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  • PIC Microcontroller Workshop

    Virtual - Zoom

    IEEE Seneca is offering PIC Microcontroller Workshop, please check out the details below for more information. This session will be recorded and uploaded at our IEEE Seneca Website. Knowledge for the digital systems, basic electronics and C programming helps to understand the workshop. Why is PIC Microcontroller important? They are low in power consumption, high performance ability and easy to support hardware and software tools like compilers, debuggers and simulators. High integration allows the costand size of the system are reduced, which makes them easily accessible. It is easy to interface additional RAM, ROM and I/O ports. Intro to PIC Mictocontroller Workshop Date: Friday March 19, 2021 Time: 11:00 a.m. - 12:00 p.m. This workshop will be an introduction to the PIC Microcontroller featuring: Microcontroller Setup RC Oscillator MPLab X Programming ESP8266 Node MCU Microcontroller Workshop Date: Friday, March 26, 2021 Time: 11:00 a.m. – 12:00 p.m. Note: For this workshop, we will be using Arduino IDE during the session. If you would like to try out or download before the workshop, please visit https://www.arduino.cc/en/software. This workshop will feature in-depth information about Amica NodeMCU: Programming and debugging library ESP8266WiFi

  • VT Chapter Rising Star Talks: Content Caching and Delivery in Heterogeneous Vehicular Networks

