SARCS Lab

Sustainable, Advanced and Robust Computing Systems

Computing at the Edge of What's Possible

“Research is to see what everybody else has seen, and to think what nobody else has thought.”

Albert Szent-Györgyi

About the laboratory

The SARCS Lab is dedicated to advancing the frontiers of computer architecture, hardware-software co-design, and emerging computing paradigms like photonics, quantum computing and in-memory computing. Our research spans RISC-V architectures, hardware accelerators, compute-in-memory, and AI systems, with a focus on developing efficient, scalable, and sustainable computing solutions for next-generation applications.

Meet the team Research areas

Recent publications

Full archive

arXiv 2026

Semantic-Guided 3D Gaussian Splatting for Transient Object Removal

A Prabakaran, Priyesh Shukla

arXiv preprint arXiv:2602.15516

arXiv Scholar

arXiv 2026

Bidirectional Quantum Processor Interfacing by a 4-Kelvin Analog Signal Chain for Superconducting Qubit Control and Quantum State Readout

D RV, L Kanawat, Priyesh Shukla

arXiv preprint arXiv:2602.14165

arXiv Scholar

arXiv 2026

TernaryLM: Memory-Efficient Language Modeling via Native 1-Bit Quantization with Adaptive Layer-wise Scaling

N Nargund, Priyesh Shukla

arXiv preprint arXiv:2602.07374

arXiv Scholar

VTS 2025

MOSAIC: Collaborative Compute-in-Memory µArrays for Flexible and Scalable Deep Learning

Amit Ranjan Trivedi, Shamma Nasrin, Priyesh Shukla, et al.

IEEE 43rd VLSI Test Symposium (VTS), Tempe, AZ, USA

DOI

ICEdge 2025

ProbCIMs: Compute-in-Memory Paradigms for Robust and Efficient Probabilistic Computing & AI

Priyesh Shukla, Amit Ranjan Trivedi, Siddarth Gottumukkula, M P Samartha

IEEE International Conference on Intelligent Computing and Systems at the Edge (ICEdge)

Scholar

DATE 2024

Navigating the unknown: Uncertainty-aware compute-in-memory autonomy of edge robotics

Nastaran Darabi, Priyesh Shukla, et al.

Design, Automation & Test in Europe Conference & Exhibition (DATE), Valencia, Spain

DOI

TCAS I 2022

MC-CIM: Compute-in-memory with monte-carlo dropouts for bayesian edge intelligence

Priyesh Shukla, Shamma Nasrin, et al.

IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS I)

DOI

VLSI 2021

Ultralow-power localization of insect-scale drones: Interplay of probabilistic filtering and compute-in-memory

Priyesh Shukla, Ankith Muralidhar, et al.

IEEE Transactions on Very Large Scale Integration (VLSI) Systems

DOI

AFFILIATES & PARTNERS

Dispatches

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Dec 15, 2025

Paper Accepted at ICEDGE 2025

Our paper titled 'ProbCIMs: Compute-in-Memory Paradigms for Robust and Efficient Probabilistic Computing & AI' accepted at the Intelligent Computing and Systems at the Edge (ICEDGE) 2025.

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Sep 22, 2025

Priyesh Shukla on insect-sized drones and life on the Edge

IIITH's Prof. Priyesh Shukla, a Ph.D from the University of Illinois, talks about exciting work on insect-sized drones and life on the Edge. He brings youthful energy and industrial R&D experience to his work in sustainable AI and Quantum Computing Systems at IIITH's Center for VLSI and Embedded Systems Technology and Computer Systems Group.

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