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  • The Digital Utility – From AI, AR, MR to Blockchain platforms to support P2P

    Virtual - Zoom

    This event has been cancelled. Certificate for Course THE DIGITAL UTILITY, Signed by the Instructor. 15 PDUs per course for 5 day course. Discounts available for students and for companies who register more than 5 people for the event. Email dustin.dunwell@ieee.org for details. Course Timetable: Start time: 6:00 pm ET End time: 9:00 pm ET On each of the following dates: Monday, September 21, 2020 Wednesday, September 23, 2020 Thursday, September 24, 2020 Monday, September 28, 2020 Thursday, October 1, 2020 Speakers: Puica Nitu, Afiny Akdemir Location: Virtual – Zoom Full meeting details, including passwords to join the meetings, will be sent out to registrants before the event. Organizer: IEEE Toronto Contact: Satish Saini, Dustin Dunwell Register: https://meetings.vtools.ieee.org/m/238130 Course Fees: Non-IEEE Members: $250 CAD Active Members: $220 CAD Student Members: $50 CAD Discounts available for students and for companies who register more than 5 people for the event. Course Content: The Digital utility encompasses technological end-to-end digitization with emphasis on the consumer, on the flexibility and integration of renewable technologies while offering an increased portfolio of market services. This is the first course of 4 e-learning courses. Each course runs 5 evenings, for 3 hours each. The first course presents the integration of new technologies in light of regulatory changes. The course explores the penetration of renewable energy resources facilitated by the operating flexibility brought by power electronics. Interoperability aspects and industry standards are discussed, with focus on the consumer centric paradigm of Transactive Energy. This course defines AI followed by VR, AR and MR as they apply to power systems. Practical examples illustrate each methodology. Special attention is given to advanced AI applications with Machine Learning for load and solar energy forecasts. The White House call-to-action of a decade ago allows utilities today to utilize energy platforms and APIs to standardize reporting, optimize consumption and leverage the much needed open exchange of solar data. The course introduces the Blockchain as a new line of defense against cyber threats and its increasing application to Peer-to-Peer transactions to stimulate green energy trading and also trading Renewable Certificates or Credits. The course provides industry examples from utilities and agencies from Canada, US, EU and Southeast Asia. Course Outline: Introduction: Historical Evolution of the inverter-based technologies Performance Requirements: Power System Controls Regulatory Agreements NERC, EU ENTSO The Role of the ISO Demonstration of Essential Reliability Services – Control algorithms Power System Stability in an Inverter dominated Grid TRANSACTIVE ENERGY – THE PROSUMER P2P Energy Trading Collaboration between Market Entities and Government Agencies Cloud Services for Utilities – NAESB Green Button, Orange Button ARTIFICIAL INTELLIGENCE -AI and Artificial Neural Networks- ANN AI and ANN Applications in Power Systems: Machine Learning Training the algorithm for Short Term Load Forecast and Solar Energy Forecasts IOT – Internet of Things; A brief look into Interoperability INTERNET OF THINGS WORLD FORUM REFERENCE MODEL AR- AUGMENTED REALITY VR- VIRTUAL REALITY MR- MIXED REALITY and AR-Augmented Reality IEDs- Intelligent Electronic Devices and SENSORS IEDs – Examples and Functionality BLOCKCHAIN Security Certification ; Vulnerability Blockchain Applications in the Power Industry- P2P Trading Trading Renewable Certificates Emission Credits Class Test 45 min and Discussions for Course Certification The target audience for this course includes practitioners at all levels in the organization in companies in the power industry, LDCs, regulatory agencies and students in engineering and economics. The course would benefit law firms supporting renewable investments, and CleanTech groups. Biographies: Puica Nitu, M.Sc. P.Eng., SM IEEE, CIGRE Puica Nitu is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex utility projects in operations (EMS, energy derivatives, reliability studies and policy) and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. Most recently, Puica was the Operations Expert for a regulatory assessment of the Oman Control Centre. With over 25 years with Ontario Hydro and its successor company Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, NSERC (Natural Sciences and Engineering Research Council of Canada), Senior Member IEEE and Elsevier since 1990. Puica Nitu chaired international conferences, lectured on 4 continents, published a book on Reliability and Security of Nuclear Power Plants, papers in IEEE, PICA, CIGRE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars to OPG, seminars organized by the Power Engineering Society, IEEE and seminars to power companies worldwide, including Thailand, Saudi Arabia, Oman, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Puica Nitu is a registered member of the Professional Engineers of Ontario, Canada. Afiny Akdemir Afiny Akdemir is the co-founder and Director of Research at Xesto Inc.  Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as “Toronto’s Best Tech Startup 2019” and was named one of the top 10 “Canadian AI Startups to Watch” as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. Afiny Akdemir specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, Afiny leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, Afiny is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. His ongoing projects examine the results of the regularity of the equation that governs optimal matching between two arbitrary sets in different dimensions. He is developing algorithmic applications of these results, as well as studying these applications in the context of big data and statistical estimation where the parameter space is much larger than the number of observations. Afiny earned a Bachelor’s and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, Afiny has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, Afiny is also an avid traveller and plays the violin.