    The IEEE Toronto Vehicular Technology Chapter is hosting two talks as part of their Rising Star Series! Haixia Peng and Huaqing Wu are at their final stages of their PhD studies at the University of Waterloo. They will share their research on mobile edge computing/caching/ communication, network slicing, Artificial Intelligence (AI) enabled IoV networks, and integrated space-air-ground vehicular networks during their PhD studies. Location: All events are held with Zoom Meeting https://ryerson.zoom.us/j/96808290854 Meeting ID: 968 0829 0854 Contact: Please contact Lian Zhao at l5zhao@ryerson.ca for any questions The details of each talk are below. Intelligent Multi-Dimensional Resource Slicing in MEC-Assisted Vehicular Networks Date & Time: Tuesday, March 16, 2021 7:00 p.m. – 8:00 p.m. Speaker: Haixia Peng, University of Waterloo Abstract: Benefiting from advances in the automobile industry and wireless communication  technologies, the vehicular network has been emerged as a key enabler of intelligent  transportation services. However, with more and more services and applications, mobile data  traffic generated by vehicles has been increasing and the issue of the overloaded computing task  has been getting worse. Because of the limitation of spectrum resources and vehicles’ onboard  computing/caching resources, it is challenging to promote vehicular networking technologies to  support the emerged services and applications, especially those requiring sensitive delay and  diverse resources. To effectively address the above challenges, two potential technologies, multi access edge computing (MEC) and unmanned aerial vehicle (UAV), can be exploited in  vehicular networks. In this presentation, I will introduce how to adopt optimization and AI technologies for efficient resource slicing, and therefore supporting various applications with  satisfied quality of service (QoS) requirements in MEC- and/or UAV-assisted vehicular  networks. For a relatively simple vehicular network scenario with only terrestrial MEC servers, a  model-based method is applied for dynamic spectrum management, including spectrum slicing,  spectrum allocating, and transmit power controlling. For a vehicular network supported by both  terrestrial and aerial MEC servers, an AI-based method is applied to effectively manage the  spectrum, computing, and caching resources while satisfying the QoS requirements of different  applications. Biography: Haixia Peng received her M.S. and Ph.D. degrees in Electronics and  Communication Engineering and Computer Science from Northeastern University, Shenyang,  China, in 2013 and 2017, respectively. She is currently a Ph.D. student in the Department of  Electrical and Computer Engineering at the University of Waterloo, Canada. Her current  research focuses on Internet of vehicles, resource management, multi-access edge computing,  and reinforcement learning. She has authored or co-authored more than 30 technical papers.  She serves/served as a reviewer for IEEE Journals on Selected Areas in Communications (JSAC),  IEEE Transactions on Communications, IEEE Transactions on Vehicular Technologies, etc. more  than 20 prestigious journals, and as a TPC member in IEEE ICC, Globecom, VTC, etc.  conferences. Content Caching and Delivery in Heterogeneous Vehicular Networks Date & Time: Tuesday, March 30, 2021 7:00 p.m. – 8:00 p.m. Speaker: Huaqing Wu, University of Waterloo Abstract: Connected and automated vehicles (CAVs), which enable information exchange and  content delivery in real time, are expected to revolutionize current transportation systems.  However, the emerging CAV applications such as content delivery pose stringent requirements on  latency, throughput, and global connectivity. To empower multifarious CAV content delivery,  heterogeneous vehicular networks (HetVNets), which integrate the terrestrial networks with aerial  networks and space networks, can guarantee reliable, flexible, and globally seamless service  provisioning. In addition, edge caching can facilitate content delivery by caching popular files in  the HetVNet access points (APs) to relieve the backhaul traffic with a lower delivery delay. In this  talk, we investigate the content caching and delivery schemes in the caching-enabled HetVNet.  First, we study the content caching in terrestrial HetVNets with intermittent network connections.  A coding-based caching scheme is designed and a matching-based content placement algorithm is  proposed to minimize the content delivery delay. Second, UAV-aided caching is considered to  assist vehicular content delivery in aerial-ground vehicular networks (AGVN) and a joint caching  and trajectory optimization (JCTO) problem is investigated to jointly optimize content caching,  content delivery, and UAV trajectory. To enable real-time decision-making in highly dynamic  vehicular networks, we propose a deep supervised learning scheme to solve the JCTO problem.  Third, we investigate caching-assisted cooperative content delivery in space-air-ground integrated  vehicular networks (SAGVNs), where the vehicle-to-AP association, bandwidth allocation, and  content delivery ratio are jointly optimized. To address the tightly coupled optimization variables,  we propose a load- and mobility-aware cooperative delivery scheme to solve the joint optimization  problem with the consideration of user fairness, load balancing, and vehicle mobility. Biography: Huaqing Wu received the B.E. and M.E. degrees in Electrical Engineering  from Beijing University of Posts and Telecommunications, Beijing, China, in 2014 and 2017,  respectively. She is currently working toward the Ph.D. degree at the Department of Electrical and  Computer Engineering, University of Waterloo, Waterloo, ON, Canada. Her current research  interests include vehicular networks with emphasis on edge caching, wireless resource  management, space-air-ground integrated networks, and application of artificial intelligence (AI)  for wireless networks. She has authored/co-authored more than 30 technical papers which are  published in prestigious refereed journals (IEEE JSAC, TWC, WCM, etc.) and conferences (IEEE  ICC, Globecom, VTC, etc.).

  • EDS Distinguished Lecture – Self-Heating in FinFETs: Characterization, Reliability and Impact on Logic Circuits

