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Artificial Intelligence Seminars

Danielle Belgrave | AI Seminar

Danielle Belgrave, Machine Learning ResearcherHealth Intelligence Group, Microsoft Research

4:00pm – 5:30pm

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Jitendra Malik (Title: TBD)

Jitendra Malik, Arthur J. Chick ProfessorDept. of Electrical Engg & Computer Science, UC Berkeley

4:00pm – 5:30pm

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Past Seminars

Semantic Scholar, NLP, and the Fight Against COVID-19

Oren Etzioni, Chief Executive Officer at Allen Institute for AI

4:00pm – 5:30pm

Learning sight from sound

Andrew Owens, Assistant Professor in Electrical and Computer EngineeringUniversity of Michigan

4:00pm – 5:15pm in Remote/Virtual

AI Seminar | Dissertation Defense

Efficient Belief Propagation for Perception and Manipulation in Clutter

Karthik Desingh

3:00pm – 5:00pm

Distortion-based Analysis of Voting: Limited Communication, and an Analysis Framework based on LP Duality and Flows

David Kempe , Professor, Computer ScienceUniversity of Southern California

4:00pm – 5:15pm in 3725 Beyster Building

NumPy: A look at the past, present, and future of array computation

Ross Barnowski, Postdoctoral Scholar

1:30pm – 3:00pm in 3725 Beyster Building

Language Grounding in Situated Communication

Joyce Chai, Professor, Electrical Engineering and Computer ScienceUniversity of Michigan

4:00pm – 5:15pm in 3725 Beyster Building

Software Engineering Intelligence

Marouane Kessentini, Associate Professor, Computer and Information Science University of Michigan – Dearborn

4:00pm – 5:15pm in 3725 Beyster Building

Applications of AI for Accessibility

Robin Brewer, Assistant Professor – School of Information and Computer Science and Engineering University of Michigan

4:00pm – 5:15pm in 3725 Beyster Building

From Recognition to Reasoning

Justin Johnson, Assistant ProfessorComputer Science and Engineering, University of Michigan

4:00pm – 5:15pm in 3725 Beyster Building

Joint Models for Social, Behavioral and Textual Information

Dan Goldwasser, Assistant Professor in Computer SciencePurdue University

4:00pm – 5:15pm in 3725 Beyster Building

Toward Human-Like AI: Cognitive Architecture, Common Model of Cognition & Interactive Task Learning

John E. Laird, John L. Tishman Professor of EngineeringUniversity of Michigan

4:00pm – 5:15pm in 3725 Beyster Building

Friends Don’t Let Friends Deploy Black-Box Models: The Importance of Intelligibility in Machine Learning for HealthCare

Rich Caruana, Senior Principal ResearcherMicrosoft Research

4:00pm – 5:15pm in 3725 Beyster Building

Computational exercises of creative language

Carlo Strapparava, Senior ResearcherFondazione Bruno Kessler – Istituto per la ricerca scientifica e Tecnologica

4:00pm – 5:15pm in 3725 Beyster Building

Game Playing Meets Game Theory: Strategic Learning from Simulated Play

Michael P. Wellman, ProfessorComputer Science and Engineering, University of Michigan

4:00pm – 5:15pm in 3725 Beyster Building

Efficient Algorithms for Learning Combinatorial Structures from Limited Data

Asish Ghoshal, PhD graduatePurdue University

Why Do Neural Networks Learn?

Behnam Neyshabur, PostdocNew York University

Learning Hierarchical Control Programs

Roy Fox, PostdocUniversity of California, Berkeley

Bridging Data, Design, and Domain Knowledge to Build Human-Centered Systems that Support Wellbeing

Elizabeth Murnane, PostdocStanford University

The Role of Context in Natural Language Processing

Soujanya Poria, PostdocSchool of Computer Science & Engineering, NTU, Singapore

Towards Human-Level Recognition via Contextual, Dynamic, and Predictive Representations

Fisher Yu, PostdocUniversity of California, Berkeley

Efficient Training and Inference in Deep Learning

Ji Liu , Assistant ProfessorUniversity of Rochester

Understanding and Improving Deep Neural Networks

Jeff Clune, Associate Professor and Senior Research ManagerUniversity of Wyoming and Uber AI Labs

Towards Generalization and Efficiency in Reinforcement Learning

Wen Sun, Ph.D. CandidateCarnegie Mellon University

Computer Vision Seminar

Rethinking the relationship between data and robotics

Lerrel Pinto, PhD CandidateCarnegie Mellon University

Computer Vision Seminar

Image Synthesis for Self-Supervised Visual Representation Learning

Richard Zhang, Research ScientistAdobe Research

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