About

I am now a Research Assistant Professor in the Department of Computer Science at City University of Hong Kong, advised by Prof. Xiaohua Jia. I have a broad research interest in the area of zero-knowledge proofs, privacy-preserving approaches, and trustworthy AI. I obtained my Bachelor’s Degree in 2018 and Doctor’s Degree in 2024 from the School of Artificial Intelligence of Beijing Normal University. Prior to the RAP in CityU, I was a Postdoc Research Fellow in the Lab for AI-Powered FINTECH in Hong Kong.

Education Background

• Beijing Normal University (09/2020-07/2024)
  • Ph.D., recommended;
  • Research Area: Zero-knowledge proofs
• Virginia Tech (2021.09-2024.07)
  • Visiting PhD student
• Beijing Normal University (09/2018-08/2020)
  • Master of Computer Science, recommended;
  • Research Area: Deep learning and computer vision;
• Beijing Normal University (09/2014-08/2018)
  • Bachelor of Science in Computer Science, School of Artificial Intelligence;

News

• Our paper “Zero-Knowledge AI Inference with High Precision” has been accepted by Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security (CCS’25). Thanks to all the co-authors for the great work!
• I have two papers accepted by the 34th Conference on Information and Knowledge Management (CIKM’25)!
• Our paper “Accelerating Zero-Shot NAS With Feature Map-Based Proxy and Operation Scoring Function” has been accepted by TPAMI! 12/07/25
• I will work as a Research Assistant Professor at CityU starting from 2025.08!
• Our paper “An Efficient and Zero-Knowledge Classical Machine Learning Inference Pipeline” has been accepted by TDSC! 06/17/24
• I have graduated from Beijing Normal University and got my Ph.D. degree! 05/29/24

Publications (A full list can be found on my Google Scholar.)

[1] Haodi Wang, Tangyu Jiang, Yu Guo, Fangda Guo, Rongfang Bie, Xiaohua Jia. Label Noise Correction for Federated Learning: A Secure, Efficient and Reliable Realization. 40th IEEE International Conference on Data Engineering (ICDE’24). 2024.

[2] Tangyu Jiang, Haodi Wang, Rongfang Bie. MeCo: Zero-Shot NAS with One Data and Single Forward Pass via Minimum Eigenvalue of Correlation, Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS’23). 2023. (Spotlight paper, Co-first author).

[3] Haodi Wang, Thang Hoang. ezDPS: An Efficient and Zero-Knowledge Machine Learning Inference Pipeline[J]. Proceedings on Privacy Enhancing Technologies (PETS’23), 2023, 2: 430-448.

[4] Haodi Wang, Yu Guo, Rongfang Bie, Xiaohua Jia. Verifiable Arbitrary Queries with Zero Knowledge Confidentiality in Decentralized Storage. IEEE Transactions on Forensics and Security (TIFS). 2024(19): 1071-1085.

[5] Haodi Wang, Rongfang Bie, Thang Hoang. An Efficient and Zero-Knowledge Classical Machine Learning Inference Pipeline. IEEE Transactions on Dependable and Secure Computing (TDSC). 2024.03. (Accepted)

[6] Wang H., Jiao L., Bie R., Wu H. Semantic Inpainting with Multi-dimensional Adversarial Network and Wasserstein Distance. In: Peng Y. et al. (eds) Pattern Recognition and Computer Vision. PRCV 2020. Lecture Notes in Computer Science, vol 12307. 2020. Springer, Cham. \url{https://doi.org/10.1007/978-3-030-60636-7_7}.

[7] Ming He, Haodi Wang, Yunchuan Sun, Rongfang Bie, Tian Lan, Qi Song, Xi Zeng, Matevz Pustisek, Zhenyu Qiu. $T^2L$: Traceable and Trustable Consortium Blockchain for Logistics Based on Authenticated Data Source and ZK-Proof of Retrievability. Digital Communication and Networks. 2022. (Corresponding author).

[8] Haodi Wang, Libin Jiao, Hao Wu, Rongfang Bie. New Inpainting Algorithm Based on Simplified Context Encoders and Multi-Scale Adversarial Network[A]. 2018 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2018[C].Elsevier B.V.，2018:254-263

[9] Yu Guo, Yuxin Xi, Haodi Wang, Mingyue Wang, Cong Wang, Xiaohua Jia. FedEDB: Building a Federated and Encrypted Data Store via Consortium Blockchains. Transactions on Knowledge and Data Engineering. 2023.

[10] Yun Li, Cun Ye, Yuguang Hu, Ivring Morpheus, Yu Guo, Chao Zhang, Yupeng Zhang, Zhipeng Sun, Yiwen Lu, and Haodi Wang. 2021. ZKCPlus: Optimized Fair-exchange Protocol Supporting Practical and Flexible Data Exchange. In Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security (ACM CCS’21). Association for Computing Machinery, New York, NY, USA, 3002–3021. DOI: https://doi.org/10.1145/3460120.3484558.

[11] Libin Jiao, Hao Wu, Haodi Wang, Rongfang Bie. Multi-scale semantic image inpainting with residual learning and GAN[J]. Neurocomputing，2019，331(9252312):199-212

Teaching Experience

• Lecturer, City University of Hong Kong, CS2115 Computer Organization
• TA, Beijing Normal University, Principle of Database System (2019 Fall, 2020 Fall)
• TA, Beijing Normal University, Deep Learning (2018 Fall)

Honor & Awards

• The First prize of the scholarship for New Graduate Students of Beijing Normal University, 2018;
• The First prize of Academic Scholarship for Graduate Students of Beijing Normal University, 2019, 2020, 2021, and 2022.
• The Outstanding student cadres of Beijing Normal University, 2019;
• Merit Student and Outstanding Members of Beijing Normal University.

International Experience

• University of California, Berkeley (Summer School 07/2018-08/2018)
  • Course: The person in big data, 93.48 out of 100;
  • Course: Academic writing, 95.49 out of 100.
• Virginia Tech, Blacksburg (Visiting Ph.D. 01/2020-12/2023)
  • Advisor: Prof. Thang Hoang
  • Research interest: Zero-knowledge proof in ML/DL