Zijie Huang (黄子倢)

I am a research scientist at Google Deepmind, working on Gemini. 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 Information Engineering from Shanghai Jiao Tong University (SJTU). I love piano, badminton and traveling.

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News

  • 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. Congrats to Guancheng!

  • 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!

  • May.2024: One paper accepted by ACL 2024.

  • Feb.2024: One paper accepted by WWW 2024.

Professional Experiences

  • Aug.2024 -- May.2025, Amazon , Palo Alto, CA
    Applied Scientist. Work on LLM for Shopping.

  • 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]

Selected Honors & Awards


Selected Publications (Full Publications)

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]
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks
Zewen Liu, Xiaoda Wang, Bohan Wang, Zijie Huang, Carl Yang, Wei Jin
The Conference on Knowledge Discovery and Data Mining (KDD Tutorial), 2025 [Paper]
Rethink GraphODE Generalization within Coupled Dynamical System
Guancheng Wan, Zijie Huang, Wanjia Zhao, Xiao Luo, Yizhou Sun, Wei Wang
International Conference on Machine Learning (ICML), 2025. Spotlight [Paper]
Accelerating Neural ODEs: A Variational Formulation-based Approach
Hongjue Zhao, Yuchen Wang, Hairong Qi, Zijie Huang, Han Zhao, Lui Sha, Huajie Shao
The Thirteenth International Conference on Learning Representations (ICLR), 2025. [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]
DoMiNO: Down-scaling Molecular Dynamics with Neural Graph Ordinary Differential Equations
Fang Sun, Zijie Huang, Yadi Cao, Xiao Luo, Wei Wang, Yizhou Sun
MLMP workshop @ The Thirteenth International Conference on Learning Representations (MLMP@ICLR), 2025. Oral [Paper]
FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation
Haixin Wang, Ruoyan Li, Fred Xu, Fang Sun, Kaiqiao Han, Zijie Huang, Guancheng Wan, Ching Chang, Xiao Luo, Wei Wang, Yizhou Sun
arxiv, 2025. [Paper]
From Coarse to Fine: A Physics-Informed Self-Guided Flow Diffusion Model
Ruoyan Li*, Zijie Huang*, Yizhou Sun, Wei Wang
arxiv, 2025. [Paper]
A Social Dynamical System for Twitter Analysis
Zhiping Xiao, Xinyu Wang, Yifang Qin, Zijie Huang, Mason A. Porter, Yizhou Sun
arxiv, 2025. [Paper]
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]
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]
FUSE: Measure-Theoretic Compact Fuzzy Set Representation for Taxonomy Expansion
Fred Xu, Song Jiang, Zijie Huang, Xiao Luo, Shichang Zhang, Yuanzhou Chen, Yizhou Sun
Annual Meeting of the Association for Computational Linguistics (ACL-Findings), 2024 [Paper]
BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations
Kaiqiao Han, Yi Yang, Zijie Huang, Xuan Kan, Ying Guo, Yang Yang, Lifang He, Liang Zhan, Yizhou Sun, Wei Wang, Carl Yang
IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2024 [Paper]
Predicting Time Series of Networked Dynamical Systems without Knowing Topology
Yanna Ding, Zijie Huang, Malik Magdon-Ismail, Jianxi Gao
preprint, 2024. [Paper]
MIRAI: Evaluating LLM Agents for Event Forecasting
Chenchen Ye*, Ziniu Hu*, Yihe Deng*, Zijie Huang, Mingyu Derek Ma, Yanqiao Zhu, Wei Wang
arxiv, 2024 [Paper] [Code] [Project Page]
Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey
Haixin Wang, Yadi Cao, Zijie Huang, Yuxuan Liu, Peiyan Hu, Xiao Luo, Zezheng Song, Wanjia Zhao, Jilin Liu, Jinan Sun† , Shikun Zhang, Long Wei, Yue Wang, Tailin Wu, Zhi-Ming Ma, Yizhou Sun
arxiv, 2024 [Paper] [Code]
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]
CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems
Song Jiang,Zijie Huang, Xiao Luo and Yizhou Sun
The Conference on Knowledge Discovery and Data Mining (KDD), 2023 [Paper]
HOPE: High-order Graph ODE For Modeling Interacting Dynamics
Xiao Luo, Jingyang Yuan, Zijie Huang, Huiyu Jiang, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun
International Conference on Machine Learning (ICML), 2023 [Paper]
CARE: Modeling Interacting Dynamics Under Temporal Distribution Shift
Xiao Luo, Haixin Wang, Zijie Huang, Huiyu Jiang, Abhijeet Sadashiv Gangan, Song Jiang, Yizhou Sun
The Conference on Neural Information Processing Systems (NeurIPS), 2023 [Paper]
Watching to Simulate Glass Dynamics from Their Static Structure by Machine Learning
Han Liu, Zijie Huang, Samuel S. Schoenholz, Ekin D. Cubuk, Morten M. Smedskjaer, Yizhou Sun, Wei Wang and Mathieu Bauchy
Materials Horizons, 2023 [Paper]
Synergistic Signals: Exploiting Co-Engagement and Semantic Links via Graph Neural Networks
Zijie Huang, Baolin Li, Hafez Asgharzadeh, Anne Cocos, Lingyi Liu, Evan Cox, Colby Wise, Sudarshan Lamkhede
arxiv, 2023 [Paper]
A Survey on Graph Neural Network Acceleration: Algorithms,Systems, and Customized Hardware
Shichang Zhang, Atefeh Sohrabizadeh, Cheng Wan, Zijie Huang, Ziniu Hu, Yewen Wang, Yingyan (Celine) Lin, Jason Cong, Yizhou Sun
arxiv, 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]
DyDiff-VAE: A Dynamic Variational Framework for Information Diffusion Prediction
Ruijie Wang, Zijie Huang, Shengzhong Liu, Huajie Shao, Dongxin Liu, Jinyang Li, Tianshi Wang, Dachun Sun,Shuochao Yao, Tarek Abdelzaher
The International ACM SIGIR Conference on Research and Developmentin Information Retrieval (SIGIR), 2021 [Paper]
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]
Weakly Supervised Attention for Hashtag Recommendation using Graph Data
Amin Javari, Zhankui He, Zijie Huang, Raj Jeetu, Kevin Chen-Chuan Chang
The Web Conference (WWW) , 2020 [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: May. 2025