Seminars
The AI3 Insights Series (AIS) is an ongoing program at the AI Innovation Institute, where distinguished leaders are invited to present lectures to the artificial intelligence community. Since it began in the Fall of 2019, the AIS has successfully hosted many prominent AI researchers and changemakers.
Other outstanding speakers of interest come as part of the Computer Science Distinguished Lecture Series (DLS). Recent visitors include Lyle Ungar, University of Pennsylvania; Rene Vidal, Johns Hopkins University; Daniel I. Rubenstein, Princeton University; and Patrick McDaniel, Pennsylvania State University.
Fall 2025
Meir Feder, Tel-Aviv University
Information-Theoretic Framework for Understanding Modern Machine-Learning
Spring 2022
Tony Zador, Yale University
The Genomic Bottleneck Algorithm for Faster Learning and Better Generalization
Fall 2021
Stanley Bak, Stony Brook University
What Can We Prove About Neural Networks?
Spring 2021
Arie Kaufman, Stony Brook University
Video Analytics and Machine Learning for Biomedical Imaging Diagnosis
Owen Rambow, Stony Brook University
Natural Language Understanding and Semantic Parsing
Haibin Ling, Stony Brook University
Computer Vision and Applications in the Deep Learning Era
Fall 2020
Alex Koulakov, University of Minnesota
Brain Evolution as a Machine Learning Algorithm
Spring 2020
Naoya Inoue, Japan Advanced Institute of Science and Technology
Do Natural Language Understanding Systems Learn to Understand or to Find Shortcuts?
Baojian Zhou , Fudan University
Learning Graph-Structured Sparse Models
Michael Ryoo, Stony Brook University
Video Architecture Search
Jeffrey Heinz, Stony Brook University
What Does Learning Mean?
Fall 2019
Jerome Zhengrong Liang, Stony Brook University
Machine Learning from Original Images to Texture Patterns: A Paradigm Shift from Non-Medical Application to Medical Diagnosis
Michael Douglas, Stony Brook University
AI in Math and Physics
Zhenhua Liu , Stony Brook University