Welcome to my research page. I am a PhD student in mathematics at Purdue University. I was very fortunate to previously have had mentors of Xiaohui Chen, Paul Atzberger, and Chris Anderson.
I study pure and applied mathematical foundations of artificial intelligence. My research interests can best be categorized as scientific machine learning, physics-informed learning, geometric deep learning, and deep learning for differential equations (ODEs, PDEs, SDEs), although my research interests are broad and intersect other areas of mathematics but in ML.
My research has been highlighted by attempting to bridge familiar machine learning with that which is more classical. Why should we attempt to understand, observe, and quantify normal data structures without considering the tools from higher mathematics? I find mathematics is an underrated perspective towards artificial intelligence.
Please feel free to contact me. I strongly encourage you to reach out if you have questions, comments, or want to chat about mathematics or otherwise. Do not hesitate to add me on LinkedIn or shoot me an email.
At UIUC, I was affiliated with the Grainger College of Engineering through DIGIMAT, a research group focused on the interface of data science, statistical physics, and materials science. DIGIMAT is co-hosted by the National Center for Supercomputing Applications and Materials Research Lab.
Previously, I was a member of Atzberger Research Group, a group focused on statistical physics, numerical analysis, scientific computation, and machine learning.
One can reach me by email. My university email is agracyk at purdue dot edu, but my permanent email is andrewgracyk at gmail dot com. Either works great.
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The Isle of Eigg in Laig Bay, Scotland
andrewgracyk.com 