Anant Raj

Hello 

Marie-Curie Fellow
SIERRA Project Team (Inria),
Ecole Normale Supérieure, PSL Research University.


Coordinated Science Laboratory (CSL),
University of Illinois at Urbana-Champaign (UIUC).

Email: anant dot raj at inria

Short Bio

I will be joining the Indian Institute of Science (IISc) as an Assistant Professor in the Department of Computer Science and Automation (CSA) staring Fall 2024. I am currently a Marie-Curie Fellow, jointly hosted by Prof. Francis Bach at SIERRA Project Team (Inria) and Prof. Maxim Raginsky at Coordinated Science Laboratory (CSL), UIUC. Before that, I completed my PhD in Machine Learning at Max-Planck Institute for Intelligent Systems in the Empirical Inference Department under the supervision of Prof. Bernhard Schoelkopf. I received my B.Tech-M.Tech dual degree in Electrical Engineering from IIT Kanpur where my research was advised by Prof. Rajesh M Hegde, Prof. Vinay Namboodiri, Prof. Amitabha Mukerjee and Prof. Tinne Tuytelaars (External Master's Thesis Advisor). My research interest is in understanding problems in general machine learning theory and applications. More specifically, I am interested in optimization theory, kernel methods and theoretical foundation of machine learning. I have also a vivid interest in understanding the resource efficient learning such as active learning, coresets and distributed inference. On the application side, I am interested in application of machine learning methods in healthcare domain.

Recent News

  • Jun 2024: I am joining Indian Institute of Science (IISc) as an Assistant Professor in the Department of Computer Science and Automation (CSA) in Fall 2024.

  • May 2024: Our Paper on practical policy gradient got accepted at Reinforcement Learning Conference (RLC), 2024. Check it out.

  • May 2024: Our paper on inverse optimization got accepted at ICML 2024. Check it out.

  • May 2024: I am back at SIERRA Research Team at Inria, Paris.

  • Apr 2024: Attended Heavy-Tails in Machine Learning Research Program at Alan Turing Institute, London.

  • Feb 2024: Gave a talk at KAUST Rising Stars in AI Symposium 2024 , hosted by the AI Initiative at KAUST.

  • Jan 2024: Our paper on Learning with Abstention got accepted at TMLR 2024. Check it out.

  • Nov 2023: Gave a talk at IMS Young Mathematical Scientist Forum — Statistics and Data Science on stability of heavy-tailed SGD.

  • Sep 2023: Our papers on Wasserstein stability bound for SGD and sampling using PSD model have been accepted to Neurips 2023.

  • Jul 2023: Presented our work on stability bound for heavy-tailed SGD at ICML 2023 in Hawaii, USA.