Modern Artificial Intelligence | NYU Tandon School of Engineering

Modern Artificial Intelligence

ECE special seminar series
addressing the most important new research in the world of artificial intelligence (AI)

Geometric abstract image of brain


The Seminar Series in Modern Artificial Intelligence is hosted by the Department of Electrical and Computer Engineering at NYU Tandon. Organized by Professor Anna Choromanska, the series aims to bring together faculty and students to discuss the most important research trends in the world of AI. The speakers include world-renowned experts whose research is making an immense impact on the development of new machine learning techniques and technologies and helping to build a better, smarter, more-connected world. 

View the AI Seminar Series Playlist on YouTube

    Spring 2024

    Jamie Shotton

    Wayve Technologies

    "Frontiers in Embodied AI for Autonomous Driving"

    February 27, 2024

    "Gretton Headshot"

    Arthur Gretton

    University of College London

    "Learning to act in noisy contexts using deep proxy learning"

    March 11, 2024

    Drew Bagnell Headshot

    Drew Bagnell


    "An Invitation to Imitation"

    April 15, 2024

    Headshot of Samantha Wood

    Dr. Samantha Wood

    Indiana University Bloomington

    "Reverse-Engineering the “Recipe” for Object Perception"

    April 30, 2024

    Fall 2023

    Maria Florina Balcan

    Carnegie Mellon University

    "Machine Learning for Algorithm Design"

    September 26, 2023

    Sanja Fidler

    University of Toronto

    "Generative AI for 3D Content"

    October 24, 2023

    Spring 2023

    Alex Smola

    Amazon Web Services

    "AutoGluon: Empowering (Multimodal) AutoML for the Next 10 Million Users"

    February 8, 2023

    Nicolò Cesa-Bianchi

    University of Milan and Polytechnic University of Milan, Italy

    "Online learning, bandits, and digital markets"

    March 28, 2023

    Ulrike von Luxburg

    University of Tuebingen, Germany

    "Explainability and regulation"

    May 9, 2023

    Fall 2022

    Robert Schapire

    Microsoft Research

    "Convex Analysis at Infinity: An Introduction to Astral Space"

    John Langford


    "Discovering an agent's controllable latent state"

    Chris Wiggins

    Columbia University, New York Times

    "Data Science at The New York Times"

    Fall 2021

    Michael Friedlander

    University of British Columbia

    "Geometric Duality in Optimization"

    Karl J. Friston

    Karl J. Friston

    Queen Square Institute of Neurology, University College London

    "Deep Inference"

    Faye Cobb

    Dr. Fay Cobb Payton

    North Carolina State University

    "Coding, Coded & Counting: A Bias Continuum"


    Spring 2021

    Sham Kakade

    Sham Kakade

    University of Washington

    "Towards a Theory of Generalization in Reinforcement Learning"

    Mutale Nkonde

    Mutale Nkonde

    Founding Director of AI for the People

    "Elections, Online Chatter and Content Moderation"

    Joelle Pineau

    Facebook and McGill University

    "Building Reproducible, Reusable, and Robust Deep Reinforcement Learning Systems"

    Danielle Belgrave and Niranjani Prasad

    Microsoft Research Cambridge

    "Machine Learning for Personalised Healthcare: Opportunities, Challenges and Insights"

    Spring 2020

    Jan Kautz, VP of Learning and Perception Research at NVIDIA

    "Generative Models for Image Synthesis"
    February 13, 2020

    Gabor Lugosi, Pompeu Fabra University

    "Archeology of Random Trees"
    Thursday, March 5, 2020

    Fall 2019

    Leon Bottou

    Leon Bottou, Facebook AI Research

    "Learning Representations Using Causal Invariance"

    Francis Bach

    Francis Bach, INRIA, Paris France

    "Distributed Machine Learning over Networks"

    Raia Hadsell

    Raia Hadsell, Head of Robotics Research at DeepMind

    "Challenges for Deep Reinforcement Learning in Complex Environments"


    Spring 2019

    Martial Hebert

    Martial Hebert, Carnegie Mellon University

    "Research challenges in using computer vision in robotics systems"

    Tony Jebara

    Tony Jebara, Netflix

    "Machine Learning for Personalization"

    Manuela Veloso

    Manuela Veloso, JP Morgan Chase

    "Towards a Lasting Human-AI Interaction"

    Eric Kandel

    Eric Kandel, Columbia University

    "The Biology of Memory and Age-Related Memory Loss"

    Fall 2018

    Anima Anandkumar

    Anima Anandkumar, Caltech

    "The AI Trinity: Data + Algorithms + Infrastructure"

    Kai-Fu Lee

    Kai-Fu Lee, Sinovation Ventures

    "The Era of Artificial Intelligence"

    David Blei

    David Blei, Columbia University

    "The Blessings of Multiple Causes"

    Richard J. Roberts

    Richard J. Roberts, New England Biolabs, Inc.

    "The Path to the Nobel Prize"

    Fall 2017

    Yann LeCun

    Yann LeCun, Facebook AI Research

    "Obstacles to Progress in Deep Learning & AI"

    Yoshua Bengio

    Yoshua Bengio, Montreal Institute for Learning Algorithms

    "GANs and Unsupervised Representation Learning"

    Stefano Soatto

    Stefano Soatto, UCLA Vision Lab

    "The Information Knot Tying Sensing and Action"

    Vladimir Vapnik

    Vladimir Vapnik, Columbia University

    "Rethinking Statistical Learning Theory"