    Toronto, Ontario Canada

    The Circuits & Devices Chapter of IEEE Toronto is pleased to invite you to join us for a virtual talk by Distinguished Lecturer Dr. Durga Misra of the New Jersey Institute of Technology. Please see below for schedule and details. Topic: Self-Heating in FinFETs: Characterization, Reliability and Impact on Logic Circuits Abstract: Device scaling for sub-10 nm CMOS technology has introduced bulk/SOI FinFETs This talk will outline the self-heating (SH) in FinFETs and its characterization. Local self-heating can potentially affect device performance and exacerbate the effects of some reliability mechanisms. Three different measurement methodologies for the electrical characterization of FinFET self-heating at wafer-level will be described. Also, the impact of self-heating on reliability testing at DC conditions as well as realistic CMOS logic operating (AC) conditions will be discussed. Front-end-of-line (FEOL) reliability mechanisms, such as hot carrier injection (HCI) and non-uniform time dependent dielectric breakdown (TDDB) will also be outlined. Self-heating is also studied at more realistic device switching conditions in logic circuits by utilizing ring oscillators with several densities and stage counts. The measurements indicate that self-heating is considerably lower in logic circuits compared to constant voltage stress conditions and degradation is not distinguishable. Speaker: Prof. Durga Misra, Department of Electrical and Computer Engineering, New Jersey Institute of Technology Biography: Prof. Durga Misra is a Professor in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, USA. His current research interests are in the areas of nanoelectronic/optoelectronic devices and circuits; especially in the area of nanometer CMOS gate stacks and device reliability. He is a Fellow of IEEE and is currently a Distinguished Lecturer of IEEE Electron Devices Society (EDS) and served in the IEEE EDS Board of Governors. He is a Fellow of the Electrochemical Society (ECS). He received the Thomas Collinan Award from the Dielectric Science & Technology Division of ECS. He is also the winner of the Electronic and Photonic Division Award from ECS. He edited and co-edited more than 45 books and conference proceedings in his field of research. He has published more than 200 technical articles in peer reviewed Journals and in International Conference proceedings including 95 Invited Talks. He has graduated 19 PhD students and 40 MS students. He received the M.S. and Ph.D. degrees in electrical engineering from the University of Waterloo, Waterloo, ON, Canada, in 1985 and 1988, respectively.

  • IEEE VT Chapter Women in Engineering Series

    On April 13, 2021 at 7:00 p.m., Dr. Fatima Hussain will present the talk “Insider Threat and Behaviour Modelling/Professional Career Development Discussions”. Date: Tuesday, April 13, 2021 Time: 7:00-8:00pm Speaker(s): Dr. Fatima Hussain, Senior Member, IEEE, Manager, Event Management and Analytics, User Behaviour Analytics and Insider Threat, Global Cyber Security, Royal Bank of Canada, Toronto Adjunct Professor, Ryerson University, Toronto Location: All events are held with Zoom Meeting https://ryerson.zoom.us/j/96808290854 Meeting ID: 968 0829 0854 Organizer(s): IEEE VT Chapter Contact: Lian Zhao Abstract: In the first half of the talk, discussion about behaviour modelling and insider threat is done. Insider threat classification and related threat vectors are discussed in detail. Afterwards, various methods used for identification and remediation of insider threat are presented, along with cutting edge enterprise level tools and frameworks.In the second half of the talk, we will have on-live discussions for professional caree rdevelopment, through experience sharing and opinion sharing, to encourage and guide young researchers career development plan, and to motivate women career development in engineering. Biography: Fatima Hussain received the Ph.D. and M.A.Sc. degrees in Electrical and Computer engineering from Ryerson University, Toronto, ON, Canada. Upon graduation, she was a Postdoctoral Fellow with the Network-Centric Applied Research Team (N-CART), where she worked on various NSERC-funded projects in the realm of the Internet of Things. Currently, she is part of User Behaviour and Insider Threat team ,working as a Manager, Event Management and Analytics in Royal Bank of Canada (RBC), Toronto.She is responsible foremployee profiling and detection of insider threats, by establishing baseline behaviours. She is working as an editor for IEEE Newsletter (Toronto), and associate editor for various journals. She is also an Adjunct Professor with Ryerson University and her role includes supervision of graduate research projects. Her research interests include cyber security,insider threat, XAI etc. Her background includes a number of distinguished professorships with Ryerson University and University of Guelph, where she has been awarded for her research, teaching, and course development accomplishments within wireless telecommunication and Internet of Things.

  • CAS Distinguished Lecture – Augmented Perception: Next Generation Wearables and Human-Machine Interfaces

