Director, AI Theory Lab
Principal Researcher, Noah's Ark Lab
Huawei Technologies
E-mail: zhenguol AT gmail.com
We are hiring (Chief Scientist/Researcher/Intern):
Topics: Foundation of Generative AI / AI for Math / AI Agents
Responsibilities: Conduct frontier AI research on high-impact projects
Qualifications: Proven track record in AI research and solving real-world problems. Team work.
Locations: Hong Kong, Shenzhen, Beijing, Nanjing, London
About
I am currently the director of the AI Theory Lab in Huawei Noah’s Ark Lab, and an Adjunct Professor in the department of computer science and engineering, The Hong Kong University of Science and Technology. I was an associate research scientist in the department of electrical engineering, Columbia University, working with Prof. Shih-Fu Chang. I received BS and MS degrees in mathematics at Peking University, and PhD degree in machine learning at The Chinese University of Hong Kong, advised by Prof. Xiaoou Tang. My research interests include machine learning and artificial intelligence. I am an Area Chair of NeurIPS 2023 and ICLR 2024, and selected as 2023 AI 2000 Most Influential Scholar between 2013-2022 (by AMiner) and Top 2% Scientists Worldwide 2023 (by Stanford University).
My current research focus is in the foundation of generative AI and its real-world applications to AIGC, mathematical reasoning, and scientific discovery.
DDP: Diffusion Model for Dense Visual Prediction, ICCV 2023 Yuanfeng Ji, Zhe Chen, Enze Xie, Lanqing Hong, Xihui Liu, Zhaoqiang Liu, Tong Lu, Zhenguo Li, Ping Luo.
MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation, ICCV 2023 Chongjian Ge, Junsong Chen, Enze Xie, Zhongdao Wang, Lanqing Hong, Huchuan Lu, Zhenguo Li, Ping Luo.
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation, ICCV 2023 Haiyang Wang, Hao Tang, Shaoshuai Shi, Aoxue Li, Zhenguo Li, Bernt Schiele, Liwei Wang.
DT-Solver: Automated Theorem Proving with Dynamic-Tree Sampling Guided by Proof-level Value Function, ACL 2023 Wang Haiming, Ye Yuan, Zhengying Liu, Jianhao Shen, Yichun Yin, Jing Xiong, Enze Xie, Han Shi, Yujun Li, lin li, Jian Yin, Zhenguo Li, Xiaodan Liang.
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization, ICML 2023 Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhi-Ming Ma.
CO3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving, ICLR 2023 Runjian Chen, Yao Mu, Runsen Xu, Wenqi Shao, Chenhan Jiang, Hang Xu, Yu Qiao, Zhenguo Li, Ping Luo.
Fair-CDA: Continuous and Directional Augmentation for Group Fairness, AAAI 2023 Rui Sun, Fengwei Zhou, Zhenhua Dong, Chuanlong Xie, Lanqing Hong, Jiawei Li, Rui Zhang, Zhen Li, Zhenguo Li
DAMix: Exploiting Deep Autoregressive Model Zoo for Improving Lossless Compression Generalization, AAAI 2023 Qishi Dong, Fengwei Zhou, Ning Kang, Chuanlong Xie, Shifeng Zhang, Jiawei Li, Heng Peng, Zhenguo Li.
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization, NeurIPS 2022 Qishi Dong, Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li.
Understanding Square Loss in Training Overparametrized Neural Network Classifiers, NeurIPS 2022, Spotlight Tianyang Hu, Jun Wang, Wenjia Wang, Zhenguo Li.
DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection, NeurIPS 2022 Lewei Yao, Jianhua Han, Youpeng Wen, Xiaodan Liang, Dan Xu, Wei Zhang, Zhenguo Li, Chunjing Xu, Hang Xu.
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds, NeurIPS 2022 Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li, Jianan Li, Zhenguo Li, Liwei Wang.
DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction, ECCV 2022 Kaichen Zhou, Lanqing Hong, Changhao Chen, Hang Xu, Chaoqiang Ye, Qingyong Hu, Zhenguo Li.
Generative Negative Text Replay for Continual Vision-Language Pretraining, ECCV 2022 Shipeng Yan, Lanqing Hong, Hang Xu, Jianhua Han,Tinne Tuytelaars, Zhenguo Li, Xuming He.
CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving, ECCV 2022 Kaican Li, Kai Chen, Haoyu Wang, Lanqing Hong, Chaoqiang Ye, Jianhua Han, Yukuai Chen, Wei Zhang, Chunjing Xu, Dit-Yan Yeung, Xiaodan Liang, Zhenguo Li, Hang Xu.
AutoHash: Learning Higher-order Feature Interactions for Deep CTR Prediction, IEEE Trans. on Knowledge and Data Engineering (TKDE) 2022 Niannan Xue, Bin Liu, Huifeng Guo, Ruiming Tang, Fengwei Zhou, Stefanos Zafeiriou, Yuzhou Zhang, Jun Wang, Zhenguo Li.
