Assistant Professor
City University of Hong Kong (CityU)
luzhichaocn [at] gmail [dot] com
Zhichao Lu received Ph.D degree in Electrical and Computer Engineering from
Michigan State University under the supervision of Prof.
Kalyanmoy Deb
(FIEEE, FACM),
where he studied bilevel optimization, evolutionary multi-objective optimization,
and neural architecture search.
In the broad context of AI, his current research focuses on the intersections of
evolutionary computation, learning, and optimization, notably on developing efficient
and automated ML/DL algorithms and systems, with the overarching goal of making
AI accessible to everyone.
Prospective Students: I am always looking for self-motivated students with strong mathematical and programming background. Please refer to openings for potential opportunities.
- Enhancing Multimodal Learning via Hierarchical Fusion Architecture Search
With Inconsistency Mitigation
Kaifang Long, Chuntao Ding, Lianbo Ma, Qing Li, Min Huang, Jianhui Lv, and Zhichao Lu
IEEE TIP '25 [
,
]
- NestQuant: Post-Training Integer-Nesting Quantization for On-Device DNN
Jianhang Xie, Chuntao Ding, Xiaqing Li, Shenyuan Ren, Yidong Li, and Zhichao Lu
IEEE TMC '25 [
,
]
- ShadowMaskFormer: Mask Augmented Patch Embedding for Shadow Removal
Zhuohao Li, Guoyang Xie, Guannan Jiang, and Zhichao Lu
IEEE TAI '25 [
,
]
- Neural Architecture Search as Multiobjective Optimization Benchmarks:
Problem Formulation and Performance Assessment
Zhichao Lu, Ran Cheng, Yaochu Jin, Kay Chen Tan, and Kalyanmoy Deb
IEEE TEVC '24 [
,
,
]
- TFormer: A Transmission-Friendly ViT Model for IoT Devices
Zhichao Lu, Chuntao Ding, Felix Juefei-Xu, Vishnu Naresh Boddeti, and Shangguang Wang
IEEE TPDS '23 [
,
]
- LoNAS: Low-Cost Neural Architecture Search Using a
Three-Stage Evolutionary Algorithm
Wei Fang, Zhenhao Zhu, Shuwei Zhu, Jun Sun, Xiaojun Wu, and Zhichao Lu
IEEE CIM '23 [
,
]
- A Resource-Efficient Feature Extraction
Framework for Image Processing in IoT Devices
Chuntao Ding, Yidong Li, Zhichao Lu , Shangguang Wang, and Guo Song
IEEE TMC '22 [
,
]
- Surrogate-Assisted Multiobjective Neural Architecture Search for
Real-Time Semantic Segmentation
Zhichao Lu, Ran Cheng, Shihua Huang, Haoming Zhang, Changxiao Qiu, and Fan Yang
IEEE TAI '22 [
,
]
- Towards Transmission-friendly and Robust CNN Models over Cloud and Device
Chuntao Ding, Zhichao Lu, Felix Juefei-Xu, Vishnu N. Boddeti, Yidong Li, and Jiannong Cao
IEEE TMC '22 (Best Paper Award) [
,
,
]
- Minimizing Expected Deviation in Upper-level Outcomes Due to Lower-level Decision-making Uncertainty in
Hierarchical Problems
Kalyanmoy Deb, Zhichao Lu, Ian Kropp, J. Sebastian Hernandez-Suarez, Rayan Hussein, Steven Miller, and A. Pouyan Nejadhashemi
IEEE TEVC '22 [
,
]
- Neural Architecture Transfer
Zhichao Lu, Gautam Sreekumar, Erik Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, and Vishnu N. Boddeti
IEEE TPAMI '21 [
,
,
]
- A New Many-Objective Evolutionary Algorithm based on Generalized Pareto Dominance
Shuwei Zhu, Lihong Xu, Erik Goodman, and Zhichao Lu
IEEE TCYB '21 [
,
]
- Multiobjective Evolutionary
Design of Deep Convolutional Neural Networks for Image Classification
Zhichao Lu, Ian Whalen, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman, Wolfgang Banzhaf, and Vishnu N. Boddeti
IEEE TEVC '21 [
,
,
]
- Rethinking Code Similarity for Automated Algorithm Design with LLMs
Rui Zhang, and Zhichao Lu
ICLR '26 [
,
]
- FAST: Foreground-aware Diffusion with Accelerated Sampling Trajectory
for Segmentation-oriented Anomaly Synthesis
Xichen Xu, Yanshu Wang, Jinbao Wang, Xiaoning Lei, Guoyang Xie, Guannan Jiang, and Zhichao Lu
NeurIPS '25 [
,
]
- DEIM: DETR with Improved Matching for Fast Convergence
Shihua Huang, Zhichao Lu, Xiaodong Cun, Yongjun Yu, Xiao Zhou, and Xi Shen
CVPR '25 [
,
]
- Trade-offs in Image Generation: How Do Different Dimensions Interact?
