Zijie Huang (黄子倢)

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, machine learning in general, with a special focus on dynamical system modeling, knowledge graph reasoning, LLMs 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.

Email  /  linkedin  /  Github  /  Google Scholar

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News

  • 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.

Intern Experience

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

  • Jun 2023 -- Sep 2023, Netflix Algorithm Engineer Team, Los Gatos, CA
    Machine Learning Intern

  • Jun 2022 -- Sep 2022, Amazon Product Graph Team (PG), Seattle, WA
    Applied Scientist Intern

  • Jun 2021 -- Sep 2021, Amazon Search (A9), Bay Area, CA
    Applied Scientist Intern

  • Jun.2018 -- Oct.2018, University of Illinois at Urbana-Champaign (UIUC) , Urbana, IL
    Reseach Intern

Selected Publications (Full Publications)

From Coarse to Fine: A Physics-Informed Self-Guided Flow Diffusion Model
Ruoyan Li*, Zijie Huang*, Yizhou Sun, Wei Wang
arxiv, 2025. [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
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]
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]
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
ENLSP-IV@The Conference on Neural Information Processing Systems (NeurIPS), 2024. [Paper]
Predicting Time Series of Networked Dynamical Systems without Knowing Topology
Yanna Ding, Zijie Huang, Malik Magdon-Ismail, Jianxi Gao
preprint, 2024. [Paper]
Graph Fourier Neural ODEs: Bridging Spatial and Temporal Multiscales in Molecular Dynamics
Fang Sun, Zijie Huang, Haixin Wang, Yadi Cao, Xiao Luo, Wei Wang, Yizhou Sun
preprint, 2024. [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]
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]
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]
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]
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]
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]
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]
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]

Selected Honors & Awards

  • EECS Rising Star, 2023.

  • KDD Student Traval Award, 2023

  • ICML Student Travel Award, 2023

  • Amazon & UCLA Science Hub Fellowship, 2022.

  • NeurIPS Student Travel Award, 2020.

  • National Scholarship, 2017.

  • Outstanding Graduate of Shanghai Jiao Tong University, 2019.

  • Chunstung Scholarship, 2018.

  • Yongling Liu Scholarship, 2018.

  • Meritorious Winner, Mathematics Contest in Modeling, 2017.

  • Academic Excellence Scholarship of SJTU, 2016,2017,2018.


Academic Services

  • PC member of KDD2020, SSL@WWW2021, AAAI2022, AAAI2023, KDD2023, AAAI2024

  • Journal/Conference Reviewer: TKDD 2020, AAAI 2021, KDD2021, ICDM2021, KDD2022, TKDD 2023, Neurips 2023, CIKM2023, TOIS2023, JAIR2023, LOG2024, ICLR2024, SDM2024, WWW2024

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: Jan. 2025