    Virtual - Zoom

    The Circuits & Devices Chapter of IEEE Toronto is pleased to invite you to join us for a virtual talk by Distinguished Lecturer Dr. Andrew Mason of the Michigan State University. Topic: Augmented Perception: Next Generation Wearables and Human-Machine Interfaces Abstract: Products like Fitbit and the Apple Watch have brought to the public decades of foundational work on wearable technologies achieved by researchers in the IEEE CAS Society and related groups. Similarly, research into brain- and human-machine interface is starting to enter the public domain in applications including deep brain stimulation, prosthetic limb control, and human assistive devices. While researchers continue to explore new wearable sensing and human-interface paradigms, it is vital that we also explore what applications the next generation of wearable human-machine interfaces can and should enable. This talk will review key challenges and approaches within wearable assistive device and brain/human interface technologies. Aspects of physiological, environmental, and behavioral sensing within wearable platforms will be discussed, and technical challenges will be highlighted. Finally, the next generation concept of augmented human perception, real time machine-enhanced awareness that expands natural human senses, will be introduced. Utilizing wearable sensing and real-time feedback through visual, audio and tactile mechanism, augmented perception is poised to revolutionize the human experience, enhance daily performance, and enable new pathways to address mental and physical health concerns. Speaker: Andrew Mason of Michigan State University Biography: Andrew J. Mason received the BS in Physics with highest distinction from Western Kentucky University in 1991, the BSEE with honors from the Georgia Institute of Technology in 1992, and the MS and Ph.D. in Electrical Engineering from The University of Michigan, Ann Arbor in 1994 and 2000, respectively. From 1999 to 2001 he was an Assistant Professor at the University of Kentucky.  In 2001 he joined the Department of Electrical and Computer Engineering at Michigan State University in East Lansing, Michigan, where he is currently a Professor.  His research explores mixed-signal circuits, microfabricated structures and machine learning algorithms for integrated microsystems in biomedical, environmental monitoring and sustainable lifestyle applications.  Current projects are focused on design of augmented human awareness systems including signal processing algorithms and hardware for brain-machine interface, wearable/implantable biochemical and neural sensors, and lab-on-CMOS integration of sensing, instrumentation, and microfluidics. Dr. Mason is a Senior Member of the Institute of Electrical and Electronic Engineers (IEEE) and serves on the Sensory Systems and Biomedical Circuits and Systems Technical Committees of the IEEE Circuits and Systems Society. He is an Associate Editor for the IEEE Trans. Biomedical Circuits and Systems and regularly serves on the technical and review committees for several IEEE conferences. Dr. Mason was co-General Chair of the 2011 IEEE Biomedical Circuits and Systems Conference. He is a recipient of the 2006 Michigan State University Teacher-Scholar Award and the 2010 Withrow Award for Teaching Excellence. Email: mason@msu.edu

  • A Short Course in “Electrical Power Substations- Planning, Design, Construction & Project Management”

