Data Science Presentations

This page includes links to presentations given in the weekly CSE DSI Machine Learning Seminar as well data science-related workshops organized by researchers at the University of Minnesota and keynote or invited addresses by CSE DSI leadership.

CSE DSI Leadership

• Knowledge-Guided Machine Learning: A New Framework for Accelerating Scientific Discovery and Addressing Global Climate Challenges. Address by CSE DSI Director Vipin Kumar at the 8th International Conference on Data Science and Management of Data at IIT Jodhpur, December 18-21, 2024
• Knowledge-Guided Machine Learning: A New Framework for Accelerating Scientific Discovery and Addressing Global Climate Challenges. Keynote address by CSE DSI Director Vipin Kumar at the 2024 NSF HDR (Harnessing the Data Revolution) Ecosystem Conference held at the University of Illinois Urbana-Champaign (September 9-12, 2024). The talk ends at 51:48 and is followed by a question and answer session.
• KGML-Ag: A New Framework for Agricultural Decision Making. Given by CSE DSI Director Vipin Kumar at the AI for Agriculture Summit 2024 held at the National Academy of Sciences in Washington, D.C., in July 2024.

CSE DSI GenAI Day (May 20, 2025)

Several of the talks from the morning session of GenAI Day are posted on the CSE DSI YouTube Channel on the GenAI Day 2025 Playlist.

CSE DSI Machine Learning Seminar

Recordings of past presentations can be viewed on the CSE DSI YouTube channel.

Knowledge Guided Machine Learning: A Framework for Scientific Discovery (KGML2024)

See the KGML2024 playlist on the CSE DSI YouTube channel to view recordings of the talks and panel discussions at the KGML2024 workshop. Visit the workshop website to learn more about the speakers and get links to the speakers' slides.

Knowledge Guided Machine Learning: A Framework for Scientific Discovery (2020-2021)

Recordings of 87 presentations can be viewed on the KGML YouTube channel. Visit the project website.

This workshop is part of a 2-year conceptualization project funded by the NSF's Harnessing the Data Revolution (HDR) program involving researchers from the University of Minnesota, University of Wisconsin, Penn State, Colorado State University, and the University of Virginia. This project aims to develop a framework that uses the unique capability of data science models to automatically learn patterns and models from data, without ignoring the treasure of accumulated scientific knowledge. Specifically, the project builds the foundations of knowledge-guided machine learning (KGML) by exploring several ways of bringing scientific knowledge and machine learning models together using pilot applications from four domains: aquatic ecodynamics, climate and weather, hydrology, and translational biology.

Funding for this project was provided by the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea. The project team was led by the University of Minnesota, including faculty and researchers from the College of Science and Engineering and the College of Food, Agricultural and Natural Resource Sciences, and also included researchers from the University of Virginia, the University of Wisconsin-Madison, Colorado State University, Pennsylvania State University, and the United States Geological Survey. 

Women in AI and Data Science Conference (WiADS) 2024

Recordings from the November 2024 conference are available on the university-wide DSI YouTube channel. VIisit the conference website. The conference was organized by the University of Minnesota Data Science Initiative with support from MinneAnalytics.