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June 8, 2021 @ 9:30 am - 1:00 pm
Join the Vector Institute to explore the impact of artificial intelligence (AI) on the new era of mobility. This online, half-day symposium will feature technical talks and a panel discussion with Vector experts and industry practitioners, covering key areas in mobility such as advanced robotics, and autonomous and electric vehicles, looking at their applications and impacts across sectors.”
We are entering a new era in mobility in which AI plays a central role. This era is often described as one of connected, autonomous, shared and electric (CASE) mobility. While this transformation is unlocking major opportunities—such as financial and operational efficiencies, more efficient movement of people and goods, and increased safety and sustainability—there are many challenges in taking AI-related mobility research and applying it to the real world. This event will focus on exploring the fascinating and complex intersection of mobility research and industry application
This event is open to:
Vector researchers who wish to hear from other researchers in the Vector community who are focused on machine, deep, and reinforcement learning applied to areas such as autonomous vehicles and advanced robotics.
Vector students and new grads interested in learning about this interesting application space for AI, and connecting with Vector Industry Sponsors who are hiring.
Vector Industry Sponsors and their employees that are looking to learn about the latest advances and trends in AI applied to mobility, both from researchers and other industry professionals.
This event is open to Vector Sponsors, Vector Researchers, and Vector students only. Any registration that is found not to be a Vector Sponsor, Vector Researcher or Vector student will be asked to provide verification and, if unable to do so, will not be able to attend the event.Register
- 9:30 AM Opening Remarks (Shingai Manjengwa, Vector Institute)
- 9:35 AM Research Talk: The Nexus of Connected Autonomous Electric Vehicles and AI-enabled Transactive Energy Systems (Melike Erol-Kantarci, University of Ottawa)
- 10:05 AM Industry Talk: Industry mega-trends in mobility and AI (Todd Deaville, Magna International)
- 10:40 AM Research Talk: Robots in the Wild: Towards Ensuring Safety During and After Learning (Florian Shkruti, University of Toronto)
- 11:15 AM Industry Panel: Barriers to the adoption of AI in mobility (Moderated by Deval Pandya, Vector Institute)
- 11:50 AM Industry Talk: A Ride to the Future: Opportunities and challenges in autonomous rail (David Beach, Thales Canada)
- 12:25 PM Research Talk: Machine learning for mobile robots: safety, data efficiency, and fast adaptation (Angela Schoellig, University of Toronto)
- 12:55 PM Closing Remarks (Shingai Manjengwa, Vector Institute)
The Nexus of Connected Autonomous Electric Vehicles and AI-enabled Transactive Energy Systems
by Melike Erol-Kantarci, Canada Research Chair (Tier 2) on AI-Enabled Next-Generation Wireless Networks, Associate Professor and Founding Director, Networked Systems and Communications Research (NETCORE) Lab, School of Electrical Engineering and Computer Science, University of Ottawa, Faculty Affiliate, Vector Institute
Battery and charging technologies of Connected Autonomous Electric Vehicles (CAEVs), as well as their smart, two-way interaction with the power grid are of extreme importance to their success in the future mobility ecosystem. Emerging transactive energy systems, boosted by machine learning tools, are offering many innovations that are arising from CAEV and power grid interactions. This talk will cover the exciting opportunities in the nexus of CAEVs and AI-enabled transactive energy systems.
Industry mega-trends in mobility and AI
by Todd Deaville, Director of Engineering and Research & Development, Magna International
What are the mega-trends driving our mobility future? Where does AI intersect & have the most profound impact? This talk will answer these questions while also examining some of the most exciting challenges and opportunities for researchers and entrepreneurs in the space from the point of view of Canada’s leading mobility technology company for automakers.
Robots in the Wild: Towards Ensuring Safety During and After Learning
by Florian Shkruti, Assistant Professor, Computer Science; Department of Computer Science, University of Toronto; Faculty Member, UofT Robotics Institute; Faculty Affiliate, Vector Institute
Autonomous vehicles that rely on learned components or even end-to-end systems for decision-making and control are being deployed in real-world environments with increasing frequency. The promise of these methods is that adaptation to real-world data will exceed the performance of traditional manually-engineered pipelines. Yet, despite many positive examples, full and robust robot autonomy in real-world environments remains elusive due lack of safety guarantees in the face of rare events. In this talk I will argue that in order to increase the reliability of autonomous vehicles we need to pursue at least two challenging research directions: (a) automatically generating photorealistic simulation scenarios that are tailored to stress-test the perception and planning pipelines of autonomous vehicles, and (b) providing safety guarantees during exploration in reinforcement learning. I will present ongoing work in my lab that addresses both of these questions.