  • Career Night Series: Which Direction Should I Take with My Career?

    On Tuesday, September 22, 2020 at 6:00 p.m., IEEE Toronto WIE will host the webinar “Career Night Series: Which Direction Should I Take with My Career?”. Day & Time: Tuesday, September 22, 2020 6:00 p.m. – 8:00 p.m. Organizers: IEEE Toronto WIE, Ryerson Computer Science Location: Virtual – Webinar Contact: Wincy Li Description: Not sure whether to pursue a PhD or Postdoc? Unclear about your career options? In this webinar, you will learn how to research the labour market so that you will be empowered with the tools and resources you need for career decision making and planning. If you require any accessibility needs, please contact Wincy at wincyli@ryerson.ca as soon as possible. Register: Click here to visit the registration page.

  • Collaborative Multi-Resource Allocation in Terrestrial-Satellite Network (TSN) Towards 6G

    On Wednesday, September 30, 2020 at 9:00 a.m., Shu Fu of Chongqing University, China will present “Collaborative Multi-Resource Allocation in Terrestrial-Satellite Network (TSN) Towards 6G”. Day & Time: Wednesday, September 20, 2020 9:00 a.m. – 10:00 a.m. Speaker: Shu Fu of Chongqing University, China Organizer: IEEE Toronto Vehicular Technology Chapter Location: Virtual – Zoom Contact: Lian Zhao Abstract: Terrestrial-Satellite Network (TSN) is critical for achieving the integrated ground-air-space in 6G by its employment of flight equipments to increase space resource diversity. The employment of flight equipments and the equipped caching, computing, and communication (3C) resources lead to the problem of multi-resource co-allocation while challenging the objective of low delay, large throughput, and high energy efficiency. We focus on solving this problem in terms of the following aspects: firstly, we will build a Nash bargaining model to implement the 3C resource allocation to maximize the user fairness guaranteed throughput. Secondly, we will discuss about the optimization of the satellite-terrestrial allocation of the unmanned aerial vehicle (UAV) based relays. Moreover, for the weak coverage areas of the ground gateways, we will discuss the mobile co-allocation of multi-resource model for UAV-BS. Finally, we will consider the heterogeneous traffic data characteristics to build co-allocation of multi-resource models, based on which the low delay constrained inter-satellite relaying and routing mechanism and satellite-terrestrial store-and-forward mechanism with high energy efficiency will be achieved. Register: Please visit https://events.vtools.ieee.org/m/240949 for the Zoom link. Biography: Shu Fu received the Ph.D. degree in communication and information system from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2016. He joined the College of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China, as an Assistant Professor in 2016, and has been an Associate Professor since 2018. He had been awarded twice “National Scholarship” during his PhD’s study. He was a visiting PhD student at University of Waterloo in 2014-2015; and a visiting professor at Ryerson University, Canada in 2019. He is a communication committee member of Chinese Institute of Electronics (CIE) Internet of Things Youth Specialist Group. He has published more than 30 IEEE journal papers and conference papers. His research interests include B5G network, UAV network, and terrestrial-satellite network, etc.

