Welcome!

I am a Postdoctoral Researcher in Econometrics and Statistics at the Booth School of Business, University of Chicago, hosted by Prof. Nabarun Deb. I received my Ph.D. in Statistics from the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame, advised by Prof. Lizhen Lin and Prof. Daren Wang.

Before my Ph.D., I completed a Five-year Integrated M.Sc. in Mathematics at Visva Bharati, advised by Prof. Swapan Kumar Pandit. During my final year, I spent a year as a visiting student at the Chennai Mathematical Institute, where I completed my master’s dissertation under Prof. Issan Patri.

For details on my research, teaching, and publications, see my CV (pdf).

I was born and raised in Bihar, India.

Research

My research interests include:

• Statistical foundations of deep generative models
• Nonparametric statistics in high-dimensions
• Change point detection and inference
• Optimal Transport
• Tensor estimation

Publications

Shivam Kumar, Yun Yang, Lizhen Lin. A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models. arxiv, ICML (2025).

Working Papers

Shivam Kumar, Haotian Xu, Carlos-Misael Madrid-Padilla, Yuehaw Khoo, Oscar-Hernan Madrid-Padilla, Daren Wang. Bias-variance Tradeoff in Tensor Estimation. arxiv, Under Review. (2025)

Shivam Kumar, Haotian Xu, Haeran Cho, Daren Wang. Estimation and Inference for Change Points in Functional Regression Time Series. arxiv Under Review. (2024)

Work in Progress

Shivam Kumar, Yixin Wang, Lizhen Lin. Statistical Foundation of Matching Flow Based Generative Models. In Progress. (2025+)