Events

Upcoming Events

Frontiers of GenAI & Science

The fourth workshop in our Minnesota AI for Science Series, Frontiers of GenAI & Science, will be held at the McNamara Alumni Center on August 4–5, 2026.

Past Events

CSE DSI Machine Learning Seminar with Jiajin Li (Business, UBC)

Details coming soon.

CSE DSI Machine Learning Seminar with Stephan Rabanser (Princeton)

Dr. Stephan Rabanser (Princeton) will give a talk entitled Towards a Science of AI Agent Reliability.

CSE DSI Machine Learning Seminar with Jia Liu (SEAS, Harvard)

Prof. Jia Liu (Harvard) will give a talk entitled Agentic and Physical AI for Scientific Discovery and Intelligent Manufacturing.

CSE DSI Machine Learning Seminar with Geir Eirik Dullerud (ECE, UMN)

Professor Geir E. Dullerud will speak on Learning and System Identification for Safety and
Control Design in Dynamical Processes.

CSE DSI Machine Learning Seminar with Aditi S Krishnapriyan (Chemistry, UC Berkeley)

Dr. Aditi S Krishnapriyan (Chemistry, UC Berkeley) will speak on Learning physical dynamics with generative machine learning.

CSE DSI Machine Learning Seminar with Jiawei (Joe) Zhou (CS, Stony Brook)

Dr. Jiawei (Joe) Zhou will speak on "The Future of NLP (→ AI) Systems: Efficiency, Multimodality, and Trustworthiness."

CSE DSI Machine Learning Seminar with Ismail Alkhouri (LANL & UMich)

Dr. Ismail Alkhouri (Los Alamos National Laboratory and the University of Michigan) will give a talk entitled Differentiable Combinatorial Optimization at Scale.

CSE DSI Machine Learning Seminar with Geoff Pleiss (Stats, UBC)

Dr. Geoff Pleiss (Statistics, UBC) will give a talk entitled Ensembles in the Age of Overparameterization: Promises and Pathologies.

CSE DSI Hosts Workshop on GenAI for Science & Engineering

The CSE Data Science Initiative (CSE DSI) is holding a full-day Generative AI for Science & Engineering (GenAI4Sc) workshop on Friday, February 13, 2026.

CSE DSI Machine Learning Seminar with Aaron Molstad (Statistics, UMN)

Prof. Aaron Molstad (UMN, Statistics) will speak on A direct approach to tree-guided feature aggregation for high-dimensional regression.