Zijie Huang (黄子倢)

I am a research scientist at Google Deepmind, working on Gemini pretraining, synthetic data for reasoning, etc. I received my Ph.D. in Computer Science at University of California, Los Angeles (UCLA), where I was fortunate to be advised by Prof.Yizhou Sun and Prof.Wei Wang. My research interest lies in generative AI, AI4Science in general, with a special focus on LLMs, dynamical system modeling, knowledge graph reasoning, and diffusion models. My Ph.D. research was generously supported by Amazon Ph.D. Fellowship. I was selected as EECS rising star 2023.

Before UCLA, I received my bachelor's degree of Electrical and Computer Engineering (ECE) from Shanghai Jiao Tong University (SJTU) in 2019. I love piano, badminton and traveling.

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News

  • Mar.2026: One survey paper accepted by ACM Computing Surveys.

  • Nov.2025: One paper accepted by KDD 2026 Research Track.

  • Sep.2025: Two papers accepted by NeurIPS 2025 main track. See you in San Diego!

  • Aug.2025: Invited talk -- Neural Dynamics for Science: The Symbiosis of Deep Graph Learning and Differential Equations [video recording].

  • Jun.2025: One paper accepted by TMLR 2025. Congrats to Fang!

  • May.2025: One paper accepted by ACL 2025 main track. Congrats to Derek and Yanna!

  • May.2025: Our tutorial on GraphODEs is accepted by KDD 2025. Huge thanks to all my collaborators!

  • May.2025: One paper accepted by ICML 2025 main track as a spotlight.

  • Jan.2025: One paper accepted by ICLR 2025 main track.

  • Dec.2024: One paper accepted by AAAI 2025. Congrats to Yanna!

  • Sep.2024: Two papers accepted by NeurIPS 2024 main track. One paper accepted by BHI.

  • Jun.2024: Passed my doctoral defense!

Education


Ph.D.           Sep. 2019 - June. 2024
                   University of California Los Angeles (UCLA), Los Angeles, CA, U.S.
                   Ph.D. in Computer Science 		Image

B.S.             Sep. 2015 - June. 2019
                   Shanghai Jiao Tong University (SJTU), Shanghai, China.
                   B.S. in Electrical and Computer Engineering
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Selected Honors & Awards


Selected Publications (Full Publications)

