PeopleofSuperintelligence

Researcher

Kun Wang

Kun Wang is an AI researcher whose work spans graph learning and language-model knowledge editing. In 2022, he coauthored the A2DJP framework for predicting urban anomalies, and in 2024 he studied as a PhD student at the University of Science and Technology of China while coauthoring the EXGC and Heterophilic Snowflake Hypothesis papers on graph neural networks. His October 2024 paper AlphaEdit projected parameter updates onto the null space of preserved knowledge to edit language models, earning an ICLR Outstanding Paper Award in April 2025. In November 2025, he coauthored the KGMET framework to guide language-model memory edits with knowledge graphs. Since 2024, he is a postdoctoral researcher at Nanyang Technological University.

Timeline

  1. 2022

    A2DJP for urban anomaly prediction

    In 2022, he coauthors A2DJP, a graph-based learning framework in IEEE Transactions on Knowledge and Data Engineering for jointly predicting urban anomaly distribution and duration.

  2. February 2024

    EXGC for graph condensation

    He coauthors EXGC in February 2024, pairing a mean-field variational approximation for faster convergence with a gradient information bottleneck to prune redundancy in graph condensation.

  3. June 2024

    The Heterophilic Snowflake Hypothesis

    As first author of The Heterophilic Snowflake Hypothesis in June 2024, he constructs a proxy label predictor so connected nodes can decide whether to aggregate their neighbors.

  4. 2024

    A PhD student at USTC

    During the summer of 2024, he is a PhD student at the University of Science and Technology of China (USTC) and works as an intern.

  5. October 2024

    AlphaEdit for knowledge editing

    With coauthors in October 2024, he introduces AlphaEdit, which projects perturbations onto the null space of preserved knowledge before applying updates to language-model parameters.

  6. April 2025

    An ICLR Outstanding Paper

    ICLR gives AlphaEdit an Outstanding Paper Award in April 2025.

  7. November 2025

    Knowledge-graph memory editing

    In November 2025, he coauthors Knowledge Graph-Driven Memory Editing with Directional Interventions, introducing the KGMET framework to guide language-model knowledge editing with knowledge graphs.

  8. Since 2024

    Postdoctoral work at NTU

    He joins Nanyang Technological University as a postdoctoral researcher in 2024.

Career

  1. Since 2024Nanyang Technological UniversityPostdoctoral researcher

Education

  1. University of Science and Technology of ChinaPhD

From the biography.

  1. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Nanyang Technological University. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Nanyang Technological University. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. Google has the highest combined h-index among AI organizationsIncludes Nanyang Technological University. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  4. 5 of the 25 people with the most-cited recent papers also lead on career citationsIncludes Nanyang Technological University. We compare citations to 2023–2025 papers with career citations and h-index, after correcting reviewed publication-date errors: who leads, when they started and where they work.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Kun Wang yet. Send us a free-licensed photo.

  1. 中国科学技术大学 wangyang--Home--Scientific Research faculty.ustc.edu.cn. Checked 22 October 2026.
  2. EXGC: Bridging Efficiency and Explainability in Graph Condensation arxiv.org. Checked 22 October 2026.
  3. The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs arxiv.org. Checked 22 October 2026.
  4. Qingsong Wen's Education and Experience sites.google.com. Checked 22 October 2026.
  5. AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models arxiv.org. Checked 22 October 2026.
  6. Announcing the Outstanding Paper Awards at ICLR 2025 blog.iclr.cc. Checked 22 October 2026.
  7. Xiangnan He's Homepage hexiangnan.github.io. Checked 22 October 2026.
  8. Knowledge Graph-Driven Memory Editing with Directional Interventions - ACL Anthology aclanthology.org. Checked 22 October 2026.
  9. Kun Wang - Lacuna lacuna.tiptreesystems.com. Checked 22 October 2026.
  10. SnowCat - Minghui Pan panmingh.com. Checked 22 October 2026.