We’re excited to hold our annual Robotics and AI Symposium again this year on October 12, 2023! As in previous years, Amber Mac will once again be our MC and debate moderator for the day. Our debate posters this year were also designed using Midjourney too!
Join us in person for lively debates and interesting discussions around robotics, artificial intelligence, and human-machine interaction!
RAIS2023 is brought to you in part with the generous support of the J. Armand Bombardier Foundation.
|Opening Remarks by Dr. Joshua Marshall, Institute Director
Dr. Angela Schoellig
Battle of the Brains: Can universities compete with industrial labs in AI research?
Our panel will feature Dr. Ting Hu (Queen’s), Dr. Ahmad Beriami (Google), Dr. Dan Desjardins (Distributed), and Dr. Ali Etemad (Queen’s).
|Networking Lunch, Research Poster Competition
We will be serving lunch in our exhibition area alongside our Research Poster Competition and exhibitor booths.
Good Bot Bad Bot: Is robotics helping or hindering progress on UN Sustainable Development Goals?
Our panel will feature Dr. Heather Aldersey (Queen’s), Dr. Michael Jenkin (York), Dr. Jackson Crane (Queen’s), and Dr. Melissa Greeff (Queen’s).
Dr. Angela Schoellig is an Alexander von Humboldt Professor for Robotics and Artificial Intelligence at the Technical University of Munich. She is also an Associate Professor at the University of Toronto Institute for Aerospace Studies and a Faculty Member of the Vector Institute in Toronto. Angela 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. In Canada, she has held a Canada Research Chair (Tier 2) in Machine Learning for Robotics and Control and a Canada CIFAR Chair in Artificial Intelligence, and has been a principal investigator of the NSERC Canadian Robotics Network. She is a recipient of 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 is the four-time winner of the North-American SAE AutoDrive Challenge (2018-21).
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).
It’s no secret that AI research is heavily reliant on access to the computing resources, particularly GPU computing. In the race to develop new technologies and publish new work in top journals, computational speed is incredibly important. However, GPU compute clusters are expensive to acquire and maintain and it’s difficult for university researchers to keep buying new computing hardware. Private companies, on the other hand, have more resources to acquire and maintain newer and faster equipment. Meta AI, for example, has a “22,000 NVIDIA V100 Tensor Core GPUs in a single cluster that performs 35,000 training jobs a day.” Given the disparity in ability to acquire the critical computing hardware, it begs the question: “Can universities compete with industrial labs in AI research?”
Our debate panel will include:
Dr. Ting Hu, Associate Professor, School of Computing, Queen’s University
Dr. Ting Hu received her postdoctoral and PhD training from the Geisel School of Medicine, Dartmouth College, and the Department of Computer Science, Memorial University, respectively. Her research focus lies on two inter-related areas, bio-inspired intelligent computing and bioinformatics. She is interested in 1) designing robust and interpretable evolutionary learning algorithms, a creative approach to AI, and 2) mining large-scale biomedical data using complex networks and machine learning techniques.
Dr. Dan Desjardins, CEO of Distributive
Dr. Desjardins is the CEO of Distributive, the Kingston-based company developing the Distributive Compute Protocol (DCP), a next-generation distributed computing platform built on web technology. DCP stitches together all of the computers and laptops in a room or building to form a supercomputer for use by data scientists, devops engineers, and computational scientists. Dan has a PhD in Physics from Queen’s University, and he himself needs a lot of computing power for his electrodynamics research. Prior to Distributive, Dan served 18 years in the Royal Canadian Air Force as a CC130H Hercules military search and rescue pilot and as an Assistant Professor of Physics and Space Science at the Royal Military College of Canada. Dan ranked among the top hundred candidates during Canada’s 2016 astronaut recruitment campaign.
Dr. Ahmad Beirami, Google Research
Ahmad Beirami is a research scientist at Google Research, leading research efforts on building safe, helpful, and scalable generative language models. At Meta AI, he led research to power the next generation of virtual digital assistants with AR/VR capabilities through robust generative language modeling. At Electronic Arts, he led the AI agent research program for automated playtesting of video games and cooperative reinforcement learning. Before moving to industry in 2018, he held a joint postdoctoral fellow position at Harvard & MIT, focused on problems in the intersection of core machine learning and information theory. He is the recipient of the 2015 Sigma Xi Best PhD Thesis Award from Georgia Tech.
