Dr. Ye Shi received the Ph.D. degree at the University of Technology Sydney, Australia in 2018. Dr Shi served as a Research Assistant at the University of New South Wales, Australia and a Postdoctoral Fellow at the University of Technology Sydney from 2017 to 2020. Dr. Shi has been an Assistant Professor (PI) in the School of Information Science and Technology at ShanghaiTech University since January 2021. He is leading the YesAI Lab at ShanghaiTech University.

✡️ Research Interests

• Trustworthy AI: controllable, robust, efficient, and safe AI methods, particularly interested in diffusion models, reinforcement learning, and federated learning;

• Deep Learning Basics: optimal transport, implicit differentiation, optimization layer, deep equilibrium models;

• AI \& Optimization Applications: optimization and control, humanoid robot, embodied AI, smart grid, etc.

🔊 Position Openings

• Postgraduate Students: Dr. Ye Shi recruits 2~3 postgraduate students for each academic year. The candidate is expected to be self-motivated in one of the following areas: Trustworthy AI, Deep Learning Basics, Optimization and Control, Smart Energy, etc. A solid mathematical background and sufficient programming skills are required. If you are interested in this opening, please email me your CV;
• Undergraduates/Visting Students: We warmly welcome students majored in Machine Learning, Computer Science, Mathematics, Electric Engineering, Information and Communication Engineering, and other related disciplines to join our group;
• Research Assistant: Dr. Ye Shi is seeking a research assistant to work closely with the principal investigator, postdoc, and students in the laboratory. A Bachelor’s or master’s degree in mathematics, computer science, machine learning, electrical engineering, control, or related areas is required.

🔥 News

📝 Selected Publications

NeurIPS 2024

Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization, NeurIPS 2024

Shutong Ding, Ke Hu, Zhenhao Zhang, Kan Ren, Weinan Zhang, Jingyi Yu, Jingya Wang, Ye Shi*

[paper] [project] [code]

NeurIPS 2024

Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective, NeurIPS 2024

Haixiang Sun, Ye Shi*

NeurIPS 2024

Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method, NeurIPS 2024

Bikang Pan, Wei Huang, Ye Shi*

[paper] [code]

ICML 2024

Guidance with Spherical Gaussian Constraint for Conditional Diffusion, ICML 2024

Lingxiao Yang, Shutong Ding, Yifan Cai, Jingyi Yu, Jingya Wang, Ye Shi*

[paper] [code]

ICML 2024

Harmonizing Generalization and Personalization in Federated Prompt Learning, ICML 2024

Tianyu Cui, Hongxia Li, Jingya Wang, Ye Shi*

[paper] [code]

CVPR 2024

Global and Local Prompts Cooperation via Optimal Transport for Federated Learning, CVPR 2024

Hongxia Li, Wei Huang, Jingya Wang, Ye Shi*

[paper] [code]

CVPR 2024

$\text{S}^2$Fusion: A Unified Diffusion Framework for Scene-aware Human Motion Estimation from Sparse Signals, CVPR 2024

Jiangnan Tang, Jingya Wang*, Kaiyang Ji, Lan Xu, Jingyi Yu, Ye Shi*

[paper] [code]

CVPR 2024

HOI-M$^3$: Capture Multiple Humans and Objects Interaction within Contextual Environment, CVPR 2024

Juze Zhang, Jingyan Zhang, Zining Song, Zhanhe Shi, Chengfeng Zhao, Ye Shi, Jingyi Yu, Lan Xu, Jingya Wang*

[paper] [project] [code]

ICLR 2024

Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory, ICLR 2024

Wei Huang, Ye Shi*, Zhongyi Cai, Taiji Suzuki

[paper]

NeurIPS 2023

Reduced Policy Optimization for Continuous Control with Hard Constraints, NeurIPS 2023

Shutong Ding, Jingya Wang, Yali Du, Ye Shi*

[paper] [code]

NeurIPS 2023

Two Sides of The Same Coin: Bridging Deep Equilibrium Models and Neural ODEs via Homotopy Continuation, NeurIPS 2023

Shutong Ding#, Tianyu Cui#, Jingya Wang, Ye Shi*

[paper] [code]

NeurIPS 2023

CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels, NeurIPS 2023

Wanxing Chang, Ye Shi, Jingya Wang

[paper] [project] [code]

NeurIPS 2023

Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning, NeurIPS 2023

Zhongyi Cai, Ye Shi*, Wei Huang, Jingya Wang

[paper] [code]

