Events

CAIDA proudly hosts events to engage and connect the BC AI community and beyond.  CAIDA has three ongoing seminar series: AI & Fundamentals, AI & Applications, and AI & Ethics; attracting more than 2000 attendees since September 2019.  CAIDA also hosts larger events: our first AI showcase "Emerging Technologies: BC's AI Showcase" was in November 2020 and had over 700 registrants, and CAIDA’s 2021 Open House had almost 200 registrants.  We look forward to hosting more events to help connect the AI community.  If you would like to be notified about our upcoming events, please contact admin@caida.ubc.ca to be added to our email list.

Past Events

SeminarOperationalizing Counterfactual Metrics: Incentives, Ranking, and Information Asymmetry - Serena Wang, PhD Student, UC Berkeley
November 30, 2023
SeminarAchieving Codec Telepresence - Michael Zollhoefer, Director, Reality Labs Research (RL-R), Meta
November 20, 2023
SeminarDiffusion Models: From Foundations to Image, Video and 3D Content Creation - Karsten Kreis, Senior Research Scientists, NVIDIA’s Toronto AI Lab
July 18, 2023
SeminarReconstructing Training Data from Model Gradient, Provably - Qi Lei, Assistant Professor, NYU
July 11, 2023
SeminarMultimodal AI in the Era of Gigantic Pretrained Language Models: Challenges and (Some) Remedies - Boyang Albert Li, Associate Professor, Nanyang Technological University
June 26, 2023
SeminarReconstructing and Synthesizing 3D Scenes - Young Min Kim, Associate Professor, Seoul National University
June 23, 2023
SeminarStatistical implications of group invariance of distributions - Peter Orbanz, Professor, University College London
April 20, 2023
SeminarDifferentially Private Fine-tuning of Language Models - Gautam Kamath, Assistant Professor, University of Waterloo
August 29, 2022
SeminarCausality and Autoencoders in the Light of Drug Repurposing for COVID-19 - Caroline Uhler, Associate Professor, MIT
March 1, 2022
SeminarLearning Novel Classes and Attributes While Wandering Within a World - Richard Zemel, Professor, University of Toronto
November 22, 2021
SeminarComputational Visual Pathways for Multi-Task Learning and Simulation - Rogerio Feris, Principal Scientist and Manager, MIT-IBM Watson AI Lab
November 30, 2021
SeminarDeep learning for the Physical Sciences - Max Welling, Professor, University of Amsterdam
November 16, 2021
SeminarTractable Probabilistic Reasoning for Trustworthy AI - YooJung Choi, Ph.D. candidate, UCLA
November 24, 2021
SeminarThe Provable Effectiveness of Policy Gradient Methods in Reinforcement Learning and Controls - Sham Kakade, Professor, University of Washington; Microsoft Research
September 27, 2021
SeminarRobots that Rapidly Adapt to Diverse Tasks and Environments - Deepak Pathak, Assistant Professor, Carnegie Mellon University
July 28, 2021
SeminarNormalizing Flows in Theory and Practice - Marcus Brubaker, Assistant Professor, York University; Faculty Affiliate, Vector Institute
April 27, 2021
SeminarInvariance in machine learning methods: What, why, and then? - Benjamin Bloem-Reddy, Assistant Professor, UBC
March 31, 2021
SeminarLearning Generative Models of 3D Shapes: From Implicit Functions to Structured Representations - Richard (Hao) Zhang, Professor, SFU
February 22, 2021
SeminarPOSTPONED: A future with self-driving vehicles - Raquel Urtasun: Professor, University of Toronto; Chief Scientist, Uber ATG
January 18, 2021
SeminarActive Learning by Learning - Hsuan-Tien Lin, Professor, National Taiwan University; Chief Data Science Consultant, Appier Inc.
January 14, 2021
SeminarOvercoming Mode Collapse and the Curse of Dimensionality - Ke Li, Assistant Professor, Simon Fraser University
December 2, 2020
SeminarA tour of distributional reinforcement learning - Marc G. Bellemare, Research Scientist, Google Brain, Mila
November 18, 2020
SeminarIn Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors, Daniel Roy and Jeffrey Negrea
October 26, 2020
SeminarIntuitive Understanding of Generalization in Neural Networks - Jimmy Ba, Assistant Professor, University of Toronto
October 23, 2020
SeminarThe Non-Stochastic Control Framework - Naman Agarwal, Research Scientist, Google AI, Princeton
October 5, 2020