PILC: Practical Image Lossless Compression with an End-to-end GPU Oriented Neural Framework, CVPR 2022 Ning Kang, Shanzhao Qiu, Shifeng Zhang, Zhenguo Li, Shu-Tao Xia.
ManiTrans: Entity-Level Text-Guided Image Manipulation via Token-wise Semantic Alignment and Generation, CVPR 2022, Oral Jianan Wang, Guansong Lu, Hang Xu, Zhenguo Li, Chunjing Xu, Yanwei Fu.
OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization, CVPR 2022, Oral Nanyang Ye, Kaican Li, Haoyue Bai, Runpeng Yu, Lanqing Hong, Fengwei Zhou, Zhenguo Li, Jun Zhu.
Long-tail Recognition via Compositional Knowledge Transfer, CVPR 2022 Sarah Parisot, Pedro M Esperanca, Steven McDonagh, Tamas J Madarasz, Yongxin Yang, Zhenguo Li.
Semi-Supervised Object Detection via Multi-instance Alignment with Global Class Prototypes, CVPR 2022 Aoxue Li, Peng Yuan, Zhenguo Li.
Revisiting Over-smoothing in BERT from the Perspective of Graph, ICLR 2022, Spotlight, notable-top-25% Han Shi, Jiahui Gao, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee and James Kwok.
On Redundancy and Diversity in Cell-based Neural Architecture Search, ICLR 2022 Xingchen Wan, Binxin Ru, Pedro M Esperança, Zhenguo Li.
Generalizing Few-Shot NAS with Gradient Matching, ICLR 2022 Shoukang Hu, Ruochen Wang, Lanqing Hong, Zhenguo Li, Cho-Jui Hsieh and Jiashi Feng.
Rethinking Adversarial Transferability from a Data Distribution Perspective, ICLR 2022 Yao Zhu, Jiacheng Sun, Zhenguo Li.
How Well Does Self-Supervised Pre-Training Perform with Streaming Data?, ICLR 2022 Dapeng Hu, Shipeng Yan, Qizhengqiu Lu, Lanqing Hong, Hailin Hu, Yifan Zhang, Zhenguo Li, Xinchao Wang and Jiashi Feng.
Memory Replay with Data Compression for Continual Learning, ICLR 2022 Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong and Jun Zhu.
Improving Model Training with Multi-fidelity Hyperparameter Evaluation, MLSys 2022 Yimin Huang, Yujun Li, Hanrong Ye, Zhenguo Li, Zhihua Zhang.
AutoBERT-Zero: Evolving BERT Backbone from Scratch, AAAI 2022 Jiahui Gao, Hang Xu, Han shi, Xiaozhe Ren, Philip L.H. Yu, Xiaodan Liang, Xin Jiang, Zhenguo Li.
Task-customized Self-supervised Pre-training with Scalable Dynamic Routing, AAAI 2022 Zhili Liu, Jianhua Han, Lanqing Hong, Hang Xu, Kai Chen, Chunjing Xu, Zhenguo Li.
AIM: Automatic Interaction Machine for Click-Through Rate Prediction, IEEE Trans. on Knowledge and Data Engineering (TKDE) 2022 Chenxu Zhu, Bo Chen, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu.
iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder, NeurIPS 2021, Spotlight, top 3% Shifeng Zhang, Ning Kang, Tom Ryder, Zhenguo Li.
OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression, NeurIPS 2021 Chen Zhang, Shifeng Zhang, Fabio Maria Carlucci, Zhenguo Li.
On Effective Scheduling of Model-based Reinforcement Learning, NeurIPS 2021 Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li.
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps, NeurIPS 2021 Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Jiawei Li, Sung-Ho Bae, Zhenguo Li.
Towards a Theoretical Framework of Out-of-Distribution Generalization, NeurIPS 2021 Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang.
SODA10M: Towards Large-Scale Object Detection Benchmark for Autonomous Driving, NeurIPS 2021, Datasets and Benchmarks Track Jianhua Han, Xiwen Liang, Hang Xu, Kai Chen, Lanqing HONG, Chaoqiang Ye, Wei Zhang, Zhenguo Li, Xiaodan Liang, Chunjing Xu.
One Million Scenes for Autonomous Driving: ONCE Dataset, NeurIPS 2021, Datasets and Benchmarks Track Jiageng Mao, Minzhe Niu, Chenhan Jiang, hanxue liang, Jingheng Chen, Xiaodan Liang, Yamin Li, Chaoqiang Ye, Wei Zhang, Zhenguo Li, Jie Yu, Chunjing Xu, Hang Xu.
NASOA: Towards Faster Task-oriented Online Fine-tuning with a Zoo of Models, ICCV 2021 Hang Xu, Ning Kang, Gengwei Zhang, Chuanlong Xie, Xiaodan Liang, Zhenguo Li.
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization, ICCV 2021 Haoyue Bai, Fengwei Zhou, Lanqing Hong, Nanyang Ye, S.-H. Gary Chan, Zhenguo Li.