NeurIPS 2023

Contextually Affinitive Neighborhood Refinery for Deep Clustering, NeurIPS 2023

Chunlin Yu, Ye Shi, Jingya Wang

[paper] [code]

ICCV 2023

Knowledge-Aware Federated Active Learning with Non-IID Data, ICCV, 2023

Yu-Tong Cao, Ye Shi, Jingya Wang, Baosheng Yu, Dacheng Tao

[paper] [code]

IJCAI 2023

StackFLOW: Monocular Human-Object Reconstruction by Stacked Normalizing Flow with Offset, IJCAI, 2023

Chaofan Huo, Ye Shi, Yuexin Ma, Lan Xu, Jingyi Yu, Jingya Wang

[paper] [project] [code]

IEEE TNNLS 2023

FedTP: Federated Learning by Transformer Personalization, IEEE Transactions on Neural Networks and Learning Systems, 2023

Hongxia Li#, Zhongyi Cai#, Jingya Wang, Jiangnan Tang, Weipng Ding, Chin-Teng Lin, Ye Shi*

[paper] [code]

CVPR 2023

NeuralDome: A Neural Modeling Pipeline on Multi-View Human-Object Interactions, CVPR 2023

Juze Zhang, Haimin Luo, Hongdi Yang, Xinru Xu, Qianyang Wu, Ye Shi, Jingyi Yu, Lan Xu*, Jingya Wang*

[paper] [project] [video]

ICLR 2023

Alternating Differentiation for Optimization Layers, ICLR 2023

Haixiang Sun, Ye Shi*, Jingya Wang, Hoang Duong Tuan, H.V. Poor, Dacheng Tao

[paper] [code]

AAAI 2023 (oral)

IKOL: Inverse kinematics optimization layer for 3D human pose and shape estimation via Gauss-Newton differentiation, AAAI 2023 (oral)

Juze Zhang, Ye Shi*, Yuexin Ma, Lan Xu, Jingyi Yu, Jingya Wang*

[paper] [project] [code]

AAAI 2023 (oral)

Lifelong Person Re-Identification via Knowledge Refreshing and Consolidation, AAAI 2023 (oral)

Chunlin Yu, Ye Shi, Zimo Liu, Shenghua Gao, Jingya Wang*

[paper] [project] [code]

NeurIPS 2022 (Spotlight)

Unified Optimal Transport Framework for Universal Domain Adaptation, NeurIPS 2022 (Spotlight)

Wanxing Chang, Ye Shi*, Hoang Duong Tuan, Jingya Wang*

[paper] [project] [code] [video] [VALSE]

IEEE Transactions on Fuzzy Systems 2022

Federated Fuzzy Neural Networks with Evolutionary Rule Learning, IEEE Transactions on Fuzzy Systems, 2022

Leijie Zhang, Ye Shi*, Yu-Cheng Chang and Chin-Teng Lin*

[paper] [code]

ACM MM 2022

Mutual Adaptive Reasoning for Monocular 3D Multi-Person Pose Estimation, ACM MM 2022

Juze Zhang, Jingya Wang*, Ye Shi*, Lan Xu, Fei Gao, Jingyi Yu

[paper]

• Distributed Semi-supervised Fuzzy Regression with Interpolation Consistency Regularization, Ye Shi#, Leijie Zhang#, Zehong Cao, M. Tanveer and Chin-Teng Lin*, IEEE Transactions on Fuzzy Systems, 2022. [paper] [code]

• Distributionally Robust Optimization for Vehicle-to-grid with Uncertain Renewable Energy, Qi Li#, Pengchao Tian#, Ye Shi*, Yuanming Shi and Hoang Duong Tuan, ICCAIS 2022 (Oral). [paper]

• Distributed model predictive control for joint coordination of demand response and optimal power flow with renewables in smart grid, Ye Shi*, Hoang Duong Tuan, Andrey V. Savkin, Chin-Teng Lin, Jian Guo Zhu, H. Vincent Poor, Applied Energy, 2021. [paper]

• Hierarchical fuzzy neural networks with privacy preservation on heterogeneous big data, Leijie Zhang#, Ye Shi#*, Yu-Cheng Chang, and Chin-Teng Lin, IEEE Transactions on Fuzzy Systems, 2021. [paper] [code]

• PMU Placement Optimization for Efficient State Estimation in Smart Grid, Ye Shi, Hoang Duong Tuan*, Trung Q. Duong, H. Vincent Poor and Andrey V. Savkin, IEEE Journal on Selected Areas in Communications, 2020. [paper]

