engineering from Chalmers University of Technology, Gothenburg, Sweden. In 2013-2017, he was a Postdoc researcher at Chalmers University. Currently, he works as a senior researcher in Ericsson Research, Gothenburg, Sweden. Behrooz is the recipient of the VR Research Link grant, Sweden, 2014, the Ericsson’s Research grant, Sweden, 2013, 2014 and 2015, the ICT SEED grant, Sweden, 2017, as well as the Wallenbergs research grant, Sweden, 2018. He is a Senior Member of IEEE since Aug. 2019. Also, Behrooz is the recipient of the IEEE best reviewer award, IEEE Transactions on Wireless Communications, 2018. Currently, he works as an Editor in IEEE Wireless Communications Letters, IEEE Communications Letters, the journal of Communications and Information Networks as well as the associate editor of Frontiers in Communications and Networks. He was a member of European Commission projects “mm-Wave based Mobile Radio Access Network for 5G Integrated Communications” and “ARTIST4G” as well as various national and international research collaborations. His current research interests include integrated access and backhaul, hybrid automatic repeat request, Green communications, millimeter wave communications, and backhauling. He has co-authored 57 journal papers, 45 conference papers and 40 patent applications. Register: Please visit https://events.vtools.ieee.org/m/233754 for more details and to register.

  • Introduction to NLP for Classification Task – Session 2

    Online via Zoom

    Recorded Material: Video: https://drive.google.com/file/d/1gBUK_NtU3kSNblsGaYouLHyfDHlxr1tt/view PowerPoint: 2.IntroductiontoNLP,Kagle On Wednesday, July 15, 2020 at 6:00 p.m., IEEE Toronto WIE and Computational Intelligence Society will be hosting “Introduction to Natural Language Processing (NLP) for Classification Task – Session 2”. Day & Time: Wednesday, July 15, 2020 6:00 p.m. ‐ 8:00 p.m. Organizers: IEEE Toronto WIE, Computational Intelligence Society Location: Virtual – Zoom Contact: Ayda Naserialiabadi, Younes Sadat Nejad Abstract: Introduction to Natural Language Processing (NLP) for Classification Task is a series of workshops hosted by IEEE Toronto Section, WIE, Computational Intelligence Society, Instrumentation Measurement/Robotics Automation Chapter and Ryerson Advanced AI lab. Our main goal is to get started on NLP classification tasks for competition and explore duplicate question detection and sentiment analysis tasks. In the second session, we will introduce the concept of deep learning, and then specifically focus on Natural Language Process. We will also introduce Kaggle Account as an environment for python coding. Register: Please visit https://events.vtools.ieee.org/m/235444 or https://events.vtools.ieee.org/m/235447 for more details and to register.

  • Introduction to NLP for Classification Task – Session 4

    Online via Zoom Toronto, Ontario Canada

    On Wednesday, July 29, 2020 at 6:00 p.m., IEEE Toronto WIE, Computational Intelligence Society, and IM/RA will be hosting “Introduction to Natural Language Processing (NLP) for Classification Task – Session 4”. Day & Time: Wednesday, July 29, 2020 6:00 p.m. ‐ 8:00 p.m. Organizers: IEEE Toronto WIE, Computational Intelligence Society, IM/RA Society Location: Virtual – Zoom Contact: Ayda Naserialiabadi, Younes Sadat Nejad Abstract: Introduction to Natural Language Processing (NLP) for Classification Task is a series of workshops hosted by IEEE Toronto Section, WIE, Computational Intelligence Society, Instrumentation Measurement/Robotics Automation Chapter and Ryerson Advanced AI lab. Our main goal is to get started on NLP classification tasks for competition and explore duplicate question detection and sentiment analysis tasks. In this session, we will be focusing on RNN and LSTM. Register: Please visit https://events.vtools.ieee.org/m/236479 or https://events.vtools.ieee.org/m/236480 for more details and to register.

  • Measurement, Control and Protection in Smart Grid Energy Management Systems for Smart Buildings in a Smart City

    Toronto, Ontario Canada

    Webinar by the IEEE Ottawa Section, Instrumentation & Measurement Society Chapter (IMS), Power and Energy Society Ottawa Chapter (PES), Reliability Society and Power Electronics Society Joint Chapter (RS/PELS), Communications Society, Consumer Electronics Society, and Broadcast Technology Society Joint Chapter (ComSoc/ CESoc/BTS), and IEEE Ottawa Educational Activities (EA). Day & Time: Thursday, July 30, 2020 6:30 p.m. ‐ 7:30 p.m. Speaker: Prof. Saifur Rahman Organizers: IEEE Ottawa Section, Instrumentation & Measurement Society Chapter, Power and Energy Society Chapter, Reliability Society and Power Electronics Society, Broadcast Technology Society Join Chapter, IEEE Ottawa Educational Activities, IEEE Toronto WIE Location: Virtual – Zoom Contact: Ayda Naserialiabadi Abstract: Smart grid is a modern electric system with its architecture, communications, sensors, measurements, automation, computing hardware and software for improvement of the efficiency, reliability, flexibility and security. In particular, the smart grid, when fully deployed, will facilitate the (i) increased use of digital information and measurement, control & protection technologies, (ii) deployment and grid-integration of distributed energy resources (DERs), (iii) operation of demand response and energy efficiency programs, and (iv) integration of consumer-owned smart devices and technologies. Different non-linear controls, such as back-stepping control, feedback linearization, model predictive control, and sliding mode control are applied to control DERs, and their grid integration. Another control technique gaining application in the smart grid space is based on multi-agent systems (MAS) which provide autonomy, reactivity and proactivity. As speedy communication facilities, such as fiber-optics, microwave, GSM/GPRS, 4G/5G are becoming the integral parts of the functioning smart grid, the integration of MAS in smart grid applications is becoming simple and feasible. This lecture focuses on the measurement & control issues of the smart grid and how MAS can provide an efficient tool to address such issues. In addition, an overview of the related challenges and opportunities for energy efficient building operation and management with deployment experience in the US will be provided. Register: https://events.vtools.ieee.org/m/236481 Biography: Prof. Saifur Rahman is the founding director of the Advanced Research Institute (www.ari.vt.edu) at Virginia Tech, USA where he is the Joseph R. Loring professor of electrical and computer engineering. He also directs the Center for Energy and the Global Environment (www.ceage.vt.edu). He is a Life Fellow of the IEEE and an IEEE Millennium Medal winner. He was the founding editor-in-chief of the IEEE Electrification Magazine and the IEEE Transactions on Sustainable Energy. In 2006, he served on the IEEE Board of Directors as the Vice President for Publications. He is a distinguished lecturer for the IEEE Power & Energy Society (PES) and has lectured on renewable energy, energy efficiency, smart grid, electric power system operation and planning, etc. in over 30 countries. He was IEEE Power and Energy Society President 2018-2019 and is now a candidate for IEEE President-Elect 2021. He chaired the US National Science Foundation Advisory Committee for International Science and Engineering, 2010-2013. He conducted several energy efficiency projects for Duke Energy, Tokyo Electric Power Company, US National Science Foundation, US Department of Defense, State of Virginia and US Department of Energy.

  • ComSoc Distinguished Lecture: AI to Enable Digital Medicine and Detect COVID-19

    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.

  • IEEE VDL: Deep Learning for Physical Layer Communications: An Attempt towards 6G

    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.

  • Integrated Terrestrial-Aerial-Satellite Networks: Key Enabler for the Super Smart Cities of the Future

    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).

  • IEEE VDL: Localization in Drone Assisted and Vehicular Networks

    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.