Harshvardhan Mestha
I graduated from BITS Goa, with a bachelors in Electronics and Instrumentation. I will be joining NYU Courant as an M.S. student in Computer Science starting Fall 2027.
I have been working with Dr. Anand Subramoney's group since 2024, on the topic of State Space Models for in-context learning. In 2025, I spent an amazing few months at TU Dresden in Germany, as a SSMP scholar, working on efficient State Space Model based LLMs for Neuromorphic hardware, under the guidance of Prof. David Kappel and Dr. Subramoney, and I currently continue this work. Previously, I also worked as a researcher at APPCAIR, under the guidance of Prof. Ashwin Srinivasan and Dr. Tanmay Verlekar, on explainable agentic protocols and AI for Healthcare.
I also love all things related to sci-fi, space, cars, and aviation. I also draw and you can find some of my art here.
I have been working with Dr. Anand Subramoney's group since 2024, on the topic of State Space Models for in-context learning. In 2025, I spent an amazing few months at TU Dresden in Germany, as a SSMP scholar, working on efficient State Space Model based LLMs for Neuromorphic hardware, under the guidance of Prof. David Kappel and Dr. Subramoney, and I currently continue this work. Previously, I also worked as a researcher at APPCAIR, under the guidance of Prof. Ashwin Srinivasan and Dr. Tanmay Verlekar, on explainable agentic protocols and AI for Healthcare.
I also love all things related to sci-fi, space, cars, and aviation. I also draw and you can find some of my art here.
Publications
BlockMamba: Efficient Scalable Structured Sparsity for Mamba
Harshvardhan Mestha, Khaleelulla Khan Nazeer, David Kappel, Anand Subramoney
Accepted at the 2nd Workshop on World Models @ ICLR'26
lrnnx: A library for Linear RNNs
Harshvardhan Mestha*, et al.
Accepted at the Student Research Workshop @ EACL'26
Multi-Turn Human-LLM Interaction Through the Lens of a Two-Way Intelligibility Protocol
Harshvardhan Mestha, Karan Bania, Shreyas V, Sidong Liu, Ashwin Srinivasan.
Accepted at Multi-turn Interactions in LLMs @ NeurIPS'25
Learning in the Recurrent State: Gradient Descent with Linear Recurrent Networks
Yudou Tian, Neeraj Mohan Sushma, Harshvardhan Mestha, Nicolo Colombo, David Kappel, Anand Subramoney
Under review at NeurIPS 2026
Exploring the Missing Medical Context in Generated Radiology Reports
Karan Bania*, Harshvardhan Mestha*, Tanmay Tulsidas Verlekar
Accepted at SLM4Health @ AIME’25
CountCLIP - [Re] Teaching CLIP to Count to Ten
Harshvardhan Mestha, Tejas Agrawal, Karan Bania, Yash Bhisikar