Jacob Feitelberg
jef2182@columbia.edu
Columbia University
Industrial Engineering and Operations Research
I am a Ph.D. candidate in Operations Research at Columbia University. I am currently being advised by Prof. Anish Agarwal and working on projects on causal inference and artificial intelligence. I completed my M.S.E. in Applied Mathematics and Statistics at Johns Hopkins University in 2023. My thesis, titled “Globally Optimal Matching of Astronomy Catalogs Using Mixed Integer Quadratically Constrained Programming and Constrained Clustering,” was advised by Prof. Amitabh Basu and Prof. Tamás Budavári.
My interests include optimal transport, causal inference, optimization, and control theory.
Publications
Preprints- Distributional Matrix Completion via Nearest Neighbors in the Wasserstein Space Jacob Feitelberg, Kyuseong Choi, Anish Agarwal, Raaz Dwivedi
- Learning Counterfactual Distributions via Kernel Nearest Neighbors Kyuseong Choi, Jacob Feitelberg, Anish Agarwal, Raaz Dwivedi
- Fast Catalog Matching for Improved Posteriors via Constrained Clustering Jacob Feitelberg, Amitabh Basu, and Tamás Budavári
- Fast Globally Optimal Catalog Matching using MIQCP Jacob Feitelberg, Amitabh Basu, and Tamás Budavári
- MNE-ICALabel: Automatically annotating ICA components with ICLabel in Python Adam Li, Jacob Feitelberg, Anand Prakash Saini, Richard Höchenberger, Mathieu Scheltienne
- Master's Thesis: Globally Optimal Matching of Astronomy Catalogs Using Mixed Integer Quadratically Constrained Programming and Constrained Clustering Advisors: Amitabh Basu and Tamás Budavári