About Me

I am a final-year Ph.D. candidate at UC San Diego. Previously, I received my bachelor degree in Electronic Engineering from Shanghai Jiao Tong University. My research focuses on large language model efficiency, including distributed training acceleration and algorithm–system co-design for scalable and secure LLM applications. I'm honored to be recognized as the 2025 Machine Learning and Systems Rising Star.

Experience

Work

Jul 2025 - Dec 2025

PyTorch Compiler @ Meta

Research Intern

Compiler optimization passes for SimpleFSDP and AutoParallel

Jul 2024 - Sep 2024

PyTorch Distributed @ Meta

Research Intern

SimpleFSDP prototype and composability support

Jul 2022 - Sep 2022

Intel AI Labs

Research Intern

Adaptive optimization for accelerated distributed GNN training

Education

Sep 2021 – May 2026

UC San Diego

Ph.D. in Machine Learning and Data Science

Advisor: Prof. Farinaz Koushanfar

Sep 2017 – Jun 2021

Shanghai Jiao Tong University

B.E. in Electronic Engineering

Research

My research focuses on building scalable, efficient, and trustworthy systems. I work across the full stack algorithm-system co-design and co-optimization to enable secure and safe AI. For full publication list, please checkout my Google Scholar.

Scalable Computing

Arxiv 25

SimpleFSDP: Simpler Fully Sharded Data Parallel with torch.compile

Ruisi Zhang*, Tianyu Liu*, Will Feng, Andrew Gu, Sanket Purandare, Wanchao Liang, Francisco Massa

Paper Code Slide
DAC 23

AdaGL: Adaptive Learning for Agile Distributed Training of Gigantic GNNs

Ruisi Zhang, Mojan Javaheripi, Zahra Ghodsi, Amit Bleiweiss, Farinaz Koushanfar

Paper Slide

Provenance of AI-Generated Content

USENIX Security 24

REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models

Ruisi Zhang, Shehzeen Samarah Hussain, Paarth Neekhara, Farinaz Koushanfar

Paper Code Slide
Arxiv 25

Robust Zero Knowledge Verifiable Watermarking of Code LLMs with ML/Crypto Co-Design

Ruisi Zhang, Neusha Javidnia, Nojan Sheybani, Farinaz Koushanfar

Paper

Edge AI IP Protection

DAC 2024

EmMark: Robust Watermarks for IP Protection of Embedded Quantized Large Language Models

Ruisi Zhang, Farinaz Koushanfar

Paper Code Slide
DAC 2026

AttestLLM: Efficient Attestation Framework for Billion-scale On-device LLMs

Ruisi Zhang*, Yifei Zhao*, Neusha Javidnia, Mengxin Zheng, Farinaz Koushanfar

Paper

Security of Chip Design

MLCAD 2024

Automated Physical Design Watermarking Leveraging Graph Neural Networks

Ruisi Zhang, Rachel Selina Rajarathnam, David Z Pan, Farinaz Koushanfar

Paper Code Slide
IEEE TCAD 2025

ICMarks: A Robust Watermarking Framework for Integrated Circuit Physical Design IP Protection

Ruisi Zhang, Rachel Selina Rajarathnam, David Z Pan, Farinaz Koushanfar

Paper Code

Awards

  • 2025

    Machine Learning and Systems Rising Star

  • 2024

    Qualcomm Innovation Fellowship Finalist

  • 2023

    DAC Young Fellow

  • 2021

    ECE Department Fellowship at UC San Diego

  • 2018-2020

    Academic Excellence Scholarship at SJTU

Service

  • Conference Reviewer ICCV; CVPR; ICASSP; ICML; EMNLP; ACL, IJCNN
  • Journal Reviewer IEEE TDSC; IEEE TCAD; IEEE TNNLS; IEEE TIFS
  • AE Committee CCS, NDSS

Misc

I have a (non-exhaustive) reading list of research papers, talks, and books that I enjoy.

Fun facts about me:

I'm recently listening to Chen Li's music.