Exploring Geometry-aware Contrast and Clustering Harmonization for Self-supervised 3D Object Detection, ICCV 2021 Hanxue Liang, Chenhan Jiang, Dapeng Feng, Xin Chen, Hang Xu, Xiaodan Liang, Wei Zhang, Zhenguo Li, Luc Van Gool.
DetCo: Unsupervised Contrastive Learning for Object Detection, ICCV 2021 Enze Xie, Jian Ding, Wenhai Wang, Xiaohang Zhan, Hang Xu, Zhenguo Li, Ping Luo.
Multisiam: Self-supervised multi-instance siamese representation learning for autonomous driving, ICCV 2021 Kai Chen, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung.
G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation, ICCV 2021 Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang.
Adversarial Robustness for Unsupervised Domain Adaptation, ICCV 2021 Muhammad Awais, Fengwei Zhou, Hang Xu, Lanqing Hong, Ping Luo, Sung-Ho Bae, Zhenguo Li.
Towards Understanding the Generative Capability of Adversarially Robust Classifiers, ICCV 2021, Oral Yao Zhu, Jiacheng Ma, Jiacheng Sun, Zewei Chen, Rongxin Jiang, Zhenguo Li.
AutoDis: Automatic Discretization for Embedding Numerical Features in CTR Prediction, KDD 2021 Huifeng Guo, Bo Chen, Ruiming Tang, Zhenguo Li, Xiuqiang He.
SparseBERT: Rethinking the Importance Analysis in Self-attention, ICML 2021 Han Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, James T. Kwok.
iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression, CVPR 2021 Shifeng Zhang, Chen Zhang, Ning Kang, Zhenguo Li.
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS, NeurIPS 2020 Han Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, Tong Zhang.
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending, ECCV 2020 Hang Xu, Shaoju Wang, Xinyue Cai, Wei Zhang, Xiaodan Liang, Zhenguo Li.
Federated Meta-Learning with Fast Convergence and Efficient Communication, arXiv 22 Feb 2018 Fei Chen, Mi Luo, Zhenhua Dong, Zhenguo Li, Xiuqiang He.
Deep Meta-Learning: Learning to Learn in the Concept Space, arXiv 10 Feb 2018.
Fengwei Zhou, Bin Wu, Zhenguo Li.
Meta-SGD: Learning to Learn Quickly for Few-Shot Learning, arXiv 31 Jul 2017.
Zhenguo Li, Fengwei Zhou, Fei Chen, Hang Li.
Graph Edge Partitioning via Neighborhood Heuristic, KDD 2017, oral.
Chenzi Zhang, Fan Wei, Qin Liu, Zhihao Tang, Zhenguo Li.
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction, IJCAI 2017.
Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He.
VENUS: A System for Streamlined Graph Computation on a Single PC, IEEE Trans. on Knowledge and Data Engineering (TKDE), 2016.
Qin Liu, Jiefeng Cheng, Zhenguo Li, John C.S. Lui.
Walking in the Cloud: Parallel SimRank at Scale, PVLDB 2016.
Zhenguo Li, Yixiang Fang, Qin Liu, Jiefeng Cheng, Reynold Cheng, and John C.S. Lui.
VENUS: Vertex-Centric Streamlined Graph Computation on a Single PC, ICDE 2015.
Jiefeng Cheng, Qin Liu, Zhenguo Li, Wei Fan, John C.S. Lui, and Cheng He.
Locally Linear Hashing for Extracting Non-Linear Manifolds, CVPR 2014.
Go Irie, Zhenguo Li, Xiao-Ming Wu, and Shih-Fu Chang.
Analyzing the Harmonic Structure in Graph-Based Learning, NIPS 2013.
Xiao-Ming Wu, Zhenguo Li, and Shih-Fu Chang.
Learning with Partially Absorbing Random Walks, NIPS 2012.
Xiao-Ming Wu, Zhenguo Li, Anthony Man-Cho So, John
Wright, and Shih-Fu Chang.
Segmentation Using Superpixels: A Bipartite Graph Partitioning Approach, CVPR 2012.
Zhenguo Li, Xiao-Ming Wu, and Shih-Fu Chang.
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite-Quadratic-Linear Programming, NIPS 2009.
Xiao-Ming Wu, Anthony Man-Cho So, Zhenguo Li, and Shuo-Yen Robert Li.
Constrained Clustering via Spectral Regularization, CVPR 2009.
Zhenguo Li, Jianzhuang Liu, and Xiaoou Tang.
Pairwise Constraint Propagation by Semidefinite Programming for Semi-Supervised Classification, ICML 2008.
Zhenguo Li, Jianzhuang Liu, and Xiaoou Tang.
Plane-Based Optimization for 3D Object Reconstruction from Single Line Drawings, T-PAMI, 2008.
Jianzhuang Liu, Liangliang Cao, Zhenguo Li, and Xiaoou Tang.