Bio: Irina Rish is an associate professor in the Computer Science and Operations Research department at the Université de Montréal (UdeM) and a core member of Mila – Quebec AI Institute. She holds MSc and PhD in AI from University of California, Irvine and MSc in Applied Mathematics from Moscow Gubkin Institute. Dr. Rish’s research focus is on machine learning, neural data analysis and neuroscience-inspired AI. Her current research interests include continual lifelong learning, optimization algorithms for deep neural networks, sparse modeling and probabilistic inference, dialog generation, biologically plausible reinforcement learning, and dynamical systems approaches to brain imaging analysis. Before joining UdeM and Mila in 2019, Irina was a research scientist at the IBM T.J. Watson Research Center, where she worked on various projects at the intersection of neuroscience and AI, and led the Neuro-AI challenge. She received multiple IBM awards, including IBM Eminence & Excellence Award and IBM Outstanding Innovation Award in 2018, IBM Outstanding Technical Achievement Award in 2017, and IBM Research Accomplishment Award in 2009.
Zachary Chase Lipton
Bio: Zachary Chase Lipton is an assistant professor of Operations Research and Machine Learning at Carnegie Mellon University. His research spans core machine learning methods and their social impact and addresses diverse application areas, including clinical medicine and natural language processing. Current research focuses include robustness under distribution shift, cancer screening, the effective and equitable allocation of organs, and the intersection of causal thinking and the messy high-dimensional data that characterizes modern deep learning applications. He is the founder of the Approximately Correct blog (approximatelycorrect.com) and a co-author of Dive Into Deep Learning, an interactive open-source book drafted entirely through Jupyter notebooks. Find on Twitter (@zacharylipton) or GitHub (@zackchase).
Bio: Natalie Schluter is Senior Research Scientist at Google Brain and Associate Professor in NLP and Data Science at the IT University (ITU), in Copenhagen, Denmark. At ITU she co-developed and now leads the first Data Science programme in Denmark, a BSc. Before coming to ITU, she held positions as Chief Analyst at MobilePay, Danske Bank, and Postdoctoral Researcher at the University of Copenhagen and Malmö University. Natalie’s primary research interests are in algorithms and experiment methodology for the development statistical and combinatorial models of natural language understanding and generation, especially under computationally “hard” settings. She holds a PhD in NLP from Dublin City University’s School of Computing. She holds a further four degrees: an MSc in Mathematics from Trinity College, Dublin, a BSc in Mathematics and MA in Linguistics from the University of Montreal, and a BA in French and Spanish. Natalie is currently serving as Equity Director for the ACL, after serving as ACL 2020 co-Programme Chair. She is a Canadian, living in Copenhagen for the past 10 years with her two daughters.
A panel on Ethics, Fairness, and Bias in AI will be moderated by Abhishek Gupta and will feature the keynote speakers as panelists: Natalie Schluter, Zack Chase Lipton, and Irina Rish.
Submit your questions to the panel here!
Bio: Abhishek Gupta is the founder of Montreal AI Ethics Institute (https://montrealethics.ai ) and a Machine Learning Engineer at Microsoft where he serves on the CSE Responsible AI Board. His research focuses on applied technical and policy methods to address ethical, safety and inclusivity concerns in using AI in different domains. He has built the largest community driven, public consultation group on AI Ethics in the world. His work on public competence building in AI Ethics has been recognized by governments from North America, Europe, Asia, and Oceania. More information on his work can be found at https://atg-abhishek.github.io. He is a Faculty Associate at the Frankfurt Big Data Lab at the Goethe University, a guest lecturer at the McGill University School of Continuing Studies for the Data Science in Business Decisions course and a Visiting AI Ethics Researcher on the Future of Work for the US State Department representing Canada.