• Alexandra Chouldechova

  • Assistant Professor of Statistics and Public Policy
  • Heinz College, Carnegie Mellon University
  • Office: Hamburg Hall 2224
  • Email: achould(at)cmu.edu
  • Phone: 412-268-4414

Education

  • Ph.D. in Statistics, Stanford University, 2014
  • B.Sc. in Mathematical Statistics, University of Toronto, 2005-2009

Research

My main interests are in applied statistics and statistical methodology, particularly in the areas of large scale multiple testing and high dimensional data analysis. I am especially interested in non-standard testing setups where the hypotheses being tested are data-driven or structured (e.g., spatially or sequentially).

More recently I have started working on problems related to fairness in machine learning. My main interest is in better understanding how to assess black-box predictors for potentially unanticipated biases that could lead to discriminatory practices. Questions that I am actively investigating include:

  • Under what conditions can disparate impact arise?
  • How can we quantitatively characterize fairness?
  • How can we use such characterizations to develop improved systems that are less likely to result in disparate impact?

Publications and Preprints:

  • Alexandra Chouldechova. Fair prediction with disparate impact: A study of bias in recidivism prediction instruments (Submitted)
    (Conference version)(Full paper)
  • Alexandra Chouldechova, Trevor Hastie. Generalized additive model selection (Submitted) (arXiv)
  • Kanji, HD., Chouldechova, A., Harvey, C., Porter, R., Gratrix M., Faulkner G., Peek G. Safety and outcomes of mobile ECMO using a bicaval dual-stage venous catheter. (Submitted)
  • Max Grazier G'Sell, Stefan Wager, Alexandra Chouldechova, Robert Tibshirani. Sequential selection procedures and false discovery rate control (JRSS B, 2016) (arXiv)
  • Alexandra Chouldechova, David Mease. Differences in search engine evaluations between query owners and non-owners. In Proceedings of the sixth ACM international conference on Web search and data mining. (WSDM 2013) (ACM DL)
  • Liu, J., Narsinh, K. H., Lan, F., Wang, L., Nguyen, P. K., Hu, S., Lee, A., Han, L., Gong, Y., Huang, M., Nag, D., Rosenberg, J., Chouldechova, A., Robbins, R. C., Wu, J. C. Early stem cell engraftment predicts late cardiac functional recovery: preclinical insights from molecular imaging. Circulation: Cardiovascular Imaging, 5(4), 481-490. (2012) (PubMed)

In preparation:

  • Diwakar, IB., Chouldechova, A., Clements, MA., & Padman, R. On Extracting Features from Asynchronous Multivariate Data Streams
  • Clusterwise False Discovery Rate Control for Spatial Data via the Poisson Clumping Heuristic
  • False Discovery Rate and Exceedance Control Methods for Region of Interest Detection

Thesis:

  • False Discovery Rate Control for Spatial Data, Stanford 2014.(pdf)

Teaching

Here's a list of the courses I'm currently teaching, along with links to the course webpages.