Research Interests


  • Areas

    Machine Learning, Optimization, Human-Centered Design
  • Topics

    Algorithmic Fairness, Interpretability, Reliability, Accountability
  • Domains

    Medicine, Consumer Finance, Criminal Justice, Revenue Management

Recent Papers


Berk Ustun, Alexander Spangher, Yang Liu

FAT*
ACM Conference on Fairness, Accountability and Transparency, 2019

Berk Ustun, Yang Liu, David Parkes

ICML
International Conference on Machine Learning, 2019

Hao Wang, Berk Ustun, Flavio du Pin Calmon

ICML
International Conference on Machine Learning, 2019

Kelly Zuromski, Berk Ustun, Irving Hwang, Terence Keane, Brian Marx, Murray Stein, Robert Ursano, Ronald Kessler

Depression and Anxiety, 2019


Machine Learning Methods


Hao Wang, Berk Ustun, Flavio du Pin Calmon

ISIT
IEEE International Symposium on Information Theory, 2018

Berk Ustun, Cynthia Rudin

KDD
Knowledge Discovery and Data Mining, 2017

Berk Ustun, Cynthia Rudin

MLJ
Machine Learning, 2015

Berk Ustun, Stefano Tracà, Cynthia Rudin

AAAI Late Breaking Track, 2013

Panos Parpas, Berk Ustun, Mort Webster, Quang Kha Tran

INFORMS Journal of Computing, 2015


Machine Learning Applications


Berk Ustun, Lenard Adler, Cynthia Rudin, Stephen Faraone, Thomas Spencer, Patricia Berglund, Michael Gruber, Ronald Kessler

JAMA Psychiatry, 2017

Aaron Struck, Berk Ustun, Andres Rodriguez Ruiz, Jong Woo Lee, Suzette LaRoche, Lawrence J. Hirsch, Emily J. Gilmore, Jan Vlachy,
Hiba Arif Haider, Cynthia Rudin, M. Brandon Westover

JAMA Neurology, 2017

Jiaming Zeng, Berk Ustun, Cynthia Rudin

Journal of the Royal Statistical Society: Series A, 2016

Berk Ustun, M. Brandon Westover, Cynthia Rudin, Matt Bianchi

Journal of Clinical Sleep Medicine, 2015


Theses


Berk Ustun

PhD thesis. Massachusetts Institute of Technology, 2017

Berk Ustun

Master’s thesis. Massachusetts Institute of Technology, 2012