    Toronto, Canada

    The Education Committee of the IEEE Toronto Section is offering a short course in “Electrical Power Substations- Planning, Design, Construction & Project Management” in April 2021 to develop an understanding of the practical applications of Power Substations Planning process, Design aspects, Substation Components, Construction practices, Commissioning & testing procedures and relevant Project Management techniques. This is the 2nd series after successful completion of earlier course delivered on “Power System Engineering, Operation and Management” to develop an overall understanding of power system engineering and technologies in the fields of generation, transmission and distribution. What will you receive after completion:  “Certificate of Completion” along with CEUs and PDH (After completing & passing a short exam and evaluation); Course Materials in electronic Format; Continuous support on career advice, resume building and skills development. Course Timetable: Monday, April 26, 2021: 6.00 PM to 9.00 PM Tuesday, April 27, 2021: 6.00 PM to 9.00 PM Wednesday, April 28, 2021: 6.00 PM to 9.00 PM Thursday, April 29, 2021: 6.00 PM to 9.00 PM Friday, April 30, 2021: 6.00 PM to 9.00 PM Speaker(s): Satish Saini, Topic: Opening & Overall Course Introduction & Course Chair) Hemant Barot, Topic: Electrical Power Substations- Planning, Design, Construction & Project Management Location: Due to current COVID-19 restrictions- This course will be delivered On-Line (Virtual). Link and relevant details to join will be provided to all registered attendees / participants before the course. Organizer(s): Education Committee, IEEE Toronto Section Contact: Satish Saini Register: Please visit https://events.vtools.ieee.org/m/261750 to register and for more information. Admission Fees: Non-IEEE Members: $300 CAD + GST/HST IEEE Members: $250 CAD + GST/HST Course Outline: Day 1: Power system overview & segments; Ontario’s power system, supply mix & energy market Day 2: Power System Planning process & Design concepts Day 3: Power Sub-stations Components, layout & functionalities Day 4: Substations Bus Bar layout, configuration & categories Day 5: Electrical Substations construction, Project Management, actual case study & substations visuals (in place of site visit which has to be canceled due to COVID-19 restrictions) Course Test/Exam Biographies: Satish Saini Satish is a Licensed Professional Engineer registered with Professional Engineers Ontario with 35 years of accomplished management experience in various fields of energy and power. Electrical utility operations and management, business development and project management related to DS grid modernisation, renewable energy, smart metering / AMI, Advanced Distribution System (ADS) / Smart Grid, DSM and DMS. Actively participated in the development of various energy policies with ministries, regulatory authorities, utilities and local distribution companies. He is an active member of IEEE in various committees, Task Forces and Working Groups related to Smart Distribution, Smart Grid, MicroGrids and Smart Cities. Current Chair of IEEE Smart Grid Technical Activities Committee and Chair of Education Committee IEEE Toronto Section. Has a strong vision of developing the aging DS Grid with latest innovative technologies and solutions along with transforming utilities through smart grid programs Email: s.saini@ieee.org Hemant Barot Hemant Barot has a PhD in Power System Operation & Planning and is a certified Professional Engineer licensed in the Province of Ontario Canada and a Project Management Professional. His diverse work experience includes working with Utility, Research and Academic Institutes and Original Power Equipment Manufacturers. His experience includes working as a Senior Engineer in Transmission system Planning, Project Planning and Estimation as well as roles in Project Management, Conceptual Engineering and Academics.

  • IEEE AESS Chapter Summit – Regions 1-7

    Growth through engagement and teamwork The IEEE AESS Chapter Summit brings together IEEE Aerospace & Electronic Systems Society chapter officers from across the US and Canada. Local volunteer leaders play a key role in engaging and serving our local members and advancing our technical interests in the complex systems of air, space, ocean and ground environments. Training, motivation, and inspiration from sharing best practices are all on the agenda. Please contact k.kramer@ieee.org for registration and connection information.

