Yuxiao Dong @ericdongyx
Associate Professor
Computer Science, Tsinghua
Publications | Students | Talks | Services | Contact | Top
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Yuxiao is an Associate Professor of Computer Science at Tsinghua University. His research focuses on large language models, data mining, graph machine learning, and social networks. Together with collaborators, his recent work on LLM/VLM pre-training and agentic RL has been transferred into several open-sourced LLMs and products. Earlier in his career, his work on graph representation learning and pre-training was deployed for large-scale applications in Facebook, Microsoft, Tencent, and nominated for best papers in WWW'22, WWW'19, ECML-PKDD'23, and WSDM'15. He received his Ph.D. in Computer Science from University of Notre Dame, and before joining Tsinghua, he was a researcher at Meta AI and Microsoft Research Redmond. He has been very fortunate to receive the 2017 SIGKDD Dissertation Award Honorable Mention and the 2022 SIGKDD Rising Star Award. He is also very proud to be selected as one of the ten most favorite teachers in 2024 --- a recognition voted on by students once every two years.

Here are some of recent works on LLMs:

  1. agentic RL: Single-Rollout Asynchronous Optimization (SAO), CompactionRL, AgentRL, DeepDive, MobileRL, WebRL, T1 for RL Scaling, TreeRL, SWE-Dev, AndroidLab, AgentBench, AgentTuning
  2. rlhf/alignment: VisionReward, ImageReward, Scaling RLHF
  3. pre-training: Emergent Abilities vs. Loss, CogVLM, Speech-Text Pre-training, CogView3, CodeGeeX

Here are recent works on Graph Pre-Training & Graph Representation Learning, some of which were used in Facebook, Instagram, Microsoft, Tencent Games, and Alibaba:

  1. graph pre-training: GraphAlign, GraphMAE, GraphMAE2, GPT-GNN, GCC
  2. network embedding: NetMF, NetSMF, ProNE, SketchNE
  3. heterogeneous graphs: metapath2vec, Heterogeneous Graph Transformer (HGT)

More information about his experience and research can be found on LinkedIn and Google Scholar.

Students & Interns

I'm always looking for self-motivated students to work on large language models, vision language models, LLM agent, and graphs, networks. It would be great if your institutional email address is used for initial contact, if having one. Reference letters for applying for graduate schools (of at most ten universities) can be happily provided upon 1) solid outputs AND 2) at least 16 weeks of collaboration (the duration of both one semester at Tsinghua and a MSR/Facebook summer research internship).

I'm very lucky to have the opportunities to work with these brilliant students and interns (ordered by year, with their representative work done together).

  1. PhD students:
    1. Haoran Wang, Hanchen Zhang, Zhiyuan Liao, PhD 2026-
    1. Yi Jing, Master 2026-
    1. Rui Lu, Yujiang Li, Bowen Lv, PhD 2025-
    1. Mingdao Liu, PhD 2024-
    1. Yifan Xu, Xiao Xia, PhD 2023-
    1. Jiazheng Xu, PhD 2022-: ImageReward (NeurIPS'23, ImageReward PyPI downloads ), won the 2025 ByteDance PhD Fellowship (20 in China + Singapore) and the 2025 Tencent Project Up Scholarship (腾讯青云)
    1. Zhenyu Hou, PhD 2021-: Single-Rollout Asynchronous Optimization (SAO), GraphMAE (most cited in KDD'22), T1: LLM RL & Test-Time Scaling (ICML'25), won the 2025 Ant PhD Fellowship (ten globally)
  2. 2021-, Undergraduate students:
    1. Haoran Wang (PhD@Tsinghua 2026-) | Hanchen Zhang (PhD@Tsinghua 2026-) | Zhiyuan Liao (PhD@Tsinghua 2026-) | Yu Huang (PhD@Tsinghua 2026-) | Yuhang Wu (PhD@Tsinghua 2026-) | Xueqiao Sun (PhD@CMU 2026-) | Bowen Wang (vLLM 2026-) | Wenbo Duan (Master@SJTU 2026-)
    2. Yujiang Li (PhD@Tsinghua 2025-) | Rui Lu (PhD@Tsinghua 2025-) | Zhilei Bei (PhD@MIT 2025-) | Heyang Jiang (PhD@UCLA 2025-) | Yuxuan Tong (ByteDance Seed 2025-) | Tianjie Zhang (Master@CMU 2025-)
    3. Mingdao Liu (PhD@Tsinghua 2024-) | Guanghan Wang (PhD@Cornell 2024-) | Yifan An (Z.AI 2024-)
    4. Xiao Xia (PhD@Tsinghua 2023-) | Shiyu Zhao (Master@Stanford 2023-) | Weikai Li (PhD@UCLA 2023-) | Ziang Li (PhD@GaTech 2023-)
  3. 2020, summer interns@MSR Redmond:
    1. Namyong Park, 3rd year Ph.D. student at CMU | Scott Freitas (co-mentor), 3rd year Ph.D. student at Georgia Tech | Yu Zhang (co-mentor), 3rd year Ph.D. student at UIUC: 2025 SIGKDD Dissertation Award Runner-Up
  4. 2019, summer intern@MSR Redmond:
    1. Ziniu Hu, 1st year Ph.D. student at UCLA: Heterogeneous Graph Transformer (HGT) (most cited in WWW'20), GPT-GNN (KDD'20), won the 2024 SIGKDD Dissertation Award Runner-Up
  5. 2017, summer intern@MSR Redmond:
    1. Jiezhong Qiu, 1st year Ph.D. student at Tsinghua: NetMF (2nd most cited in WSDM'18), NetSMF (best paper candidate in WWW'19), won the 2022 SIGKDD Dissertation Award Runner-Up

