Haizhong Zheng

Postdoctoral Researcher
Electrical and Computer Engineering
Carnegie Mellon University
Ph.D. @ UMich
Email: haizhonz@andrew.cmu.edu

haizhong.jpeg

I am a postdoctoral researcher at InfiniAI Lab advised by Prof. Beidi Chen at Carnegie Mellon University. I am also a member of Catalyst Group at CMU. I received my Ph.D. degree from University of Michigan and was advised by Prof. Atul Prakash. Before that, I obtained my B.S. and M.S. degree from Shanghai Jiao Tong University, where I was advised by Prof. Haojin Zhu.

Research Interests: Efficient RL for LLMs; ML system; Agent; ML Security.

News

Dec 2025 RLBoost accepted to NSDI 2026.
Nov 2025 WAVE accepted to ASPLOS 2026.
Oct 2025 Gave an invited talk at Amazon SF AI Lab.
Jul 2025 Plato accepted to COLM 2025.
May 2025 Two papers (GRESO and Kinetics) accepted to NeurIPS 2025.

Selected Publications

* indicates equal contribution.

Preprint

  1. Preprint
    When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents?
    Yibo Peng* , James Song* , Lei Li* , Xinyu Yang , Mihai Christodorescu , Ravi Mangal , Corina Pasareanu , Haizhong Zheng , and Beidi Chen
    Preprint 2025
    arXiv Blog Code
  1. NeurIPS Workshop
    Prosperity before Collapse: How Far Can Off-Policy RL Reach with Stale Data on LLMs?
    Haizhong Zheng , Jiawei Zhao , and Beidi Chen
    NeurIPS Workshop 2025, Spotlight
    arXiv Blog Code

Conference

  1. NSDI
    RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs
    Yongji Wu* , Xueshen Liu* , Haizhong Zheng , Juncheng Gu , Beidi Chen , Z. Morley Mao , Arvind Krishnamurthy , and Ion Stoica
    NSDI 2026
    arXiv
  2. ASPLOS
    WAVE: Leveraging Architecture Observation for Privacy-Preserving Model Oversight
    Haoxuan Xu* , Chen Gong* , Beijie Liu* , Haizhong Zheng , Beidi Chen , and Mengyuan Li
    ASPLOS 2026
  3. NeurIPS
    Act Only When It Pays: Efficient Reinforcement Learning for LLM Reasoning via Selective Rollouts
    Haizhong Zheng , Yang Zhou , Brian R. Bartoldson , Bhavya Kailkhura , Fan Lai , Jiawei Zhao , and Beidi Chen
    NeurIPS 2025
    arXiv Blog Code
  4. NeurIPS
    Kinetics: Rethinking Test-Time Scaling Laws
    Ranajoy Sadhukhan* , Zhuoming Chen* , Haizhong Zheng , Yang Zhou , Emma Strubell , and Beidi Chen
    NeurIPS 2025
    arXiv Blog Code
  5. COLM
    Plato: Plan to Efficiently Decode for Large Language Model Inference
    Shuowei Jin* , Xueshen Liu* , Yongji Wu* , Haizhong Zheng , Qingzhao Zhang , Atul Prakash , Matthew Lentz , Danyang Zhuo , Feng Qian , and Z. Morley Mao
    COLM 2025
    arXiv
  6. ICLR
    ELFS: Label-Free Coreset Selection with Proxy Training Dynamics
    Haizhong Zheng* , Elisa Tsai* , Yifu Lu , Jiachen Sun , Brian R. Bartoldson , Bhavya Kailkhura , and Atul Prakash
    ICLR 2025
    arXiv
  7. WWW
    Harmful Terms and Where to Find Them: Measuring and Modeling Unfavorable Financial Terms and Conditions in Shopping Websites at Scale
    Elisa Tsai , Neal Mangaokar , Boyuan Zheng , Haizhong Zheng , and Atul Prakash
    WWW 2025, Oral
    arXiv
  8. NeurIPS
    Learn To be Efficient: Build Structured Sparsity in Large Language Models
    Haizhong Zheng , Xiaoyan Bai , Xueshen Liu , Z. Morley Mao , Beidi Chen , Fan Lai , and Atul Prakash
    NeurIPS 2024, Spotlight
    arXiv
  9. ECCV
    Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation
    Haizhong Zheng , Jiachen Sun , Shutong Wu , Bhavya Kailkhura , Z. Morley Mao , Chaowei Xiao , and Atul Prakash
    ECCV 2024
    arXiv
  10. ICLR
    CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception
    Jiachen Sun , Haizhong Zheng , Qingzhao Zhang , Atul Prakash , Z. Morley Mao , and Chaowei Xiao
    ICLR 2024
    arXiv
  11. ICLR
    Coverage-centric Coreset Selection for High Pruning Rates
    Haizhong Zheng , Rui Liu , Fan Lai , and Atul Prakash
    ICLR 2023
    arXiv Code
  12. CVPR
    Efficient Adversarial Training with Transferable Adversarial Examples
    Haizhong Zheng , Ziqi Zhang , Juncheng Gu , Honglak Lee , and Atul Prakash
    CVPR 2020
    arXiv Code
  13. NDSS
    Smoke Screener or Straight Shooter: Detecting Elite Sybil Attacks in User-Review Social Networks
    Haizhong Zheng , Minhui Xue , Hao Lu , Shuang Hao , Haojin Zhu , Xiaohui Liang , and Keith Ross
    NDSS 2018
    arXiv

Work Experience

Research Intern, Lawrence Livermore National Laboratory (LLNL), Livermore, CA May 2023 - Aug. 2023

Applied Scientist Intern, Amazon Web Services (AWS), Inc., Seattle, WA May 2021 - Aug. 2021