  • The Role of AI in 5G/6G and IoT-Enabled Smart Grids

    Montreal, Quebec Canada

    IEEE Young Professionals brings speakers from Canadian research groups to give the community technical talks in AI-Powered Wireless Communications and Intelligent Cyber Physical Analysis in IoT-Enabled Smart Grids. The virtual platform information will be sent to registrants a couple of hours ahead of starting the event. Contact: IEEE Young Professionals Montreal Speakers: Dr. Melike Erol-Kantarci of University of Ottawa Topic: AI-Enabled Wireless Networks: A Bridge from 5G to 6G Abstract: Future wireless networks are expected to support a multitude of services demanded by Enhanced Mobile Broadband (eMBB), Ultra-Reliable and Low-latency Communications (uRLLC), and massive Machine Type Communications (mMTC) users. Heterogeneous devices with different quality of service (QoS) demands will require intelligent and flexible allocation of network resources in response to network dynamics. For instance, a highly reliable and low-latency network is needed to enable rapid transfer of messages between connected autonomous vehicles. At the same time, the same physical infrastructure is expected to serve users with high-quality video demand or even mobile Augmented/Virtual Reality entertainment applications. Next-generation wireless networks are expected to accommodate such diverse use cases. In addition, resource efficiency, reliability, and robustness are becoming more stringent for 5G and beyond networks. To meet this, future wireless networks must incorporate a paradigm shift in network resource optimization, in which efficient and intelligent resource management techniques are employed. Artificial intelligence, or more specifically machine learning algorithms stand as promising tools to intelligently manage the networks such that network efficiency, reliability, robustness goals are achieved and quality of service demands are satisfied. The opportunities that arise from learning the environment parameters under varying behavior of the wireless channel, positions AI-enabled 5G and 6G, superior to preceding generations of wireless networks. In this keynote, we will provide an overview of the state-of-art in machine learning algorithms and their applications to wireless networks, in addition to their challenges and the open issues in terms of their applicability to various functions of future wireless networks. Biography: Melike Erol-Kantarci is Canada Research Chair in AI-enabled Next-Generation Wireless Networks and Associate Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa. She is the founding director of the Networked Systems and Communications Research (NETCORE) laboratory. She is a Faculty Affiliate at the Vector Institute, Toronto, and the Institute for Science, Society and Policy at University of Ottawa. She has over 150 peer-reviewed publications which have been cited over 5500 times and she has an h-index of 38. She has received numerous awards and recognitions. Recently, she received the 2020 Distinguished Service Award of the IEEE ComSoc Technical Committee on Green Communications and Computing. She was named as N2Women Stars in Computer Networking and Communications in 2019. Dr. Erol-Kantarci has delivered 50+ keynotes, tutorials and panels around the globe and has acted as the general chair and technical program chair for many international conferences and workshops. Her main research interests are AI-enabled wireless networks, 5G and 6G wireless communications, smart grid and Internet of things. She is an IEEE ComSoc Distinguished Lecturer, IEEE Senior member and ACM Senior Member Hadis Karimipour Topic: Intelligent Cyber Security Analysis in IoT-Enabled Smart Grids Abstract: Today’s smart grids are complex Cyber-physical Systems (CPSs) that integrate computational and physical capabilities for controlling and managing the ever-growing number of cyber-connected devices. Aside from a fault in the physical domain, CPS also suffer from cyber-attacks in both cyber and physical domain e.g., an industrial controller can be manipulated to launch various attacks such as the device state inference attack, leading to system instability. Therefore, any effort to secure the emerging critical CPSs is of paramount importance.  Nowadays, a cyber-security specialist must detect, analyze, and defend against many cyber threats in almost real-time conditions. Without the employment of artificial intelligence and machine learning techniques, dealing with a huge number of attacks in a timely manner is not possible. Intelligent, big-data analytical techniques are necessary to mine, interpret and extract knowledge of data when there is a significant amount collected from or generated by different security monitoring solutions. This talk will go through the CPS security challenges and AI-enabled state of the art solution in the literature. Biography: Dr. Hadis Karimipour is the director of the Smart Cyber-physical System (SCPS) Lab and an Assistant Professor in the School of Engineering at the University of Guelph. She is among the pioneers of using Machine Learning (ML) for security analysis of critical infrastructure. She has published more than 80 journal articles, conference papers and book chapters in top IEEE journals and conferences. She has been a keynote/invited speaker for more than 20 different IEEE/International Conference. She was the chair of the IEEE workshop on AI for Securing Cyber-Physical System (AI4SCPS) at IEEE CCECE 2019 and IEEE CyberSciTech 2020 conferences and chair of the special session on the AI for Security of IoT-Enabled Critical Infrastructures at the IEEE SMC 2020 conference. She was the technical committee member of numerous IEEE conferences, including IEEE SEGE 2018, 2019, 2020, IEEE DSAA 2020, PST 2020, IEEE EPEC 2018, 2020, and IEEE SMC 2020. Dr. Karimipour is the Associate Editor of the Frontiers in Communications and Networks Journal, Editor of American Journal of Electrical and Electronic Engineering, and Editor of Journal of Electrical Engineering. She has also served as Guest Editor for Elsevier Journal of Computer and Electrical Engineering. She was the Editor of the Springer book on Security of Cyber-physical System. Dr. Karimipour is a Senior Member of IEEE member, chair of IEEE Women in Engineering and chapter chair of the IEEE Information Theory Kitchener-Waterloo Section, and an active member of Society for Canadian Women in Science and Technology.

  • Electromagnetics Alumni Event

    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

  • 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.

  • Reconfigurable Intelligent Surfaces: A Signal Processing Perspective

    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.

  • 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.