  • IEEE Day

    IEEE Toronto Section is inviting you to our VIRTUAL celebration of IEEE Day on Tuesday, October 6, 2020! Day & Time: Tuesday, October 6, 2020 10:00 a.m. – 3:00 p.m. Speakers: Dr. Rasheed Hussain, Dr. Melike Erol-Kantarci, Dr. Sahar Rahmani, Dr. Sarath Chandar, Dr. Haniyeh Yousefpour Organizers: IEEE Toronto Section, IEEE Toronto WIE Location: Virtual – Zoom Contact: Dustin Dunwell, Maryam Davoudpour Register: Please visit https://events.vtools.ieee.org/m/239738 for the Zoom link and to register. Agenda: 10:00 a.m. – 11:00 a.m. Panel Moderator: Dr. Fatima Hussain Dr. Melike Erol-Kantarci Dr. Sahar Rahmani 11:00 a.m. – 12:00 p.m. Keynote Dr. Rasheed Hussain 12:00 p.m. – 1:00 p.m. Break 1:00 p.m. – 2:00 p.m. Tech Talk Dr. Sarath Chandat, MILA 2:00 p.m. – 3:00 p.m. Tech Talk Dr. Haniyeh Yousefpour   Biographies: Rasheed Hussain, PhD, SMIEEE Topic: The Role of APIs in Connected and Autonomous Cars: A Case for Critical Applications Rasheed Hussain is working as an Associate Professor and the Director of Institute of Information Security and Cyber-Physical Systems at Innopolis University, Innopolis, Russia. He is also the head of Networks and Blockchain Lab at Innopolis University and serves as an ACM Distinguished Speaker. He is a senior member of IEEE, member ACM, and serves as an editorial board member for various journals including IEEE Access, IEEE Internet Initiative, Internet Technology Letters, Wiley, Cluster Computing, Springer, and serves as a reviewer for most of the IEEE transactions, Springer and Elsevier Journals. He also serves as technical program committee member and chair of various conferences such as IEEE VTC, IEEE VNC, IEEE Globecom, IEEE ICCVE, IEEE ICC, ICCCN, and so on. He is a certified trainer for Instructional Skills Workshop (ISW) and a recipient of Netherland’s University Teaching Qualification (Basis Kwalificatie Onderwijs, BKO). His research interests include Information Security and Privacy and particularly security and privacy issues in Vehicular Ad Hoc NETworks (VANETs), vehicular clouds, and vehicular social networking, applied cryptography, Internet of Things, Content-Centric Networking (CCN), cloud computing, API security, and blockchain. Currently he is working on the machine and deep learning for IoT security and API security. Melike Erol-Kantarci, PhD., P.Eng., SMIEEE Topic: AI-enabled wireless networks: Opportunities and Challenges Towards 6G Melike Erol-Kantarci is Tier 2 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 has over 140 peer-reviewed publications which have been cited over 5000 times and she has an h-index of 37. She is selected to the 2019 list of “N2Women: Stars in Computer Networking and Communications”. She has received the IEEE Communication Society Best Tutorial Paper Award and the Best Editor Award of the IEEE Multimedia Communications Technical Committee in 2017, in addition to several other best paper awards. She is the co-editor of three books on smart grids and smart cities. She has delivered 40+ tutorials, plenary talks and seminars around the globe. She has acted as the general chair or technical program chair for many international IEEE conferences and workshops. Most recently, she is the TPC co-chair for IEEE CAMAD 2020, a symposium co-chair for IEEE Globecom 2020, and a track co-chair for IEEE SmartGridComm 2020. She is a senior member of the IEEE. Her main research interests are AI-enabled wireless networks, 5G and 6G wireless communications, smart grid, electric vehicles, Internet of things and wireless sensor networks. Sahar Rahmani, PhD Work Domain: Data scientist on digital/cyber crime detection Dr. Sahar Rahmani is the Director of the Data Science team at the Global Cyber Security team at RBC. Her role involves leading a team of data scientists and machine learning engineers to provide AI solutions for detecting the ever-changing landscape of cyber/digital crime. She is responsible for implementing scalable real-time machine learning solutions for our stakeholders’ security related problems. Her team, also brings insight and analytics to RBC’s controls, and risks to help executives make data-driven strategic decisions. Her continuous encouragement and emphasizing on innovations in the application of AI/ML in digital risk, resulted in solving business problems in effective ways, creating multiple patents, and presenting multiple conference talks. She has a PhD in Astrophysics from the Western University, where she applied big data analysis and data science models on astronomical data.

