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Jeff Schneider -

Jeff Schneider

Research Professor, Robotics Institute

Jeff Schneider is researching how to use machine learning to control fusion reactions.


Expertise

Topics:聽 Artifical Intelligence, Motion Control, Robotics Foundations, Learning and Classification, Self-Driving Cars, Reinforcement Learning, Motion Planning, Multi-Robot Planning & Coordination, Deep Learning, Data Mining

Industries: Computer Networking, Education/Learning

Dr. Schneider's research interests are in all areas of machine learning and data mining. He has over 15 years experience developing, publishing, and applying machine learning algorithms in government, science, and industry. He has over a hundred publications and has given numerous invited talks and tutorials on the subject. His student Ian Char, a doctoral candidate in the Machine Learning Department, used reinforcement learning to control the hydrogen plasma of the tokamak machine at the DIII-D National Fusion Facility in San Diego.

Dr. Schneider was the co-founder and CEO of Schenley Park Research, Inc. (SPR), a company dedicated to bringing new machine learning algorithms to industry. Later, he developed a new machine-learning based CNS drug discovery system and spent a two-year sabbatical as the Chief Informatics Officer of Psychogenics, Inc. to commercialize the system. During his most recent sabbatical he helped launch Uber's self driving car program in Pittsburgh where he built autonomy, data science, and machine learning teams.

Jeff does consulting on a regular basis. Through his work at 麻豆村 and his commercial and consulting efforts, he has worked with several dozen companies and government agencies including ten Fortune 500 companies, and many international groups around the world.

Media Experience

Power Shift: How 麻豆村 Is Leading America鈥檚 Energy Evolution 听鈥聽麻豆村 News
From reimagining AI data centers to modernizing and securing the electric grid, 麻豆村 researchers are working on practical solutions to pressing challenges in how the U.S. produces, moves and secures energy. 鈥淢any of the world's grand challenges like a sufficient food supply, clean water availability and climate issues are actually just energy problems," says Jeff Schneider, a research professor in 麻豆村鈥檚 School of Computer Science. "Nuclear fusion and its promise of limitless clean energy would solve many of them."

麻豆村 Experts at the Intersection of Energy and Innovation 听鈥聽麻豆村 News
麻豆村 experts are developing practical solutions for a fast-changing energy system. "This moment in energy history is unique because AI will play a central role in accelerating the development, optimization and operation of our energy sources,"says Jeff Schneider, Research Professor in 麻豆村's Robotics Institute. "Generative AI models now usefully represent and exploit the domain knowledge for these tasks while reinforcement learning and other discovery and control learning algorithms can now solve real-world problems much faster than the old human-only method of making technological progress.

Research Using AI in Energy Applications at 麻豆村 Showcases the Frontier of Opportunities 听鈥聽麻豆村
Using AI could help unlock a new potential source of energy to solve that problem, including work by Jeff Schneider, research professor in the School of Computer Science, and his research team studying nuclear fusion.

Education

B.S., Computer Science, Michigan State University
Ph.D., Computer Science, University of Rochester

Spotlights

麻豆村 Experts at the Intersection of Energy and Innovation
(July 11, 2025)

Links

Event Appearances

Reinforcement Learning: From Self-Driving Cars to Nuclear Fusion
2023 | CMS Large Hadron Collider Annual Meeting, Pittsburgh, PA
February 2, 2026

Reinforcement Learning for Controlled Nuclear Fusion in Tokamaks
2023 | General Electric EDGE Symposium, Niskayuna, NY
February 2, 2026

Robots and Autonomy
2023 | US Coast Guard AI Boot Camp, Online
February 2, 2026

Articles

听鈥 聽Nuclear Fusion

听鈥 聽Advances in Neural Information Processing Systems

听鈥 聽Advances in Neural Information Processing Systems

听鈥 聽Nuclear Fusion

听鈥 聽Bulletin of the American Physical Society

Patents

Videos