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
ICLR 2026 Workshop on Trustworthy AI

SureFED: Robust Federated Learning via Uncertainty-Aware Inward and Outward Inspection

Nasimeh Heydaribeni*, Ruisi Zhang*, Tara Javidi, Cristina Nita-Rotaru, Farinaz Koushanfar

Paper
Nature Machine Intelligence 24

Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks

Nasimeh Heydaribeni, Xinrui Zhan, Ruisi Zhang, Tina Eliassi-Rad, Farinaz Koushanfar

Paper Code
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

Arxiv 25

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

Ruisi Zhang*, Neusha Javidnia*, Nojan Sheybani, Farinaz Koushanfar

Paper
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

Edge AI IP Protection

DAC 2026

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

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

Paper
DAC 2024

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

Ruisi Zhang, Farinaz Koushanfar

Paper Code Slide

Security of AI-assisted Chip Design

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
MLCAD 2024

Automated Physical Design Watermarking Leveraging Graph Neural Networks

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

Paper Code Slide

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

Fun facts about me:

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