  • PES Webinar: Developing the Utility Workforce of the Future – Managing Continuity and Change in Complex Times

    On Tuesday, October 6, 2020 at 5:00 p.m., Brad Cawn of Quanta Technology will present “PES Webinar: Developing the Utility Workforce of the Future – Managing Continuity and Change in Complex Times”. Day & Time: Tuesday, October 6, 2020 5:00 p.m. – 6:00 p.m. Speaker: Brad Cawn of Quanta Technology Organizer: IEEE Toronto PES Chapter Location: Virtual Contact: Omid Alizadeh Abstract: Building the utility of the future requires developing a workforce of the future, one that is responsive and agile in the face of continuous technological, operational, and cultural change. Join us as we discuss how both the coronavirus and ongoing paradigmatic shifts are quickening the industry’s transformation process and how a multi-prong workforce development strategy can help your team and/organization keep pace with the speed of change. In this webinar, Brad Cawn, a Senior Advisor with Quanta Technology, will make a presentation on: the current state of the utility industry technical workforce, including the impact of recent and ongoing internal and external change factors. potential directions for the industry’s workforce and workforce development initial key activities and comprehensive actions to develop and sustain utility workforces of the future Register: Please visit https://events.vtools.ieee.org/m/240561 to register. Biography: Brad Cawn of Quanta Technology Oversees Quanta Technology’s workforce development services, including training and curriculum development, workforce transformation, retention and recruitment initiatives, and other supports. Author of multiple books/manuscripts on teaching and learning, including Ambitious Instruction (2020) and Ambitious Leadership (2016). Teaches creativity and innovation coursework at DePaul University in Chicago.

  • Career Night Series: Writing an Effective CV

    On Tuesday, October 6, 2020 at 6:00 p.m., IEEE Toronto WIE and IM/RA will host “Career Night Series: Writing an Effective CV”. Day & Time: Tuesday, October 6, 2020 6:00 p.m. – 8:00 p.m. Organizers: IEEE Toronto WIE, IM/RA, Ryerson Computer Science Location: Virtual Contact: Wincy Li Description: Not sure what the difference is between a resume and a CV? Unclear about how to structure your CV or what content to include? Join us for this webinar to learn how to construct an effective CV! If you require any accessibility needs, please contact Camara Chambers at c.chambers@ryerson.ca. Register: Please visit https://lnkd.in/gBaMf9y to register.

  • GPT-3 for Vision

    On Wednesday, October 7, 2020 at 2:00 p.m., Dr. Ehsan Kamalinejad will present “GPT-3 for Vision”. Day & Time: Wednesday, October 7, 2020 2:00 p.m. – 3:00 p.m. Speaker: Ehsan Kamalinejad, PhD Co-Founder & CTO at Visual One Associate Professor at Cal State East Bay University Former Senior Machine Learning Scientist at Apple San Francisco, USA Organizer: IEEE Toronto Signal Processing Chapter Location: Virtual – Click here for the Google Meets link. Contact: Mehrnaz Shokrollahi Abstract: Deep learning in computer vision (CV) has proved to be very effective in solving many problems in real world. However, while the raw number of researches done in standard CV problems (such as ImageNet object classification/detection) has exploded, the measurable progress in these fields has slowed down. Additionally, there are many real-world problems in vision that are simply not compatible with the current approaches. This demands a new wave of problem statements in CV (and a new set of benchmarks). This talk focuses on one important set of such problem statements. We propose that many real-world problems in vision are “event recognition” problems. We introduce a concrete definition for the event recognition problem. We will see that this definition of event detection prohibits large sample sets. Hence, these events need to be recognize based on very few samples. We start by reviewing the current literature and we propose some promising directions for approaching this problem. At the end we show some demos from our recent effort on wrestling with this very challenging problem. Our solution can be best described by the “vision counterpart of GPT-3 few shot learner”. Register: Please check back soon for the registration link. Biography: Ehsan Kamalinejad (EK) is a senior machine learning engineer. He is currently working on Visual One which is a YCombinator backed startup he co-founded. Before that he was working for several years at Apple and Amazon as a staff machine learning engineer. Ehsan holds a faculty position as an associate professor at Cal State East Bay University. He got his PhD from University of Toronto. He has more than 7 years of experience delivering machine learning products in computer vision and natural language processing. His current project, Visual One, is about bringing next level intelligence to surveillance cameras.

