Conference 2022

18 - 19 February 2022

AN AI CONFERENCE: HUMAN COMPUTER INTERACTION

ABOUT

From climate change to political polarization, global pandemics to mental illness, we live in a world characterized by a web of urgent crises. The time to meet the challenges of the future is now.

Is artificial intelligence our way to utopia? Or is machine learning a challenge we must face?

The University of Toronto AI conference is a two day event, attempting to answer these questions. A multidisciplinary gathering of the brightest minds from across the world with the goal of inspiring the next generation of thinkers, this is not an event to miss.

The conference will be taking place on the 18th and 19th of February 2022 and we are expecting 600+ students, researchers, and industry leaders.

COVID-19

COVID-19 UPDATE

Due to the ongoing spread of COVID-19 and the emergence of the Omicron variant, we have moved the conference online this year as well.

SPEAKERS

OUR SPEAKERS

Parisa Rashidi

Parisa Rashidi, Ph.D., is an associate professor in the J. Crayton Pruitt Family Department of Biomedical Engineering. Dr. Rashidi’s research aims to develop intelligent patient monitoring systems using artificial intelligence and sensing technology. Her lab is working towards predicting acuity state of patients in real-time.

Diana Inkpen

Diana Inkpen, Ph.D., is a professor at the University of Ottawa. Her interests lie in Natural Language Understanding and Generation, Lexical Semantics, Information Retrieval, Information Extraction, Automatic Text Classification, and Intelligent Agents for the Semantic Web. Currently she is researching emotion analysis, social media text, automatic text classification and information extraction from medical texts with the help of NLP.

Frank Rudzicz

Frank Rudzicz is an associate professor at the University of Toronto specializing in speech, language, machine-learning, brain-computer interfaces, healthcare, and applying AI into practice. Frank is currently working to enhance surgical safety practices with the help of machine learning.

Geoffrey Hinton

Turing Award recipient Geoffrey Hinton is an emeritus professor at the University of Toronto, as well as a VP Engineering fellow at Google and Chief Scientific Adviser at the Vector Institute. His research group in Toronto made major breakthroughs in deep learning that revolutionized speech recognition and object classification. Widely considered one of the Godfathers of AI, Professor Hinton was one of the researchers who introduced the backpropagation algorithm and the first to use backpropagation for learning word embeddings.

Alán Aspuru-Guzik

Alán Aspuru-Guzik is a professor of Chemistry and Computer Science at the University of Toronto and is also the Canada 150 Research Chair in Theoretical Chemistry and a Canada CIFAR AI Chair at the Vector Institute. He is a CIFAR Lebovic Fellow in the Biologically Inspired Solar Energy program. Alán also holds a Google Industrial Research Chair in Quantum Computing. Alán conducts research in the interfaces of quantum information, chemistry, machine learning and chemistry, and was a pioneer in the development of algorithms and experimental implementations of quantum computers and quantum simulators dedicated to chemical systems.

Nicolas Papernot

Nicolas Papernot is an assistant professor at the University of Toronto in Electrical and Computer Engineering and Computer Science, a Canada CIFAR AI Chair faculty member at the Vector Institute, a faculty affiliate at the Schwartz Reisman Institute, and a Research Scientist at Google Brain. His research is at the intersection of security, privacy, and machine learning, including the security and privacy of machine learning.

Eugene Wen

Eugene Wen is the Vice President for Group Advanced Analytics at Manulife Financial. He leads data scientist teams in supporting Group Functions, creates governance and policy frameworks for analytics, and establishes research and development (R&D) capabilities in AI/Advanced Analytics to support businesses across the company. He holds a global mandate for Fraud Analytics.
Eugene is passionate about using data and analysis to support strategic and operational decision-making. He spends substantial time in recruiting and developing advanced analytics talents.

Tomi Poutaten

Tomi is co-founder of Layer 6 and serves as TD Bank Group's Chief AI Officer. Prior to Layer 6, Tomi founded three technology companies with exits to Microsoft and Yahoo!. Tomi is a co-founder of the Vector Institute. He is a founding fellow at the Creative Destructive Lab, the world's largest AI venture accelerator. Tomi holds an MSc in Computer Engineering and an MBA from the University of Toronto.

Rama Akkiraju

Rama Akkiraju is an IBM Fellow, Distinguished Engineer, and CTO of AI Operations at IBM. Named by Forbes magazine as one of the ‘Top 20 Women in AI Research’ in 2017, she performs research in the field of artificial intelligence, particularly helming the team responsible for the "Tone Analyzer”.

Stephan Zheng

Stephan Zheng is the lead research scientist of the AI Economist team at Salesforce research, where he uses deep reinforcement learning and data-driven multi-agent simulations to design economic policies.
Zheng grew up in the Netherlands and completed his PhD carrying out machine learning in multi-agent worlds at Caltech (2018). Notably, he wrote a Master’s thesis on exotic dualities in topological string theory and received the 2011 Lorentz Graduation Prize.

Maya Ackerman

Professor Maya Ackerman is an expert on AI and Computational Creativity, with unique insight into the commercialization of cutting-edge research on human-AI collaboration. Named "Woman of Influence" by the Silicon Valley Business Journal, Professor Ackerman has integrated her passion of music and song to found WaveAI that focuses on development of AI-based musical assistance for hobbyists and professionals alike.

Yale Song

Yale Song is a Senior Researcher and a founding member of the Computer Vision Group at Microsoft Research in Redmond. His research is centered around Computer Vision and Machine Learning, especially on learning from unlabeled and noisy data. His most current research is focused on unsupervised/self-supervised learning from video data, leveraging spatio-temporal and multimodal structures.

Max Tegmark

Max Tegmark is a professor of physics at the Massachusetts Institute of Technology and the president of the Future of Life Institute. His research focuses on linking physics and machine learning: using physics-based techniques to better understand biological and artificial intelligence.

Animesh Garg

Professor Animesh Garg is an assistant professor of Computer Science at the University of Toronto, a Faculty Member at the Vector Institute, and a senior research scientist at NVIDIA. His research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments.

WHY ATTEND?

We are using Hubilo this year! Hubilo is a virtual event platform designed to engage audiences through virtual branded exhibits and easy communication with a simple user interface.

INSTITUTIONS + SPONSORS

PARTICIPATING INSTITUTIONS

18 - 19 February 2022

AN AI CONFERENCE: HUMAN COMPUTER INTERACTION

ABOUT

COVID-19 UPDATE

OUR SPEAKERS

WHY ATTEND?

PARTICIPATING INSTITUTIONS

OUR SPONSORS

Solar Sponsors

Planetary Sponsors

Lunar Sponsors