Panelists

Joelle Pineau

Joelle Pineau is the Vice President of AI Research at Meta, supporting labs across North America and Europe. She is also a faculty member at Mila and a Professor and William Dawson Scholar at the School of Computer Science at McGill University, where she co-directs the Reasoning and Learning Lab. She holds a BASc in Engineering from the University of Waterloo, and an MSc and PhD in Robotics from Carnegie Mellon University. Dr. Pineau's research focuses on developing new models and algorithms for planning and learning in complex partially-observable domains, and on applying these algorithms to complex problems in robotics, health care, games and conversational agents.

Learn more about her work at: https://www.cs.mcgill.ca/~jpineau/

Pascale Fung

Pascale Fung is a Chair Professor at the Department of Electronic & Computer Engineering at The Hong Kong University of Science & Technology (HKUST), and a visiting professor at the Central Academy of Fine Arts in Beijing. She is an elected Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) for her "significant contributions to the field of conversational AI and to the development of ethical AI principles and algorithms", an elected Fellow of the Association for Computational Linguistics (ACL) for her significant contributions towards statistical NLP, comparable corpora, and building intelligent systems that can understand and empathize with humans. 

She is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE), an elected Fellow of the International Speech Communication Association and the Director of HKUST Centre for AI Research (CAiRE), an interdisciplinary research centre on top of all four schools at HKUST. 


Learn more about her work at: https://pascale.home.ece.ust.hk/

Yao Qin

Yao Qin is an Assistant Professor at the Department of Electrical and Computer Engineering at UC Santa Barbara, affiliated with the Department of Computer Science. She is also a senior research scientist at Google Research. She obtained her PhD degree at UC San Diego in Computer Science in 2020 and worked at Google Research afterwards. Her research interests primarily focus on robustness in multi-modality models, fairness in generative modeling and AI for healthcare, particularly for diabetes. She has served as Area Chair for ICLR-2023 and ICCV-2023 and co-local Chair for KDD-2023. In addition, she has been recognized as EECS Rising Star at MIT, 2021.

Learn more about her at: https://www.ece.ucsb.edu/people/faculty/yao-qin 

Rihab Gorsane

Rihab Gorsane is a Research Engineer and a team lead at InstaDeep. She is currently working on Reinforcement Learning based projects for industrial applications where she is helping to automate the scheduling, routing, and dispatching of trains at a large scale for a national rail operator. Rihab is also involved in research projects within the company focusing on Multi-Agent RL evaluation. She is passionate about AI skills development in Africa, is a Google developer expert in Machine Learning, and has taught DL/RL courses at Tunisian universities. 

Nataša Tagasovska (moderator)

Nataša is a Senior Machine Learning Scientist at Prescient Design, Genentech since January 2022 where she joined the effort of applying ML to accelerate drug design. Her research interests are related to causal learning, generative models and multi-property optimization. Before she was a Senior Data Scientist at the SDSC at EPFL-ETHZ where she worked on translational projects applying ML to domain-specific and social science research efforts. She holds a PhD in Statistics from University of Lausanne and a BS and MSC in Computer Science and Engineering. During her studies she interend at Facebook (Meta) AI Research and NATO.