I'm Saptarshi Chakraborty (সপ্তর্ষি চক্রবর্তী), a Ph.D. student in Statistics at the Department of Statistics, University of California, Berkeley. Prior to joining Berkeley, I completed my Master's (M.Stat) and Bachelor's (B. Stat (Hons.)) degrees in Statistics from Indian Statistical Institute, Kolkata, India. Previously, I was a visiting scholar at the Department of Statistical Science, Duke University, NC, USA. I was also a summer exchange student at the Big Data Summer Institute, University of Michigan, USA in 2018, where I worked on the application of Machine Learning algorithms on medical data.


Selected Publications:

(2024) Saptarshi Chakraborty and Peter L. Bartlett. A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data. International Conference on Learning Representations (ICLR'24).
(2021) Saptarshi Chakraborty and Swagatam Das, 2021. Detecting Meaningful Clusters from High-dimensional Data: A Strongly Consistent Sparse Center-based Clustering Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
(2021) Saptarshi Chakraborty, Debolina Paul and Swagatam Das. 2021. Automated Clustering of High-dimensional Data with a Feature Weighted Mean-shift Algorithm. In 35th AAAI Conference on Artificial Intelligence, a virtual conference, Feb 2-9, 2021.
(2020) Saptarshi Chakraborty, Debolina Paul, Swagatam Das and Jason Xu. 2020. Entropy Weighted Power k-Means Clustering. In 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 691-701. PMLR, 2020.