• Parameterized bilinear matrix inequality techniques for H ∞ gain-scheduling proportional integral derivative control design, Ye Shi, Hoang Duong Tuan* and Pierre Apkarian, International Journal of Robust and Nonlinear Control, 2020. [paper]

• Consensus learning for distributed fuzzy neural network in big data environment, Ye Shi*, Chin-Teng Lin, Yu-Cheng Chang, Weiping Ding, Yuhui Shi and Xin Yao, IEEE Transactions on Emerging Topics in Computational Intelligence, 2021. [paper]

• Deep- IRTarget: An Automatic Target Detector in Infrared Imagery using Dual-domain Feature Extraction and Allocation, Ruiheng Zhang, Lixin Xu, Zhengyu Yu, Ye Shi, Chengpo Mu, Min Xu*, IEEE Transactions on Multimedia, 2021. [paper]

• Interpretable Fuzzy Logic Control for Multi-Robot Coordination in a Cluttered Environment, Yu-Cheng Chang, Ye Shi, Anna Dostovalova, Zehong Cao, Chin-Teng Lin*, Daniel Gibbons, Jijoong Kim, IEEE Transactions on Fuzzy Systems, 2021. [paper]

• Mixed integer nonlinear programming for Joint Coordination of Plug-in Electrical Vehicles Charging and Smart Grid Operations, Ye Shi*, Hoang Duong Tuan, and Andrey V. Savkin, the 10th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, 2019. [paper]

• Model Predictive Control for Smart Grids with Multiple Electric-Vehicle Charging Stations, Ye Shi, Hoang Duong Tuan, Andrey V. Savkin, Trung Q. Duong* and H. Vincent Poor, IEEE Transaction on Smart Grid, 2019. [paper]

• Optimal Power Flow over Large-Scale Transmission Networks, Ye Shi, Hoang Duong Tuan*, Andrey V. Savkin, Steven W. Su, Systems & Control Letters, 2018. [paper]

• Nonconvex Spectral Optimization Algorithms for Reduced-Order H∞ LPV-LFT controllers, Ye Shi, Hoang Duong Tuan* and Pierre Apkarian, International Journal of Robust and Nonlinear Control, 2017. [paper]

• Global Optimization for Optimal Power Flow over Transmission Networks, Ye Shi, Hoang Duong Tuan* , Hoang Tuy and Steven W. Su, Journal of Global Optimization, 2017. [paper]

• Nonconvex Spectral Algorithm for Solving BMI on the Reduced Order H∞ Control, Ye Shi*, Hoang Duong Tuan, and Steven W. Su, accepted by the 6th IEEE International Conference on Control Systems, Computing and Engineering, 2016. (Best Paper Award) [paper]

• Nonsmooth Optimization for Optimal Power Flow over Transmission Networks, Ye Shi*, Hoang Duong Tuan, Steven W. Su and H. H. M. Tam, accepted by the 3rd IEEE Global Conference on Signal and Information Processing, 2015. [paper]

📖 Educations

• 2014.02 - 2018.11, Ph.D., University of Technology Sydney, NSW, Australia.
• 2009.09 - 2013.06, B.S., Northwestern Polytechnical University, Xi’an, China.

💻 Work Experience

• Tenure-track Assistant Professor (2021.01 -now): School of Information Science and Technology, ShanghaiTech University.
• Postdoctoral Fellow (2019.07-2020.12):
  • Australian Artificial Intelligence Institute, School of Computer Science, University of Technology Sydney.
  • Supervisor: Prof. Chin-Teng Lin (IEEE Fellow), E-mail: chin-teng.lin@uts.edu.au.
• Research Assistant (2017.03-2019.06):
  • School of Electrical Engineering and Telecommunications, Faculty of Engineering, University of New South Wales.
  • Supervisor: Prof. Andrey V. Savkin, E-mail: a.savkin@unsw.edu.au

