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.
Journals

  1. 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 '23    [ http , pdf , pdf ]

  2. 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    [ http , pdf ]

  3. 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    [ http , pdf ]

  4. 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    [ http , pdf ]

  5. 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    [ http , pdf ]

  6. 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    [ http , pdf , pdf ]

  7. 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    [ http , pdf ]

  8. Neural Architecture Transfer
    Zhichao Lu, Gautam Sreekumar, Erik Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, and Vishnu N. Boddeti
    IEEE TPAMI '21    [ http , pdf , pdf ]

  9. A New Many-Objective Evolutionary Algorithm based on Generalized Pareto Dominance
    Shuwei Zhu, Lihong Xu, Erik Goodman, and Zhichao Lu
    IEEE TCYB '21    [ http , pdf ]

  10. 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    [ http , pdf , pdf ]

Conferences

  1. Revisiting Residual Networks for Adversarial Robustness
    Shihua Huang, Zhichao Lu, Kalyanmoy Deb, and Vishnu N. Boddeti
    CVPR '23    [ http , pdf ]

  2. 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    [ http , pdf ]

  3. 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    [ http ]

  4. 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    [ http ]

  5. FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
    Shihua Huang, Zhichao Lu, Ran Cheng, and Cheng He
    ICCV '21    [ http , pdf ]

  6. End-to-End Dense Video Captioning with Parallel Decoding
    Teng Wang, Ruimao Zhang, Zhichao Lu, Feng Zheng, Ran Cheng, and Ping Luo
    ICCV '21    [ http , pdf ]

  7. NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search
    Zhichao Lu, Kalyanmoy Deb, Erik Goodman, Wolfgang Banzhaf, and Vishnu N. Boddeti
    ECCV '20 (Oral presentation)    [ http , pdf ]

  8. 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    [ http ]

  9. MUXConv: Information Multiplexing in Convolutional Neural Networks
    Zhichao Lu, Kalyanmoy Deb, and Vishnu N. Boddeti
    CVPR '20    [ http , pdf ]

  10. 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)    [ http , pdf ]

  11. Finding Reliable Solutions in Bilevel Optimization Problems under Uncertainties
    Zhichao Lu, Kalyanmoy Deb, and Ankur Sinha
    GECCO '16 (Best Paper Award Finalist)

Book Chapters

  1. 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)