Dr. Ali Etemad, Electrical and Computer Engineering, Ingenuity Labs Research Institute, Queen’s University
Dr. Etemad is an Associate Professor, as well as a Mitchell Professor in AI for Human Sensing & Understanding at the Department of Electrical and Computer Engineering, Queen’s University, Canada, where he leads the Ambient Intelligence and Interactive Machines (Aiim) lab. He is also a faculty member at Ingenuity Labs Research Institute. He received his MASc and PhD degrees in Electrical and Computer Engineering from Carleton University, Ottawa, Canada, in 2009 and 2014, respectively. His main areas of research are machine learning and deep learning focused on human-centered applications with wearables, smart devices, and smart environments. Prior to joining Queen’s, he led AI and machine learning teams in the industry.
Please visit the Aiim Lab for more information.
As part of a shared blueprint for peace and prosperity for people and the planet, now and into the future, the 2030 Agenda for Sustainable Development was adopted by all United Nations Member States in 2015. The agenda includes 17 Sustainable Development Goals (SDGs) aimed at improving the quality of human life around the world by the year 2030. Queen’s University has committed to aligning its activities in research, teaching, outreach, and stewardship toward advancing the UN SDGs and publishes an annual report around advancing societal impact.
Patrick Deane, Principal and Vice-Chancellor, Queen’s University
At Queen’s, we believe our community – our people – will help solve the world’s most significant and urgent challenges, through our intellectual curiosity, passion to achieve, and commitment to collaboration.
The application of AI and robotics has had an enormous impact on improving the operations and success of many business in the manufacturing, mining, and medical spaces. Canadian company MDA builds the only giant robotic space crane in the world that is critical to building space stations in orbit around the earth and the moon. However, there is some evidence that robots can have a negative impacts as well. So we ask the question: Is robotics helping or hindering our progress on UN Sustainable Development Goals?”
Our debate panel will include:
Dr. Heather Aldersey, School of Rehabilitation Therapy, Queen’s University
Dr. Aldersey‘s research program aims to promote the full inclusion of people with disabilities globally, with a particular focus in low- and middle-income countries. She works towards achieving this aim by examining support structures for people with disabilities and their families, evaluating the processes and outcomes of implementing community based rehabilitation programs, and translating findings to inform disability policy and practice. Dr. Aldersey’s scholarship is to draw upon local strengths and capabilities and seeks to improve the quality of life of people with disabilities and their families globally. She is also the Queen’s Special Advisor to the Principal on United Nations’ Sustainable Development Goals.
Dr. Michael Jenkin, Computer Science and Engineering, York University
Dr. Jenkin is a Professor of Computer Science and Engineering and a member of the Centre for Vision Research at York University. Working in the fields of visually guided autonomous robots and virtual reality, he has published over 150 research papers, including co-authoring Computational Principles of Mobile Robotics with Gregory Dudek and a series of co-edited books on human and machine vision with Laurence Harris. Dr. Jenkin’s current research interests include: work on sensing strategies for AQUA, an amphibious autonomous robot being developed as a collaboration between Dalhousie University, McGill University and York University; the development of tools and techniques to support crime scene investigation; and the understanding of the perception of self-motion and orientation in unusual environments including microgravity.
Dr. Jackson Crane, Mechanical and Materials Engineering, Queen’s University
Dr. Crane’s research is in renewable energy conversion technologies, electrocatalysis, and low-carbon combustion. His current research focuses on detonation fundamentals with application to high-efficiency engines. He is also active in the area of alternative fuel synthesis via CO2-reduction electrocatalysis. Dr. Crane did his postdoctoral work at Queen’s University in electrocatalysis. He received his PhD and MSc from Stanford University where he studied detonation kinetics and was an NSF Graduate Research Fellow and a Stanford Graduate Fellow. Dr. Crane also worked as an Associate at the sustainability-focused non-profit Rocky Mountain Institute, and as an engineering consultant in the nuclear power industry. He received his SB from MIT.
Please visit the Crane Energy Group for more information.
Dr. Melissa Greeff, Electrical and Computer Engineering, Ingenuity Labs Research Institute, Queen’s University
Dr. Greeff is an Assistant Professor in the department of Electrical and Computer Engineering. She is a faculty affiliate with the Vector Institute for Artificial Intelligence. Her research interests include aerial robots, vision-based navigation, and safe learning-based control. She obtained her BASc in Engineering Science and her PhD from the University of Toronto.
Please visit the Robora Lab for more information.
Please also have a look at the events from RAIS2022!