Sreejith Sreekumar

Sreejith Sreekumar

CNRS Researcher · Information Theory · Machine Learning · Quantum Information Science

I am a CNRS researcher at the Laboratoire des Signaux et Systèmes (L2S), CentraleSupélec, University Paris-Saclay. My research focuses on information theory, machine learning, mathematical statistics, and quantum information science.

About

I am interested in theoretical and algorithmic foundations for communication, inference, learning systems, privacy-aware algorithms, and quantum information processing.

Education

Ph.D. (Electrical and Electronic Engineering)
Imperial College London, 2019


Research Interests

Information Theory Machine Learning Quantum Information Statistical Inference Privacy & Security Mathematical Statistics

Recent News

May 2026

Paper accepted in Quantum

Our work on Performance Guarantees for Quantum Neural Estimation of Entropies has been accepted for publication in Quantum.

March 2026

Paper accepted at ISIT 2026

Our work on One-shot Interference Channel Simulation accepted at ISIT 2026 to be held in Guangzhou, China.

Feb 2026

New preprint on arXiv

Our work on Quantum Maximum Likelihood Prediction via Hilbert Space Embeddings is available at arxiv.org/abs/2602.18364

Professional Experience

Chargé de Recherche, CNRS

2025 – Present · CentraleSupélec, University Paris-Saclay

Postdoctoral Research Associate

2023 – 2025 · Institute for Quantum Information., RWTH Aachen University

Postdoctoral Research Associate

2020 – 2023 · Cornell University

Selected Recent Publications

Performance Guarantees for Quantum Neural Estimation of Entropies

S. Sreekumar, Z. Goldfeld, and M. Wilde

Quantum, 2026

One-shot Multiple Access Channel Simulation

A. Nema, S. Sreekumar and M. Berta

IEEE Transactions on Information Theory, 2026

Distributed Quantum Hypothesis Testing under Zero-rate Communication Constraints

S. Sreekumar, C. Hirche, H-C. Cheng, and M. Berta

Annales Henri Poincaré, 2025

Locally-Measured Rényi Divergences

T. Rippchen, S. Sreekumar and M. Berta

IEEE Transactions on Information Theory, 2025

Limit Distribution Theory for Quantum Divergences

S. Sreekumar and M. Berta

IEEE Transactions on Information Theory, 2025

Limit Distribution Theory for f-Divergences

S. Sreekumar, Z. Goldfeld and K. Kato

IEEE Transactions on Information Theory, 2024

Neural Estimation of Statistical Divergences

S. Sreekumar and Z. Goldfeld

Journal of Machine Learning Research, 2022

Current Ph.D. Students

Letao Wang (co-supervised with Prof. Abdel Lisser and Prof. Zeno Toffano)

Junle Zhong (co-supervised with Prof. Mohamad Assaad)

Contact


Email: sreejith.sreekumar@centralesupelec.fr


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