  • Microwaving a Biological Cell Alive ‒ Broadband Label-free Noninvasive Electrical Characterization of a Live Cell

    On Wednesday, October 7, 2020 at 4:00 p.m., Prof. James Hwang of Cornell University will present “Microwaving a Biological Cell Alive ‒ Broadband Label-free Noninvasive Electrical Characterization of a Live Cell”. Day & Time: Wednesday, October 7, 2020 4:00 p.m. – 5:00 p.m. Speaker: Prof. James Hwang of Cornell University Organizer: IEEE Toronto Electromagnetics & Radiation Chapter Location: Virtual – Zoom Contact: George Eleftheriades Abstract: Microwave is not just for cooking, smart cars, or mobile phones. We can take advantage of the wide electromagnetic spectrum to do wonderful things that are more vital to our lives. For example, microwave ablation of cancer tumor is already in wide use, and microwave remote monitoring of vital signs is becoming more important as the population ages. This talk will focus on a biomedical use of microwave at the single-cell level. At low power, microwave can readily penetrate a cell membrane to interrogate what is inside a cell, without cooking it or otherwise hurting it. It is currently the fastest, most compact, and least costly way to tell whether a cell is alive or dead. On the other hand, at higher power but lower frequency, the electromagnetic signal can interact strongly with the cell membrane to drill temporary holes of nanometer size. The nanopores allow drugs to diffuse into the cell and, based on the reaction of the cell, individualized medicine can be developed and drug development can be sped up in general. Conversely, the nanopores allow strands of DNA molecules to be pulled out of the cell without killing it, which can speed up genetic engineering. Lastly, by changing both the power and frequency of the signal, we can have either positive or negative dielectrophoresis effects, which we have used to coerce a live cell to the examination table of Dr. Microwave, then usher it out after examination. These interesting uses of microwave and the resulted fundamental knowledge about biological cells will be explored in the talk. Register: Please visit https://events.vtools.ieee.org/m/239462 to register. Biography: James Hwang is Professor in the Department of Materials Science and Engineering at Cornell University. He graduated from the same department with a Ph.D. degree. After years of industrial experience at IBM, Bell Labs, GE, and GAIN, he spent most of his academic career at Lehigh University. He cofounded GAIN and QED; the latter became the public company IQE. Between 2011 and 2013, he was the Program Officer for GHz-THz Electronics at the U.S. Air Force Office of Scientific Research. He has been a visiting professor at Cornell University in the US, Marche Polytechnic University in Italy, Nanyang Technological University in Singapore, National Chiao Tung University in Taiwan, Shanghai Jiao Tong University, East China Normal University, and University of Science and Technology in China. He is an IEEE Life Fellow and a Distinguished Microwave Lecturer. He is also a Track Editor for the IEEE Transactions on Microwave Theory and Techniques. He has published more than 350 refereed technical papers and been granted eight U.S. patents. He has researched for decades on the design, modeling and characterization of optical, electronic, and micro- electromechanical devices and circuits. His current research interest focuses on electromagnetic sensors for individual biological cells, scanning microwave microscopy, and two-dimensional atomic-layered materials and devices.

  • Electronic commerce and business, the benefits and opportunities for online users and providers

    On Wednesday, October 28, 2020 at 5:00 p.m., Edmund Baumann will present “Electronic commerce and business, the benefits and opportunities for online users and providers”. Day & Time: Wednesday, October 28, 2020 5:00 p.m. – 6:00 p.m. Speaker: Edmund Baumann Organizer: IEEE Toronto Section Location: Virtual Contact: Satish Saini Abstract: E-commerce is very much top of mind in our current environment as organizations have put great effort in providing products and services with substantial online supply chains. This market is driven by customers who desire a minimum of physical contact between suppliers and themselves. The presentation will cover the foundations of e-commerce from the technology and business points of view. The market impact of e-commerce continues to grow and the business creativity of entrepreneurs continues to deliver products and services that the market demands after their value proposition is understood by buyers. Current business statistics are provided. Examples of successful online business are highlighted. Register: Please visit https://events.vtools.ieee.org/m/240871 to register. Biography: Edmund Baumann (SMIEEE) holds a B.ScEE (1969) from Drexel University and an MBA (1984) from York University. He has 44 years of experience with various companies such as Rockwell, Atomic Energy of Canada, Tellabs, Motorola, Sprint, Humber College, University of Guelph-Humber. He teaches degree courses on Current Issues in Digital Business Management, New Product Management, E-Commerce, Digital Marketing, Business Information Systems, Consumer Behaviour, Marketing at Humber College and University of Guelph-Humber.