🎖️ Awards

• 2024 My students received the NeurIPS 2023 Scholar Award.
• 2021 Best Student Paper Award (Corresponding author) at Australia Artificial Intelligence Institute.
• 2019 Outstanding Overseas Students Award, Chinese Ministry of Education, Australia. (A total of 500 people worldwide while only 50 people in Australia).
• 2018 FEIT PhD Post Thesis Publication Award, University of Technology Sydney 2018, Australia.
• 2017 Higher Degree Research Publication Award, University of Technology Sydney, Australia.
• 2016 Best Paper Award, the 6th IEEE International Conference on Control Systems, Computing and Engineering, Malaysia.
• 2016 ARC Discovery Scholarship, the University of Technology Sydney, 2014-2016, Australia.
• 2016 International Research Scholarships, University of Technology Sydney, 2014-2016, Australia.
• 2013 Meritorious Winner of the Interdisciplinary Contest in Modeling (ICM), The Society for Industrial and Applied Mathematics, America.
• 2012 First Prize of Chinese Undergraduate Mathematical Contest for Modeling (CUMCM), China Society for Industrial and Applied Mathematics, China.
• 2010 National Scholarship, Chinese Ministry of Education, China.

💬 Talks

• 2024.10, Controllable diffusion and optimization models for generation and decision in Embodied AI, RLChina 2024.
• 2024.04, Model-Data Hybrid-Driven Embodied Agents: Fundamentals and Applications, The 1st China Embodied AI Conference.
• 2023.11, Towards Responsible Decision and Control via Implicit Networks, RLChina 2023.
• 2019.10, Joint Coordination of Plug-in Electrical Vehicles Charging and Smart Grid Operations, IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, Beijing.
• 2018.04, Nonconvex and nonsmooth optimization in smart grids, International Forum for Interdisciplinary Sciences and Engineering Open Forum, Wuhan University.
• 2016.11, Nonconvex Spectral Algorithm for Solving BMI on the Reduced Order H∞ Control, IEEE International Conference on Control Systems, Computing and Engineering, Penang, Malaysia.

🕴️ Activities

• Session Chair The 10th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm 2019).
• Program committee
  • NeurIPS 2023, AAAI 2023, AAAI 2024, CVPR 2024, ICLR 2024, ICML 2024, NeurIPS 2024, AAAI 2025, ICLR 2025, etc.
• Reviewer
  • TNNLS, TIP, JSAC, TSG, TFS, TSE, TII, TIE, TIV, TIM, TMLR, IJRNC, etc.

🧑‍🏫 Teaching

• Course SI251 - Convex Optimization, ShanghaiTech University, 2021 Spring, 2021 Autumn, 2022 Autumn, 2024 Autumn.
• Course SI152 - Numerical Optimization, ShanghaiTech University, 2022 Spring, 2023 Spring, 2024 Spring.

🧑‍🎓 Group

• Ph.D. Students
  • Bikang Pan: B.E. at ShanghaiTech University.
  • Shutong Ding: B.E. at Fuzhou University.
  • Jiebao Zhang (jointly with Prof Haoyu Wang): M.S. at Yunnan University.
• Master Students
  • Xinru Xu: B.E. at ShanghaiTech University.
  • Tianyu Cui: B.S. at the University of Science and Technology of China.
  • Jiangnan Tang: B.E. at Beijing University of Posts and Telecommunications.
  • Lingxiao Yang: B.E. at Northeastern University.
  • Haoyu Yan: B.E. at Wuhan University of Technology.
  • Zichen Jin: B.E. at Northeastern University.
  • Siqi Yan: B.E. at ShanghaiTech University.
  • Ke Hu: B.E. at Harbin Engineering University.
  • Qun Li: B.E. at Harbin Engineering University.
  • Wentao Jiang: B.E. at China University of Mining and Technology.
  • Yahao Fan: B.E. at Zhengzhou University.
  • Zhenhao Zhang: B.E. at China University of Petroleum.
  • Kaizhen Zhu (jointly with Prof Jingya Wang): B.E. at Hangzhou Dianzi University.
• Visiting Students
  • Jun Xue: B.S. at Tongji University.
  • Fan Liu: M.S. at The University of Glasgow.
• Alumni
  • Haixiang Sun: M.S. at ShanghaiTech University. Pursuing PhD at Pudu University.
  • Pengchao Tian: M.S. at ShanghaiTech University. Working at Bilibili.
  • Hongxia Li: M.S. at ShanghaiTech University. Working at Trip.com Group.
  • Wanxing Chang (jointly with Jingya Wang): M.S. at ShanghaiTech University. Working at Alibaba DAMO Academy.
  • Zhongyi Cai (jointly with Jingya Wang): M.S. at ShanghaiTech University. Pursuing PhD at Michigan State University.
  • Qi Li: B.S. at ShanghaiTech University; Pursuing M.S. at Johns Hopkins University.