People

Saurav Muralidharan

Saurav Muralidharan is a Senior Research Scientist in the Deep Learning Efficiency Research (DLER) team. He specializes in LLM efficiency and performance optimization and has worked on model compression (pruning, distillation, low-rank factorization), SLMs, elastic and mixture-of-expert (MoE) networks. Please visit sauravm.com for more details on his research.

Research Area(s)
Artificial Intelligence and Machine Learning
Generative AI
High Performance Computing
Main Field of Interest
Artificial Intelligence and Machine Learning

Publications

2025

Minitron-SSM: Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning
Ali Taghibakhshi, Sharath Turuvekere Sreenivas, Saurav Muralidharan, Marcin Chochowski, Yashaswi Karnati, Raviraj Joshi, Ameya Sunil Mahabaleshwarkar, Zijia Chen, Yoshi Suhara, Oluwatobi Olabiyi, Daniel Korzekwa, Mostofa Patwary, Mohammad Shoeybi, Jan Kautz, Bryan Catanzaro, Ashwath Aithal, Nima Tajbakhsh, Pavlo Molchanov
NeurIPS 2025

2024

LLM Pruning and Distillation in Practice: The Minitron Approach
Sharath Turuvekere Sreenivas, Saurav Muralidharan, Raviraj Joshi, Marcin Chochowski, Mostofa Patwary, Mohammad Shoeybi, Bryan Catanzaro, Jan Kautz, Pavlo Molchanov

2020

A Programmable Approach to Neural Network Compression
Vinu Joseph, Ganesh L. Gopalakrishnan, Saurav Muralidharan, Michael Garland, Animesh Garg
IEEE Micro: Special Issue on Machine Learning for Systems