Research
Publications
Gombolay, M., Bair, A., Huang, C., & Shah, J. (2017).
Computational design of mixed-initiative human-robot teaming that
considers human factors: situational awareness, workload, and workflow
preferences. The International Journal of Robotics Research, 36(57),
597-617.
Rice, L., Bair, A., Zhang, H., & Kolter, Z. (2021).
Robustness between the worst and average case. NeurIPS 2021.
Preprints
Bair, A. , Yin, H., Shen, M., Molchanov, P., Alvarez, J. (2023).
Adaptive Sharpness-Aware Pruning for Robust Sparse Networks. Under review.
Feng, Z., Bair, A. , Kolter, Z. (2023).
Text Descriptions are Compressive and Invariant Representations for Visual Learning. Under review.
Sun, M., Liu, Z., Bair, A. , Kolter, Z. (2023).
A Simple and Effective Pruning Approach for Large Language Models.
Presentations and Workshops
Bair, A., McDermott, M., Wang, J., Zhao, W., Sheridan, S.,
Szolovits, P., Kohane, I., Haggarty, S., Perlis, R.
(2018, December 3). Improved Modeling and Analysis of Gene
Expression. Poster presented at Women in Machine Learning (WiML)
Workshop, Montr‌éal, Canada.
Bair, A., McDermott, M., Wang, J., Zhao, W., Sheridan, S.,
Szolovits, P., Kohane, I., Haggarty, S., Perlis, R.
(2019, March 4). Using Machine Learning to Improve Drug Development.
Poster presented at Women in Data Science (WiDS)
Cambridge Conference, Cambridge, MA.