Seminars

The AI Institute holds a monthly seminar series with a lively mix of local and external speakers. Upcoming events are always posted on our Institute calendar.

Other outstanding speakers of interest come as part of the Department of Computer Science Shutterstock Distinguished Lecture Series (DLS). Recent visitors include Daniel Rubenstein, Princeton University; Ellen Zegura, Georgia Tech; Brian Kernighan, Princeton University; and Patrick McDaniel, Pennsylvania State University. 

Spring 2022

Tony Zador,

The Genomic Bottleneck Algorithm for Faster Learning and Better Generalization

Fall 2021

Chao Chen,

Detection of Trojan Attacks on Deep Neural Networks - A Topological Perspective

Stanley Bak,

What Can We Prove About Neural Networks?

Spring 2021

Arie Kaufman,

Video Analytics and Machine Learning for Biomedical Imaging Diagnosis

Owen Rambow,

Natural Language Understanding and Semantic Parsing

Haibin Ling,

Computer Vision and Applications in the Deep Learning Era

Fall 2020

Alex Koulakov,

Brain Evolution as a Machine Learning Algorithm

David Gu,

A Geometric Understanding of Deep Learning

Yifan Sun,

Optimization and machine learning

Spring 2020

Naoya Inoue,

Do Natural Language Understanding Systems Learn to Understand or to Find Shortcuts?

Baojian Zhou ,

Learning Graph-Structured Sparse Models

Michael Ryoo,

Video Architecture Search

Jeffrey Heinz,

What Does Learning Mean?

Fall 2019

Jerome Zhengrong Liang,

Machine Learning from Original Images to Texture Patterns: A Paradigm Shift from Non-Medical Application to Medical Diagnosis

Michael Douglas,

AI in Math and Physics

Zhenhua Liu ,

Online Optimization and Its Applications