About Me

I am Kaizheng Wang (王凯征), a Research Fellow at the College of Computing and Data Science, Nanyang Technological University, Singapore, working under the supervision of Prof. Siu Lun Chau.

I obtained my PhD from the Department of Computer Science at KU Leuven, Belgium, supervised by Prof. Hans Hallez and Prof. David Moens, and had the privilege of being closely advised by Prof. Fabio Cuzzolin. Prior to my PhD, I received a Bachelor's degree in Mechatronics Engineering from Zhejiang University, China, and a Master's degree in Automation Engineering from RWTH Aachen University, Germany.

My research centers on uncertainty representation and quantification in deep learning, with the overarching goal of building machine learning models that are robust, reliable, and trustworthy. Specifically, I focus on designing epistemic uncertainty-aware learning algorithms and embedding this uncertainty-aware intelligence into AI systems, frameworks, and real-world applications.

I am always happy to discuss research ideas or explore potential collaborations — please feel free to reach out!

News

• 2026.05.01: 🎉🎉 One paper was accepted by ICML and selected as a Spotlight (2.2% of 24,000 valid submissions).
• 2026.04.07: 🎉🎉 I am honored to receive the runner-up award for the 2026 BNVKI AI PhD Dissertation Award, which recognizes the previous year’s best AI theses from the Benelux.
• 2026.01.12: 🎉🎉 I officially started my journey as a research fellow at NTU.
• 2025.11.08: 🎉🎉 Our Credal Ensemble Distillation paper was accpeted by AAAI 2026.
• 2025.10.31: 🎉🎉 I successfully defended my PhD. I sincerely thank all the amazing people for their years of support, guidance, and encouragement.
• 2025.10.26: 🎉🎉 Our review paper was accpeted by TPAMI.
• 2025.02.11: 🎉🎉 Our Credal Wrapper paper was awarded Spotlight by ICLR 2025 (3.3% acceptance rate)
• 2025.01.22: 🎉🎉 Two papers were accpeted by ICLR 2025.

Selected Publications

• Learning Credal Ensembles via Distributionally Robust Optimization
  Kaizheng Wang, Ghifari Adam Faza, Fabio Cuzzolin, Siu Lun Chau, David Moens, Hans Hallez.
  The 43rd International Conference on Machine Learning (ICML), 2026. Spotlight.
• A Review of Uncertainty Representation and Quantification in Neural Networks
  Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026.
• Credal Ensemble Distillation for Uncertainty Quantification
  Kaizheng Wang, Fabio Cuzzolin, David Moens, Hans Hallez.
  The 40th Annual AAAI Conference on Artificial Intelligence (AAAI), 2026.
• Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
  Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez.
  The 13th International Conference on Learning Representations (ICLR), 2025. Spotlight.
• CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
  Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez.
  Neural Networks (NN), 2025.
• Credal Deep Ensembles for Uncertainty Quantification
  Kaizheng Wang, Fabio Cuzzolin, Shireen Kudukkil Manchingal, Keivan Shariatmadar, David Moens, Hans Hallez.
  The 38th Annual Conference on Neural Information Processing Systems (NeurIPS), 2024.

Educations

PhD in Engineering Technology
KU Leuven, Belgium
2021.11 - 2025.10

MSc in Automation Engineering
RWTH Aachen University, Germany
2018.04 - 2020.10

BEng in Mechatronics Engineering
Zhejiang University, China
2013.09 - 2017.06

Awards

• ICML Spotlight Paper Award, 2026
• BNVKI AI PhD Dissertation Award (Runner-up), Benelux Association for Artificial Intelligence, 2026
• ICML Silver Reviewer Award, 2026
• IJCAI-ECAI Bronze Tier Reviewer Distinction, 2026
• ICLR Spotlight Paper Award, 2025
• Doctoral Scholarship, KU Leuven, 2021-2025
• Graduate with Honors out of Graduates of Zhejiang Provincial Institutions of Higher Learning, 2017
• Outstanding Graduates of Zhejiang University, 2017
• First-Class Scholarship for Outstanding Student, Zhejiang University, 2016

Services

• Workshop Organization: Co-organizer of E-pi UAI 2023
• Conference Reviewer: NeurIPS; ICLR; ICML; AAAI; IJCAI; UAI; AISTATS
• Journal Reviewer: IEEE TNNLS; TMLR; IEEE OJCS
• Teaching Assistant: AI in Embedded Systems [B-KUL-B3076T], KU Leuven, Spring 2023-2025
• Master Thesis Supervision: T. Demeulenaere and S. Francq (2022-2023); L. De Jonckheere (2022-2023); A. Beigrezaei (2023-2024)