Ananya Uppal

Postdoctoral Researcher
Dr. Ananya Uppal is currently a Postdoctoral Researcher at the Institute for Foundations of Machine Learning (IFML) at the University of Texas at Austin. Her main research area is statistical machine learning and theoretically understanding machine learning algorithms. She received her Ph.D. from Carnegie Mellon University and her bachelors degree from the University of Illinois at Urbana-Champaign.


Research Interests: 
  • Statistical machine learning
  • Theoretically understanding machine learning algorithms

Research Labs & Affiliations:

Institute for the Foundations of Machine Learning (IFML)

Select Publications

A Uppal, S Singh, B Poczos. 2020. Robust Density Estimation under Besov IPMs.
A Uppal, S Singh, B Póczos. 2019. Nonparametric Density Estimation and Convergence of GANs under Besov IPM Losses.
AL Turner, A Uppal, P Xu. 2015. Spacing Distribution of a Bernoulli Sampled Sequence.
AJ Hildebrand, L Kong, A Turner, A Uppal. 2012. IGL Project Report Applications of n-dimensional Integrals: Random Points, Broken Sticks and Intersecting Cylinders.
K Kong, L Lkhamsuren, A Turner, A Uppal, AJ Hildebrand. Random Points, Broken Sticks, and Triangles.

Awards & Honors

2019 - NeurIPS 2019 Honorable Mention for Outstanding Paper Award
2015 - Most Outstanding Major Award in Mathematics and Computer Science