activity
20242026
collaborators

6 papers

eess.SP2026

A Spatial Array for Spectrally Agile Wireless Processing

Ali Rasteh, Andrew Hennessee, Ishaan Shivhare +3

Massive MIMO is a cornerstone of next-generation wireless communication, offering significant gains in capacity, reliability, and energy efficiency. However, to meet emerging deman…

cs.AR2025

zkPHIRE: A Programmable Accelerator for ZKPs over HIgh-degRee, Expressive Gates

Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow +3

Zero-Knowledge Proofs (ZKPs) have emerged as a powerful tool for secure and privacy-preserving computation. ZKPs enable one party to convince another of a statement's validity with…

cs.AR2025

MTU: The Multifunction Tree Unit for Accelerating Zero-Knowledge Proofs

Jianqiao Mo, Alhad Daftardar, Joey Ah-Kiow +4

Zero-Knowledge Proofs (ZKPs) are critical for privacy-preserving techniques and verifiable computation. Many ZKP protocols rely on key kernels such as the SumCheck protocol and Mer…

cs.AR2025

Need for zkSpeed: Accelerating HyperPlonk for Zero-Knowledge Proofs

Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow +4

Zero-Knowledge Proofs (ZKPs) are rapidly gaining importance in privacy-preserving and verifiable computing. ZKPs enable a proving party to prove the truth of a statement to a verif…

cs.LG2025

Huff-LLM: End-to-End Lossless Compression for Efficient LLM Inference

Patrick Yubeaton, Tareq Mahmoud, Shehab Naga +8

As they become more capable, large language models (LLMs) have continued to rapidly increase in size. This has exacerbated the difficulty in running state of the art LLMs on small,…

cs.CR2024

TruncFormer: Private LLM Inference Using Only Truncations

Patrick Yubeaton, Jianqiao Cambridge Mo, Karthik Garimella +4

Private inference (PI) serves an important role in guaranteeing the privacy of user data when interfacing with proprietary machine learning models such as LLMs. However, PI remains…