Agniva Chowdhury

I am a Postdocroral Research Associate in the Computer Science and Mathermatics Division of Oak Ridge National Laboratory. Recently, I obtained my PhD in Statistics from Purdue University , advised by Prof. Petros Drineas and Prof. Hao Zhang.

My research revolves around developing fast and efficient randomized algorithms for various large-scale statistical as well as more general linear algebraic problems. Using the tools from randomized matrix algebra, my goal is to come up with provably accurate, fast and approximate solutions to those problems which are computationally very hard or expensive. I am also interested in various aspects of statistical machine learning including dimensionality reduction and feature selection in high dimensional data.

In terms of other academic qualifications and relevant experience, I completed my M.Sc. in Statistics from Indian Institute of Technology Kanpur in 2011. Prior to that, I obtained my B.Sc. in Statistics from the University of Calcutta in 2009. Before joining Purdue as a PhD student, I spent a few years in the data science and analytics industry. For further information, please have a look at my CV.

• 02/2024: Paper accepted in CVPR 2024.


• 12/2023: Paper accepted in AAAI 2024.


• 09/2022: Paper accepted in JMLR.


• 05/2022: Paper accepted in ICML.


• 03/2022: Paper accepted in RECOMB.


• 01/2022: Joined ORNL as a Postdoc.


• 11/2021: Defended my PhD.


• 09/2020: Paper accepted in NeurIPS.


• 09/2019: Attended workshop on Randomized Numerical Linear Algebra, Statistics, and Optimization
  organized by DIMACS at the Rutgers University, New Jersey, USA.


• 07/2019: Presented our paper on randomized discrimanint analysis at UAI 2019 in Tel Aviv, Israel.


• 05/2019: Paper accepted in UAI.


• 04/2019: Attended workshop on Algorithmic, Mathematical, and Statistical Foundations of Data Science and Applications at Purdue University, West Lafayette, USA.