Haizhong Zheng

Ph.D. Candidate

Computer Science and Engineering

University of Michigan, Ann Arbor

Email: hzzheng@umich.edu

[CV] [Scholar] [LinkedIn]

I am a final-year Ph.D. student advised by Prof. Atul Prakash at University of Michigan. I will join Carnegie Mellon University as a postdoctoral researcher working with Prof. Beidi Chen in Jan. 2025. I received my B.S. and M.S. degree from Shanghai Jiao Tong University, where I was advised by Prof. Haojin Zhu.

I was a research intern in Lawrence Livermore National Laboratory (LLNL) in the summer of 2023, supervised by Dr. Bhavya Kailkhura on the topic of LLM inference efficiency. Previously, I was an Applied Scientist Intern mentored by Dr. Wei Ding and Dr. Qian Cui at AWS in the summer of 2021.

Research Interests: Hardware-aware efficient models, machine learning system, and data efficiency algorithm.

My research focuses on building models, algorithms, and systems for scalable and efficient ML. The goal is to bridge the gap between the rapid scaling of models and the slower scaling of hardware and high-quality data. In particular, my work has been along two lines: (1) Designing and training hardware-aware and system-aware models for fast model inference. (2) Designing algorithms for efficient data selection, augmentation, and human feedback.

Selected Publications

ELFS: Enhancing Label-Free Coreset Selection via Clustering-based Pseudo-Labeling [PDF]
Haizhong Zheng*, Elisa Tsai*, Yifu Lu, Jiachen Sun, Brian R. Bartoldson, Bhavya Kailkhura, Atul Prakash. Preprint

Adaptive Skeleton Graph Decoding [PDF]
Shuowei Jin*, Yongji Wu*, Haizhong Zheng, Qingzhao Zhang, Matthew Lentz, Z. Morley Mao, Atul Prakash, Feng Qian, Danyang Zhuo. Preprint

Learn To be Efficient: Build Structured Sparsity in Large Language Models [PDF]
Haizhong Zheng, Xiaoyan Bai, Xueshen Liu, Z. Morley Mao, Beidi Chen, Fan Lai, Atul Prakash.
Advances in Neural Information Processing Systems (NeurIPS), 2024 (Spotlight)

Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation [PDF]
Haizhong Zheng, Jiachen Sun, Shutong Wu, Bhavya Kailkhura, Z. Morley Mao, Chaowei Xiao, Atul Prakash.
European Conference on Computer Vision (ECCV), 2024

CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception [PDF]
Jiachen Sun, Haizhong Zheng, Qingzhao Zhang, Atul Prakash, Z. Morley Mao, Chaowei Xiao.
International Conference on Learning Representations (ICLR), 2024

Coverage-centric Coreset Selection for High Pruning Rates [PDF] [Code]
Haizhong Zheng, Rui Liu, Fan Lai, Atul Prakash.
International Conference on Learning Representations (ICLR), 2023

Efficient Adversarial Training with Transferable Adversarial Examples [PDF] [Code]
Haizhong Zheng, Ziqi Zhang, Juncheng Gu, Honglak Lee, Atul Prakash.
Conference on Computer Vision and Pattern Recognition (CVPR), 2020

Analyzing the Interpretability Robustness of Self-Explaining Models [PDF]
Haizhong Zheng, Earlence Fernandes, Atul Prakash.
International Conference on Machine Learning (ICML) Workshop, 2019

Smoke Screener or Straight Shooter: Detecting Elite Sybil Attacks in User-Review Social Networks [PDF]
Haizhong Zheng, Minhui Xue, Hao Lu, Shuang Hao, Haojin Zhu, Xiaohui Liang, Keith Ross.
Network and Distributed System Security (NDSS), 2018

* indicates equal contribution.

Work Experience

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


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


Teaching

Co-Lead Instuctor in EECS 598-012 (Machine Learning Security and Privacy)
University of Michigan, Winter 2023


Graduate Student Instuctor in EECS 281 (Data Structures and Algorithms)
University of Michigan, Fall 2021



Last updated: 2024.9