Modern Artificial Intelligence
ECE special seminar series
addressing the most important new research in the world of artificial intelligence (AI)
Live Stream
Generative Models for Image Synthesis
Jan Kautz, NVIDIA
Live Streaming on February 13, 2020
About
NYU Tandon's Department of Electrical and Computer Engineering hosted a seminar series addressing the most important new research in the world of artificial intelligence (AI), featuring researchers who have made fundamental contributions to the emerging technology. The seminar series was organized by Professor Anna Choromanska in Fall 2017.
View the AI Seminar Series Playlist on YouTube
Spring 2020
Jan Kautz, VP of Learning and Perception Research at NVIDIA
"Generative Models for Image Synthesis"
February 13, 2020
- Watch the lecture (forthcoming)
- Event Details
Gabor Lugosi, Pompeu Fabra University
"Archeology of Random Trees"
Thursday, March 5, 2020
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- Event Details
Nicolò Cesa-Bianchi, Università degli Studi di Milano
"Machine Learning and Sequential Decision Making"
Thursday, April 2, 2020
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- Event Details
Fall 2019 Seminars
Leon Bottou, Facebook AI Research
"Learning Representations Using Causal Invariance"
Francis Bach, INRIA, Paris France
"Distributed Machine Learning over Networks"
Raia Hadsell, Head of Robotics Research at DeepMind
"Challenges for Deep Reinforcement Learning in Complex Environments"
Spring 2019 Seminars
Martial Hebert, Carnegie Mellon University
"Research challenges in using computer vision in robotics systems"
Fall 2018 Seminars
Anima Anandkumar, Caltech
"The AI Trinity: Data + Algorithms + Infrastructure"
Kai-Fu Lee, Sinovation Ventures
"The Era of Artificial Intelligence"
Richard J. Roberts, New England Biolabs, Inc.
"The Path to the Nobel Prize"
Fall 2017 Seminars
Yann LeCun, Facebook AI Research
"Obstacles to Progress in Deep Learning & AI"
Yoshua Bengio, Montreal Institute for Learning Algorithms
"GANs and Unsupervised Representation Learning"
Stefano Soatto, UCLA Vision Lab
"The Information Knot Tying Sensing and Action"
Vladimir Vapnik, Columbia University
"Rethinking Statistical Learning Theory"