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, where I was advised by Prof. Hans Hallez and Prof. David Moens. I have also had the privilege of working closely with Prof. Fabio Cuzzolin, from whom I have also received invaluable guidance.

My current research centers on uncertainty representation and quantification in deep learning, aiming to enhance the robustness, reliability, and trustworthiness of machine learning models. If you have any questions about my research or would like to collaborate with me, please feel free to reach out to me.

News

• 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 on Deep Credal Neural Networks for Uncertainty Quantification. 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.

Publications

• 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.

• Enhancing the Dependability of Autonomous Surface Vehicles through Robustness Benchmarking of Real-time Object Detection Models
  Yunjia Wang, Zihao Zhang, Kaizheng Wang, Holger Caesar, Jeroen Boydens, Davy Pissoort, Mathias Verbeke.
  Expert Systems with Applications (ESWA), 2026.
• Random-Set Neural Networks
  Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin.
  The 13th International Conference on Learning Representations (ICLR), 2025.
• A Unified Evaluation Framework for Epistemic Predictions
  Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Fabio Cuzzolin.
  AISTATS (AISTATS), 2025.
• Robust State and Protection-Level Estimation within Tightly Coupled GNSS/INS Navigation System
  Shuchen Liu, Kaizheng Wang, Dirk Abel.
  GPS Solutions (GPS Solut), 2023.

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

Services

• Workshop Organization: Co-organizer of E-pi UAI 2023
• Conference Reviewer: NeurIPS; ICLR; ICML; AAAI; IJCAI; AISTATS
• Journal Reviewer: IEEE TNNLS; TMLR; IEEE SPL; 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)