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About Me

I am a PhD candidate and NSF GRFP Fellow in the Department of Applied Mathematics and Statistics at the Colorado School of Mines. I recently concluded my MS in Data Science here at Mines, and before that, I received my BS in Applied Mathematics from the University of California, San Diego.

My research interests lie on the intersection of deep learning and statistics, particularly in developing methods to efficiently work with big spatial data. I am especially interested in interpretable ML methods, both for AI safety and for enabling scientists to assign physical significance to their models. I am affiliated with the Mines Optimization and Deep Learning group (MODL), the Learning the Earth with Artificial Intelligence and Physics (LEAP) NSF Science & Technology Center, and NASA’s Jet Propulsion Laboratory (JPL) . I am advised by Dr. Daniel McKenzie and Dr. Doug Nychka.

When I’m not working, I like to spend my time skiing, longboarding, going to concerts, lifting, and eating really spicy food!

News

• (Feb 2025) I’ll be joining Meta as a Data Scientist Intern for the summer of 2025!
• (Oct 2024) Our paper “Normalizing Basis Functions: Approximate Stationary Models for Large Spatial Data” has been published in Stat! The article can be found here, and the revised preprint can be found on arXiv.
• (Oct 2024) The new version of our R package LatticeKrig has been published on CRAN!
• (May 2024) I have been selected to perform research and co-mentor undergraduate students as a Momentum Fellow at LEAP, an NSF center focused on combining AI and climate science!
• (April 2024) Excited to announce that I have been awarded the National Science Foundation Graduate Research Fellowship (NSF GRFP)!

Contact

Email: asikorski at mines dot edu

Office: Colorado School of Mines, Chauvenet Hall (CH) 273