PhD Student
Department of Electrical Engineering
Stanford University
Office: 472E Computing and Data Science (CoDa)
rsharma3 [at] stanford [dot] edu
Curriculum Vitae

I am a PhD student in Electrical Engineering at Stanford University advised by Professor Sara Achour and Professor Mark Horowitz. I work on building compilers and simulators for quantum computers and sparse tensor algebra. My research interests broadly include compilers, computer architecture and hardware modeling.

During my PhD, I have interned at Google in the On-Device Machine Learning (ODML) team researching different KV-Cache Pruning techniques for Infinite Context Large Language Model (LLM) inference on edge devices with the LiteRT-LM framework in Summer 2025. Previously, I interned at IonQ in Summer 2021, as a Research Intern working on building efficient near-term Error-Correction implementation of Bacon-Shor Codes.

I graduated from the Indian Institute of Technology (IIT), Delhi 2021 with a degree in Electrical Engineering. At IIT Delhi, I was fortunate to be advised by Professor Debanjan Bhowmik and worked with Professor Gert Cauwenberghs at UCSD and Niraj Jha at Princeton University on compute-in-memory hardware accelerators in Machine Learning.

News

  • Oct 2025 — Presented a talk at MICRO 20025 on my paper on Probablistic modeling of Sparse Tensor Algebra called D2T2
  • Sep 2025 — Completed my internship at Google in the On-Device Machine Learning (ODML) team working on KV Cache optimizations for LLM inference on-device
  • Sep 2025 — Our paper on probablistic modeling of Sparse Tensor Algebra was accepted to MICRO 2025
  • Jun 2025 — Started interning at Google On-Device Machine Learning (ODML) team
  • Jun 2025 — Gave a talk at PLDI 2025 on our paper SPARE
  • Feb 2025 — Performed at the opening ceremony for Stanford Viennese Ball

Publications

A Probabilistic Perspective on Tiling Sparse Tensor Algebra
Ritvik Sharma, Zi Yu Xue, Nathan Zhang, Rubens Lacouture, Fredrik Kjolstad, Sara Achour, and Mark Horowitz
IEEE/ACM International Symposium on Microarchitecture (MICRO), November 2025
pdf
Compilation of Qubit Circuits to Optimized Qutrit Circuits
Ritvik Sharma and Sara Achour
Conference on Programming Language Design and Implementation (PLDI), June 2024
pdf
Onyx: A Programmable Accelerator for Sparse Tensor Algebra
Kalhan Koul, Maxwell Strange, Jackson Melchert, Alex Carsello, Yuchen Mei, Olivia Hsu, Taeyoung Kong, Po-Han Chen, Jake Ke, Keyi Zhang, Qiaoyi Liu, Gedeon Nyengele, Akhilesh Balasingam, Jayashree Adivarahan, Ritvik Sharma, Zhouhua Xie, Christopher Torng, Joel Emer, Fredrik Kjolstad, Mark Horowitz, and Priyanka Raina
IEEE Hot Chips Symposium (Hot Chips), August 2024
Onyx: A 12nm 756 GOPS/W Coarse-Grained Reconfigurable Array for Accelerating Dense and Sparse Applications
Kalhan Koul, Maxwell Strange, Jackson Melchert, Alex Carsello, Yuchen Mei, Olivia Hsu, Taeyoung Kong, Po-Han Chen, Jake Ke, Keyi Zhang, Qiaoyi Liu, Gedeon Nyengele, Akhilesh Balasingam, Jayashree Adivarahan, Ritvik Sharma, Zhouhua Xie, Christopher Torng, Joel Emer, Fredrik Kjolstad, Mark Horowitz, and Priyanka Raina
IEEE Symposium on VLSI Technology & Circuits (VLSI), June 2024
pdf
The Sparse Abstract Machine
Olivia Hsu, Maxwell Strange, Ritvik Sharma, Jaeyeon Won, Kunle Olukotun, Joel Emer, Mark Horowitz, and Fredrik Kjolstad
International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), March 2023
pdf
APEX: A Framework for Automated Processing Element Design Space Exploration using Frequent Subgraph Analysis
Jackson Melchert, Kathleen Feng, Caleb Donovick, Ross Daly, Ritvik Sharma, Clark Barrett, Mark Horowitz, Pat Hanrahan, and Priyanka Raina
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), March 2023
pdf
CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Framework
Shikhar Tuli, Chia-Hao Li, Ritvik Sharma, and Niraj Jha
ACM Transactions on Embedded Computing Systems (TECS), April 2023
pdf
A Crossbar Array of Analog-Digital-Hybrid Volatile Memory Synapse Cells for Energy-Efficient On-Chip Learning
Janak Sharda, Ritvik Sharma, and Debanjan Bhowmik
IEEE International Symposium on Circuits and Systems (ISCAS), May 2021
A 4.2-pJ/Conv 10-b Asynchronous ADC with Hybrid Two-Tier Level-Crossing Event Coding
Raj Kubendran, Jongkil Park, Ritvik Sharma, Chul Kim, Siddharth Joshi, , and Sohmyung Ha
IEEE International Symposium on Circuits and Systems (ISCAS), May 2020

Teaching

EE 205: Signals and Systems
Spring 2020-2021, Indian Institute of Technology (IIT), Delhi
EE 205: Signals and Systems
Fall 2020-2021, Indian Institute of Technology (IIT), Delhi