Sicheng Zhang, Binzhu Xie, Zhonghao Yan, Yuli Zhang, Donghao Zhou, Xiaofei Chen, Shi Qin, Jiaqi Liu, Guoyang Xie, and Zhichao Lu
ICCV '25 [
,
]
- Learning from Loss Landscape: Generalizable Mixed-Precision Quantization via
Adaptive Sharpness-Aware Gradient Aligning
Lianbo Ma, Jianlun Ma, Yuee Zhou, Guoyang Xie, Qiang He, and Zhichao Lu
ICML '25 [
]
- Revisiting Multimodal Fusion for 3D Anomaly Detection from an Architectural Perspective
Kaifang Long, Guoyang Xie, Lianbo Ma, Jiaqi Liu, and Zhichao Lu
AAAI '25 [
,
]
- Mitigating Social Bias in Large Language Models: A Multi-Objective Approach
within a Multi-Agent Framework
Zhenjie Xu, Wenqing Chen, Yi Tang, Xuanying Li, Cheng Hu, Zhixuan Chu, Kui Ren, Zibin Zheng, and Zhichao Lu
AAAI '25 [
,
]
- Multi-objective Evolution of Heuristic Using Large Language Model
Shunyu Yao, Fei Liu, Xi Lin, Zhichao Lu, Zhenkun Wang, and Qingfu Zhang
AAAI '25 (Oral) [
,
]
- Design Principle Transfer in Neural Architecture Search via Large Language Models
Xun Zhou, Xingyu Wu, Liang Feng, Zhichao Lu, and Kay Chen Tan
AAAI '25 (Oral) [
,
]
- Towards Understanding the Effectiveness of Automatic Heuristic Design with Large Language Models
Rui Zhang, Fei Liu, Xi Lin, Zhenkun Wang, Zhichao Lu, and Qingfu Zhang
PPSN '24 [
,
]
- Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model
Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, and Qingfu Zhang
ICML '24 (Oral) [
,
]
- Self-Para-Consistency: Improving Reasoning Tasks at Low Cost for Large Language Models
Wenqing Chen, Weicheng Wang, Zhixuan Chu, Kui Ren, Zibin Zheng, and Zhichao Lu
ACL '24 [
]
- Revisiting Residual Networks for Adversarial Robustness
Shihua Huang, Zhichao Lu, Kalyanmoy Deb, and Vishnu N. Boddeti
CVPR '23 [
,
]
- Mitigating Task Interference in Multi-Task Learning via Explicit Task Routing
with Non-Learnable Primitives
Chuntao Ding, Zhichao Lu, Shangguang Wang, Ran Cheng and Vishnu N. Boddeti
CVPR '23 [
,
]
- Seed Feature Maps-based CNN Models for LEO Satellite Remote Sensing Services
Zhichao Lu, Chuntao Ding, Shangguang Wang, Ran Cheng, Felix Juefei-Xu and Vishnu N. Boddeti
ICWS '23 [
]
- VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix
Teng Wang, Wenhao Jiang, Zhichao Lu, Feng Zheng, Ran Cheng, Chengguo Yin, and Ping Luo
ICML '22 [
]
- FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
Shihua Huang, Zhichao Lu, Ran Cheng, and Cheng He
ICCV '21 [
,
]
- End-to-End Dense Video Captioning with Parallel Decoding
Teng Wang, Ruimao Zhang, Zhichao Lu, Feng Zheng, Ran Cheng, and Ping Luo
ICCV '21 [
,
]
- NSGANetV2: Evolutionary Multi-Objective
Surrogate-Assisted Neural Architecture Search
Zhichao Lu, Kalyanmoy Deb, Erik Goodman, Wolfgang Banzhaf, and Vishnu N. Boddeti
ECCV '20 (Oral) [
,
]
- NSGA-Net: Neural
Architecture Search using Multi-Objective Genetic Algorithm (Extended Abstract)
Zhichao Lu, Ian Whalen, Vishnu N. Boddeti, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman, and Wolfgang Banzhaf
IJCAI '20 [
]
- MUXConv:
Information Multiplexing in Convolutional Neural Networks
Zhichao Lu, Kalyanmoy Deb, and Vishnu N. Boddeti
CVPR '20 [
,
]
- NSGA-Net: Neural
Architecture Search using Multi-Objective Genetic Algorithm
Zhichao Lu, Ian Whalen, Vishnu N. Boddeti, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman, and Wolfgang Banzhaf
GECCO '19 (Best Paper Award) [
,
]
- Finding Reliable Solutions
in Bilevel Optimization Problems under Uncertainties
Zhichao Lu, Kalyanmoy Deb, and Ankur Sinha
GECCO '16 (Best Paper Award Finalist)
- Kalyanmoy Deb, Ankur Sinha, Pekka Malo, and Zhichao Lu,
Approximate Bilevel Optimization with Population-Based Evolutionary Algorithms,
In: Dempe S., Zemkoho A. (eds) Bilevel Optimization. Springer Optimization and Its Applications, vol 161.
Springer, Cham, 2020.
(ISBN 978-3-030-52118-9)