  • Python Project-based Workshop: How to build your own intelligent agent

    On Friday, November 13, 2020 at 10:00 a.m., Enas Tarawneh will present “Python Project-based Workhsop: How to build your own intelligent agent”. Day & Time: Friday, November 13, 2020 10:00 a.m. – 12:00 p.m. Speaker: Enas Tarawneh Organizers: IEEE Toronto WIE, IM/RA, York University WiCSE Location: Virtual Contact: Ayda Naserialiabadi Abstract: The workshop will focus on creating an intelligent agent that can listen to questions given through natural language and generate natural language responses. The workshop will also dabble into customizing the voice used in these responses. This workshop includes: a) Programming speech recognition. b) Leveraging cloud-based resources such as speech-to-text, text-to-speech and AI querying to generate responses. c) Connect these together to create a turn taking intelligent agent. d) Customizing the voice used in these generated responses. Register: Please click here to register. Biography: Enas Tarawneh is a PhD student at York University in the department of Computer Science and Electrical Engineering. She works in the Vision, Graphics and Robotics (VGR) Laboratory as a research assistant. Her most recent research involves the development and evaluation of a cloud-based avatar (intelligent agent) for human-robot interaction that is part of a project funded by VISTA. She holds an OGS and VISTA doctoral scholarship. Prior to this, Enas worked as an academic Lead, instructor, and e-learning coordinator in the Institute of Applied Technology in UAE in which she received an award for “Distinguished Curriculum Support” and another for “Excellence in E-learning coordination”. Most importantly, Enas is a wife and mother of three, that believes that open-mindedness and positivism is the best accomplishment and the source of true happiness.

  • IEEE Toronto Virtual AGM 2020

    Toronto, Canada

    The IEEE Toronto Section is happy to announce our first ever online IEEE Toronto section Annual General Meeting (AGM).  Since we are not restricted to a limited number of physical participants, we are happy to open this even up to all IEEE Toronto members, as well as any guests who they would like to invite.  Please feel free to pass this information along to any interested parties. We will hear from the IEEE Toronto section, IEEE Canada, and IEEE Global representatives, as well as keynote speakers from local industry.  Awards will be presented to oustanding contributors for the past year, and prizes will be available for all attendees.  You must register for the event using the link on this page in order to qualify for prizes.  Only IEEE members will be eligible for prizes. Date: Friday, November 13, 2020 6:00 p.m. – 8:00 p.m. Location: Virtual – WebEx Register: Please visit https://events.vtools.ieee.org/m/241427 for the registration link and event link. Agenda: 6:00pm: Introduction and online meeting details 6:05pm: Section Chair report from Ali Nabavi 6:15pm: IEEE Global update from Kathy Land 6:30pm: Prize draw 6:35pm: Keynote presentation from Dr. Inmar Givoni, Director of Engineering at Uber Advanced Technology Group, Toronto 7:05pm: IEEE Canada update from Maike Luiken 7:20pm: Keynote presentation from Dr. Martin Snelgrove, CTO at Untether AI 7:50pm: Awards presentation and prize draw Keynote Speakers: Dr. Inmar Givoni, Dr. Martin Snelgrove Topic: AI for Self-Driving Cars (Dr. Inmar Givoni) At the Uber ATG R&D centre, we are working on advanced state-of-the-art models for solving a large range of problems in self driving – perception and prediction, motion planning, mapping and localization, sensor simulation, and more. All that work is publicly available through academic conferences and venues. In this talk I will cover some exciting recent advances and also discuss the path to production – how we go from research prototypes to deployed systems on vehicle. Topic: Building Cool Silicon in the Frozen North (Dr. Matin Snelgrove) Biographies: Dr. Inmar Givoni Inmar Givoni is a Director of Engineering at Uber Advanced Technology Group, Toronto, where she leads a team whose mission is to bring from research and into production cutting-edge deep-learning models for self-driving vehicles. She received her PhD (Computer Science) in 2011 from the University of Toronto, specializing in machine learning, and was a visiting scholar at the University of Cambridge. She worked at Microsoft Research, Altera (now Intel), Kobo, and Kindred at roles ranging from research scientist to VP, Big Data, applying machine learning techniques to various problem domains and taking concepts from research to production systems. She is an inventor of several patents and has authored numerous top-tier academic publications in the areas of machine learning, computer vision, and computational biology. She is a regular speaker at AI events, and is particularly interested in outreach activities for young women, encouraging them to choose technical career paths. For her volunteering efforts she has received the 2017 Arbor Award from UofT. In 2018 she was recognized as one of Canada’s 50 inspiring women in STEM and recently recognized as one of Canada’s Tech Titans: Top 19 of 2019.. She was featured in Marie Claire, Toronto Life, The Globe and Mail,  TWIML & AI podcast, ReWork’s list of 30 influential women in Canadian AI, UofT’s News, and other media venues. Dr. Martin Snelgrove Martin is CTO of Untether AI, who have just announced their first product: a high-performance AI chip that puts Peta-operations per second onto a board. The magic to getting the massive computing power AI needs is to be very careful with the femtoJoules: you can only fit so many watts in a box, so you have to use them very carefully. It turns out that to do that you have to rethink John von Neumann’s 1947 computer architecture, and it turns out that understanding AI as a workload lets you do that.    Martin was a professor at the University of Toronto, then had a Nortel/Mitel-supported industrial research chair at Carleton. Over 16 years of teaching he saw the vast majority of the students Canada paid for head straight down to California. So he moved over to the dark side, and has been in the founding team for three tech companies in Toronto; Soma, Kapik and now Untether. It turns out that because Canada produces great engineers, you can give them a great place to work by putting teams together. Top-grade talent likes working with top-grade talent.