Machine learning for mobile robots: safety, data efficiency, and fast adaptation
by Angela Schoellig, Associate Professor, the University of Toronto Institute for Aerospace Studies; Faculty Member, Vector Institute; Canada Research Chair (Tier 2), Machine Learning for Robotics and Control; Canada CIFAR Chair in Artificial Intelligence
In my talk, I will give an overview of our work on machine learning for mobile robots, including self-driving vehicles, drones and mobile manipulators. I will show how machine learning can be integrated into the perception-action loop of a robot without jeopardizing the robot’s safety. In particular, my talk focuses on approaches that: 1) leverage both prior knowledge about the robot and its environment and data collected by the robot during operation; 2) can handle changes in the environment such as different weather conditions or wear-and-tear of the robot; and 3) are data-efficient in multi-task, multi-robot scenarios. I will show examples of learning-enabled robot algorithms outperforming traditional approaches on robots operating in the real world.
Industry Panel – Barriers to adoption of AI in mobility moderated by Deval Pandya Director, AI Engineering, Vector Institute
What are the most critical barriers to the successful adoption of AI-based tools and techniques in mobility-focused companies today? What are the unique challenges? How are Canadian companies navigating these? This panel discussion with industry practitioners will provide a snapshot of the opportunities and challenges facing Canadian mobility companies today.
- Leigh Copp, Operations Manager, Innovation Hub at Linamar Corporation
- Helen Glover, Innovation Principal and Research Advisor at Canadian National Railway (CN)
- Ryan Gariepy, CTO at Clearpath Robotics and OTTO Motors
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 5800 times and she has an h-index of 39. 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 and 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/6G, smart grid and electric vehicles. She is an IEEE ComSoc Distinguished Lecturer, IEEE Senior member and ACM Senior Member.
Todd Deaville joined Magna International in 1997 and currently serves as Director, Engineering and R&D, supporting Magna’s Corporate Engineering and Research and Development team on a global basis. In this role he works with academic, industry and startup company partners to identify, technically assess, and lead or support product development activities for new technology commercialization. Todd received his Bachelors of Applied Science Degree from Dalhousie University in 1997 and Masters’ of Mechanical Engineering Degree from the University of Toronto in 2010, based on the development of a novel automotive acoustics actuator. Todd has co-authored research papers and has been awarded several patents related to automotive products and manufacturing methods.
Florian Shkruti is an assistant professor of computer science at the University of Toronto and a director of the Robot Vision and Learning lab. He is a faculty member at the UofT Robotics Institute, a faculty affiliate at Vector Institute, and a distal fellow of the NSERC Canadian Robotics Network (NCRN). His research spans autonomous robotics, machine learning, computer vision, and control. The main problems he is interested in are: decision making and control under uncertainty, imitation learning, continual adaptation, 3D perception, visual exploration and search, and safe learning. He is the recipient of the Alexander Graham Bell Doctoral Award, the AAAI Robotics Fellowship, the Coxeter Scholarship in Mathematics, and the Amazon Research Award in Robotics.
Angela Schoellig is an Associate Professor at the University of Toronto Institute for Aerospace Studies and a Faculty Member of the Vector Institute. She holds a Canada Research Chair (Tier 2) in Machine Learning for Robotics and Control and a Canada CIFAR Chair in Artificial Intelligence. She is a principal investigator of the NSERC Canadian Robotics Network and of the University’s Robotics Institute. She conducts research at the intersection of robotics, controls, and machine learning. Her goal is to enhance the performance, safety, and autonomy of robots by enabling them to learn from past experiments and from each other. She is a recipient of a Alexander von Humboldt Professorship (2021), the Robotics: Science and Systems Early Career Spotlight Award (2019), a Sloan Research Fellowship (2017), and an Ontario Early Researcher Award (2017). She is one of MIT Technology Review’s Innovators Under 35 (2017), a Canada Science Leadership Program Fellow (2014), and one of Robohub’s “25 women in robotics you need to know about (2013)”. Her team won the 2018, 2019 and 2020 North-American SAE AutoDrive Challenge sponsored by General Motors. Her PhD at ETH Zurich (2013) was awarded the ETH Medal and the Dimitris N. Chorafas Foundation Award. She holds both an M.Sc. in Engineering Cybernetics from the University of Stuttgart (2008) and an M.Sc. in Engineering Science and Mechanics from the Georgia Institute of Technology (2007).