Self-Guided Diffusion Model for Accelerating Computational Fluid Dynamics
Zijie Huang*, Ruoyan Li*, Haixin Wang, Guancheng Wan, Yizhou Sun, Wei Wang
The Conference on Knowledge Discovery and Data Mining (KDD), 2026. [Paper]
MIRAI: Evaluating LLM Agents for Event Forecasting
Chenchen Ye*, Ziniu Hu*, Yihe Deng*, Zijie Huang, Mingyu Derek Ma, Yanqiao Zhu, Wei Wang
LAW workshop @ The Conference on Neural Information Processing Systems (LAW@NeurIPS), 2025. [Paper] [Code] [Project Page]
PersonaAgent: When Large Language Model Agents Meet Personalization at Test Time
Weizhi Zhang, Xinyang Zhang, Chenwei Zhang, Liangwei Yang, Jingbo Shang, Zhepei Wei, Henry Peng Zou, Zijie Huang, Zhengyang Wang, Yifan Gao, Xiaoman Pan, Lian Xiong, Jingguo Liu, Philip S. Yu, Xian Li
MTI-LLM workshop @ The Conference on Neural Information Processing Systems (MTI-LLM@NeurIPS), 2025. [Paper]
Inferring from Logits: Exploring Best Practices for Decoding-Free Generative Candidate Selection
Mingyu Derek Ma, Yanna Ding, Zijie Huang, Jianxi Gao, Yizhou Sun, Wei Wang
Annual Meeting of the Association for Computational Linguistics (ACL), 2025. | ENLSP-IV@NeurIPS, 2024. [Paper]
Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation
Yanna Ding, Zijie Huang, Xiao Shou, Yihang Guo, Yizhou Sun, Jianxi Gao
The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025. [Paper]
GraphVis: Boosting LLMs with Visual Knowledge Graph Integration
Yihe Deng, Chenchen Ye, Zijie Huang, Mingyu Derek Ma, Yiwen Kou, Wei Wang
The Conference on Neural Information Processing Systems (NeurIPS), 2024 [Paper] [Code] [Project Page]
Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling
Zijie Huang*, Wanjia Zhao*, Jingdong Gao, Ziniu Hu, Xiao Luo, Yadi Cao, Yuanzhou Chen, Yizhou Sun, Wei Wang
The Conference on Neural Information Processing Systems (NeurIPS), 2024. Best Paper Award at DLDE workshop at Neurips 2023. [Paper] [Code] [Project Page]
Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems
Zijie Huang*, Jeehyun Hwang*, Junkai Zhang*, Jinwoo Baik, Weitong Zhang, Quanquan Gu, Dominik Wodarz, Yizhou Sun, Wei Wang
The Web Conference (WWW), 2024 | The Symbiosis of Deep Learning and Differential Equations (DLDE) workshop at Neurips, 2023 [Paper]
Generalizing Graph ODE for Learning Complex System Dynamics across Environments
Zijie Huang, Yizhou Sun and Wei Wang
The Conference on Knowledge Discovery and Data Mining (KDD), 2023 [Paper]
Concept2Box: Joint Geometric Embeddings for Learning Two-View Knowledge Graphs
Zijie Huang, Daheng Wang, Binxuan Huang, Chenwei Zhang, Jingbo Shang, Yan Liang, Zhengyang Wang, Xian Li, Christos Faloutsos, Yizhou Sun and Wei Wang
Annual Meeting of the Association for Computational Linguistics (ACL-Findings), 2023 [Paper]
Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment
Zijie Huang, Zheng Li, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, Wei Wang
Annual Meeting of the Association for Computational Linguistics (ACL), 2022 [Paper][Code] [Slides]
Coupled Graph ODE for Learning Interacting System Dynamics
Zijie Huang, Yizhou Sun, Wei Wang
The Conference on Knowledge Discovery and Data Mining (KDD), 2021 [Paper][Code] [Slides]
Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations
Zijie Huang, Yizhou Sun, Wei Wang
The Conference on Neural Information Processing Systems (NeurIPS), 2020 [Paper] [Code] [Slides]

Professional Experiences

  • April.2024 -- Jul.2024, Nvidia , Santa Clara, CA
    Research Intern. Work on Nvidia physicsnemo.

  • Jun.2023 -- Sep.2023, Netflix Algorithm Engineer Team, Los Gatos, CA
    Machine Learning Intern. Work on large-scale KG for recommendation. [Paper]

  • Jun.2022 -- Sep.2022, Amazon Product Graph Team (PG), Seattle, WA
    Applied Scientist Intern. Work on geometric KG representation learning. [Paper]

  • Jun.2021 -- Sep.2021, Amazon Search (A9), Bay Area, CA
    Applied Scientist Intern. Work on multilingual KG representation learning. [Paper]

  • Jun.2018 -- Oct.2018, University of Illinois at Urbana-Champaign (UIUC) , Urbana, IL
    Reseach Intern. Work on recommender systems. [Paper]

Academic Services

  • PC member of KDD, SSL@WWW, AAAI

  • Journal/Conference Reviewer: ICML, TKDD, AAAI, KDD, ICDM, NeurIPS, CIKM, TOIS, JAIR, LOG, ICLR, SDM, WWW

Teaching

  • Teaching Assistant, Introduction to Data Mining, Wei Wang. UCLA, 2021 Spring

  • Teaching Assistant, Introduction to Computer Science I (C++), Bruce Huang. UCLA, 2021 Winter

  • Teaching Assistant, Introduction to Data Mining, Yizhou Sun. UCLA, 2020 Fall

Last update: Sep. 2025