  • Machine Learning and Digital Signal Processing Applications in Online Video Platforms

    On Friday, November 20, 2020 at 2:30 p.m., Mehrdad Fatourechi will present “Machine Learning and Digital Signal Processing Applications in Online Video Platforms”. Day & Time: Friday, November 20, 2020 2:30 p.m. – 4:00 p.m. Speaker: Mehrdad Fatourechi, PhD Organizer: IEEE Signal Processing Chapter Toronto Section Location: This event will be hosted on google meets Meeting ID meet.google.com/yej-opbp-uxo Phone Numbers (US)+1 617-675-4444 PIN: 974 200 026 6220# Contact: Mehrnaz Shokrollahi Abstract: In the past 15 years, we have seen exponential growth in online video platforms such as YouTube, Instagram, Netflix, TikTok, amongst others. In this talk, we will look at some of the challenges these platforms have been facing and how machine learning and digital signal processing are playing important roles in addressing these challenges. We will focus on discussing 3 areas: 1- Content discovery and SEO optimization 2- Establishing trust and safety, and 3- Protecting the rights of the content owners We will also discuss some of the areas that are currently open for future research. Register: Registration is not required. Biography: Mehrdad is the VP of Engineering of BroadbandTV, a media-tech company that is advancing the world through the creation, distribution, management, and monetization of content. Mehrdad is currently responsible for managing the research and development (R&D) and IT departments. When he joined BBTV in March 2010, he was initially responsible for managing the research team, and then his role later expanded to lead the entire engineering department. Under his leadership, BBTV’s tech team has become one of the leading and most innovative teams in digital video space, building several internal and external products (including VISO Catalyst, VISO Collab, VISO Prism, VISO NOVI, and VISO Mine) as well as filing several patents. Mehrdad has an in-depth knowledge of digital signal processing, machine learning, and pattern recognition algorithms. He holds a PhD in Electrical Engineering from the University of British Columbia (UBC), where he was nominated for NSERC’s Doctoral Prize Award. He is an author on more than 30 journal and conference papers with a focus on pattern recognition, machine learning and intelligent algorithms. He previously held positions in the tech/education industry including roles as a research associate and sessional lecturer at UBC, as well as consulting with several companies (INETCO, BC Mining Research, and STC enterprises). He was the co-chair of the IEEE Signal Processing Chapter in Vancouver for two years.