David Beach earned his Master of Applied Science from the University of Toronto Institute for Aerospace Studies, and spent over a decade working on computer vision for space applications, including robotic planetary mining, on-orbit damage inspection, and automated rendezvous and docking. He has been with Thales Canada in Toronto since 2015, and is currently the Product Line Architect with the Research and Technology group, focused on the application of advanced technology to meet the challenges of future mass transit.
Leigh Copp has been Operations Manager of the Linamar Innovation Hub since 2017. He has been with Linamar for 26 years, starting from when he was a student at McMaster University, and has played various roles across the organization. Leigh studied Engineering Physics at McMaster University and holds a degree in Electrical Engineering from Ryerson University.
Helen Glover began her career as a geomatic engineer for multinational engineering firm Aurecon before moving into innovation management at CN in 2012, living the dream of building the future freight railroad for our society’s needs. She has played pivotal roles in the implementation of train control systems and autonomous track inspection, and is CN’s expert at bringing emerging technologies to the boots on the ground.
Ryan Gariepy believes that the ubiquitous presence of autonomous robotics is not far away, and is personally driving this vision as the CTO of Clearpath Robotics and OTTO Motors. OTTO Motors provides industrial self-driving vehicles to the world’s biggest and most innovative brands for use in their manufacturing and warehousing facilities, while Clearpath Robotics is the world leader in platforms and support for academic and commercial field robotics research. He serves on the board of directors for the NSERC Canadian Robotics Network, the Open Source Robotics Foundation and is a co-founder of ROSCon, the first and largest conference for robotics developers. Ryan is also an associate with CDL-Space, an advisor to several startups and venture capital groups, a founder and former Next Generation Manufacturing Canada board of directors member. Ryan regularly speaks on topics from technology focused lectures at major universities, to policy commentary at the UN, to live interviews with CNN, BBC, and the CBC. He led the effort resulting in Clearpath being the first for-profit company to publicly speak up about the dangers of lethal autonomous weapons systems. Ryan completed both a B.A.Sc. degree in Mechatronics Engineering and a M.A.Sc. degree in Mechanical Engineering at the University of Waterloo, and has over 50 pending patents in the field of intelligent systems.
Event Host Biographies
A data scientist by profession, Shingai Manjengwa is the Director of Professional Development at the Vector Institute for Artificial Intelligence in Toronto, where she translates advanced AI research into educational programming to increase AI capacity, and drive AI adoption and innovation in industry. She serves on the advisory council for, “Accelerating the adoption of AI in healthcare, ” a program by the Michener Institute of Education at UHN and the Vector Institute to empower front-line healthcare workers with literacy and skills in AI. Shingai also serves on the board of the Institute on Governance (IOG). Shingai holds a Master’s degree in Business Analytics from New York University’s Stern School of Business.
Deval Pandya is Director of AI Engineering at Vector Institute and one of the 100 Global Future Energy Leaders with the World Energy Council. He is passionate about building Artificial Intelligence and Machine learning systems for expediting energy transition and combating Climate Change. Prior to joining Vector, Deval was leading the Data Science team at Shell focusing on application in New Energies and Asset management. During his career, he has led development of scalable machine learning applications in the domains of nature-based solutions, predictive maintenance, e-mobility, microgrid optimizations and hydrogen value chain. Deval also serves as a Director on the technical steering committee of Moja Global, A not for profit, collaborative project that brings together a community of experts to develop open-source software under Linux Foundation used for country level greenhouse gas accounting from AFOLU sector. Deval is on the task force for Digitalization in Energy at United Nations Economic Commission of Europe (UNECE) and mentor at Creative Destruction Labs. He enjoys traveling and cooking in his free time.”