Ziwen Wang(王子文)

Ziwen Wang(王子文)

A proactive and ambitious Ph.D. student at Anhui University who is unwilling to settle for mediocrity.

About Me

I am a Ph.D. student majoring in computer science at Anhui University, China. I am honored to be a member of the BIMK (Institute of Bio-inspired Intelligence and Mining Knowledge). My research focuses primarily on the areas of intelligent education, recommender systems and evolutionary computation. More relevant information can be found on our homepage. Intelligent education encompasses cutting-edge research areas such as cognitive diagnosis(CD), knowledge tracing(KT), computerized adaptive testing(CAT), and learning path recommendation(LPR) involving various deep learning technologies. More information can be found in our research papers. If you are interested in collaboration or discussion, please feel free to contact me via email or WeChat. We look forward to our dialogue and mutual learning, creating new opportunities for collaboration, just as determined individuals can achieve remarkable things.

📖 Educations and Experiences

  • Ph.D.: Sep. 2020 - Present, Computer Science and Technology, Anhui University
  • B.S.: Sep. 2016 - Jun. 2020, Information and Computing Science, Anhui University

💻 Research Interest

  1. Trustworthy Intelligent Education
    • Generalized CD & KT (Fairness)
    • Interpretable CD & KT (Interpretability)
    • Federated CD & KT (Privacy)
    • Robust CD & KT (Robustness)
  2. Automated X
    • Neural Architecture Search
    • Automatic Algorithm Design
    • Symbolic Regression
  3. Evolutionary Multi-objective Optimization for 1️⃣ & 2️⃣

🏆 Honors and Awards

  • 2025.12 Natural Science Research Project of Anhui Educational Committee, Doctoral Research Project.
  • 2021 to 2025 First Class Award Scholarship of the Graduate.
  • 2019.4 Meritorious Winner, Mathematical Contest in Modeling / Interdisciplinary Contest in Modeling (MCM/ICM).

🧑‍🎨 Reviewers

  • Journals: TIST, TLT.
  • Conferences: NeurIPS, SIGKDD, ICLR, ICML, SIGIR, AAAI, ACM MM, IJCAI.

🔥 News

  • 2026.05:  🎉🎉 Our work “Beyond Item Selection: Rethinking Ability Evolution in Computerized Adaptive Testing” has been accepted by KDD 2026 (Research Track). [Paper]
  • 2026.03:  🎉🎉 Our work “Large Language Model-assisted Evolutionary Neural Architecture Search for Cognitive Diagnosis” has been accepted by IEEE TETCI. [Paper]
  • 2025.12:  🎉🎉 Our work “Reconciling Cognitive Modeling with Knowledge Forgetting: A Continuous Time-aware General Neural Network Framework” has been accepted by ACM TIST. [Paper]
  • 2025.11:  🎉🎉 Our work “Breaking Robustness Barriers in Cognitive Diagnosis: A One-Shot Neural Architecture Search Perspective” has been accepted by KDD 2026 (Research Track). [Paper]
  • 2025.11:  🎉🎉 Our work “PEOAT: Personalization-Guided Evolutionary Question Assembly for One-Shot Adaptive Testing” has been accepted by AAAI 2026 (Research Track). [Paper]
  • 2025.11:  🎉🎉 Our work “Debiased Cognitive Diagnosis: A Contrastive Counterfactual Modeling Method via Variational Autoencoder” has been accepted by AAAI 2026 (Oral). [Paper]
  • 2025.04:  🎉🎉 Our work “Endowing Interpretability for Neural Cognitive Diagnosis by Efficient Kolmogorov-Arnold Networks” has been accepted by IJCAI 2025. [Paper]
  • 2024.09.26:  🎉🎉 Our work “DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis” has been accepted by NeurIPS 2024. [Paper]
  • 2024.09.01:  🎉🎉 Our group won the Golden Award of the 2022 Anhui College Students’ ‘Internet+’ Innovation and Entrepreneurship Competition (GAOJIAO Main Track), supervised by Ye Tian and Xingyi Zhang.

📝 Publications