Other Seminars

Explainability and Interpretability through Interaction

Pursuing Health and Inclusion Through Sociotechnical Systems

Bridging Continuous and Discrete Optimization through the Lens of Approximation

Objectively Measure Developers’ Cognitive Activities: Code, Biases, and Brains

Mobile Health Approaches to Precision Medicine

Machine Learning and Causality: Building Efficient, Reliable Models for Decision-Making

Collaboration as a Lens for Inclusive Technical Innovation

Realizing the Promise of Autonomy

Automotive Cloud Computing

Danielle Belgrave | ML for Personalized Mental Healthcare

Cracking the diversity code: Understanding computing pathways of those least represented in order to foster their representation

Understanding and Generating Natural Language of Complex Discourse

Software-Hardware Systems for the Internet of Things

Logic Solvers and Machine Learning: The Next Frontier

Building Multi-Language Tools

Using deep-learning methods to predict cancer patient survival

MIDAS 2019 Annual Symposium – Embracing the Challenge: Data Science for the Next Ten Years

MIDAS 2019 Annual Symposium – Embracing the Challenge: Data Science for the Next Ten Years

MIDAS 2019 Annual Symposium – Embracing the Challenge: Data Science for the Next Ten Years

Towards building Internet of Vehicles

Algorithms for Coping with Intractability and Uncertainty

Michigan AI Symposium – “AI for Society”

EECS Homecoming Luncheon

Detection structure and patterns in big biomedical data

Coding Theory in the Big Data Era