Scholar
Suhas Vijaykumar
Google Scholar ID: QYoK7RIAAAAJ
Amazon Science post-doc (Amazon.com)
Citations & Impact
Citations
123
H-index
7
i10-index
5
Publications
16
Co-authors
17
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Kernel Ridge Regression Inference with Applications to Preference Data (with Rahul Singh)
- Multiple Randomization Designs: Estimation and Inference with Interference (with Lorenzo Masoero et al., to appear in Journal of the Royal Statistical Society: Series B)
- Hedonic Prices and Quality Adjusted Price Indices Powered by AI (with Pat Bajari et al., Journal of Econometrics 2025)
- Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions (with Abhineet Agarwal et al., NeurIPS 2023)
- Localization, Convexity and Star Aggregation (NeurIPS 2021)
- Can Calibration and Equal Error Rates Be Reconciled? (with Claire Lazar Reich, Proceedings of the 2nd Symposium on the Foundations of Responsible Computing, FORC 2021)
- Frank-Wolfe Meets Metric Entropy (Working Paper)
- Higher Bruhat Orders in Type B (with Seth Shelley-Abrahamson, Electronic Journal of Combinatorics 2016)
Research Experience
- Was an Amazon Science Post-doc, working on experimental design under network interference with Guido Imbens and Thomas Richardson.
Education
- Received Ph.D. in Economics and Statistics from MIT, advised by Victor Chernozhukov and Anna Mikusheva.
Background
- Currently an Assistant Professor in the Department of Economics at U.C. San Diego. Research interests include econometrics, policy analysis, high-dimensional statistics, and machine learning theory. Particularly interested in making machine learning algorithms more reliable and fair, and quantifying their uncertainty to help answer scientific questions and make high-stakes decisions.
Miscellany
- Enjoys playing the guitar and is passionate about rock climbing.