Publications

=== please see Google Scholar in a chronological list. ===

Teaching & Tutorials

  1. 2024--, Advanced Artificial Intelligence (Graduate) --- with Prof. Yang Liu, CS, Tsinghua
  2. 2023--, Numerical Analysis (Undergraduate), CS, Tsinghua
  3. 2023--, Programming (Undergraduate), CS, Tsinghua
  4. 2023/2024, Guest Lecture, LLMs, Tsinghua EMBA
  5. 2023, Guest Lecture, LLMs, Peking EMBA
  6. 2022/2023, Guest Lecture, Data Mining, CS, Tsinghua
  7. 2020, Guest Lecture, Knowledge Graph, Computer Science Department, Stanford University
  8. 2020/2021/2022, Guest Lecture, Advanced Machine Learning, Computer Science Department, Tsinghua University
  9. 2023, Tutorial, Graph Representation and Pre-Training, WWW'23
  10. 2020, Tutorial (Invited), Graph Representation Learning, ECML/PKDD'20 slides
  11. 2019, Tutorial, Representation Learning on Networks (full day), WWW'19 slides
  12. 2019, Tutorial, Learning from Networks (full day), KDD'19 slides
  13. 2018, Tutorial, Computational Models for Social and Information Network Analysis, KDD'18 slides

Invited Talks

  1. 2024: Invited talk at Stanford, CA
  2. 2024: Invited talk at Nanjing U.
  3. 2023: Invited talk at Caltech, CA
  4. 2023: Keynote at IJCAI'23 LLM Symposium
  5. 2023: Invited Talk at KDD China Summit 2023: Graph Pre-Training: From GPT-GNN to GraphMAE to GCC
  6. 2022: IJCAI Early Career Spotlight Invited Talk
  7. 2019: Invited Talk at INFORMS'19 Informs Annual Meeting: Representation Learning on Networks
  8. 2019: Microsoft Security and Compliance AI Summit
  9. 2019: AI and Tensor Conference at Los Alomos National Lab
  10. 2019: Invited Talk at NetSci'19 Satellite on Quantifying Success
  11. 2019: Invited Talk at NetSci'19 Satellite on Network Representation Learning
  12. 2018: Invited Talk at NetSci'18 Higher-Order Models in Network Science Satellite (HONS'18)
  13. 2018: Invited Talk at NICO, Northwestern University, IL
  14. 2017: Invited Talk at Labs in Tsinghua University
  15. 2016: Keynote at ACM JCDL'16 Workshop on Mining Scientific Publications (WOSP'16)
  16. 2016: Invited Talks at Labs in Stanford University / Tsinghua University / Chinese Academy of Sciences (CAS)
  17. 2015: Invited Talks at Labs in Oxford University / Hesburgh Library at University of Notre Dame
  18. 2023: Invited talk at Annual Meetings of CISP, Tsinghua Foundation Model Research Center
  19. 2023: Invited talks at LLM-related Forums at WAIC'23, BDTC'23, CSIG'23
  20. 2023: Invited Talk at CCF ADL / CCF SSP
  21. 2023: Invited Talk at Tencent / Webank / CMCC / VMware China / iTechClub / OpenAtom Global Open-Source Summit
  22. 2023: Invited Talk at Tsinghua School of Management, Tsinghua PBC School of Finance / ICT of CAS / Beijing Normal University
  23. 2022: Invited Talk at Shandong University / Renmin University of China / Beijing Jiaotong University
  24. 2022: Invited Talk at CNCC 2022 LLM Forum
  25. 2021: Invited Talk at Tsinghua University, Computer Science Department
  26. 2020: Invited Talk at Beijing BAAI Conference Knowledge & Intelligence Forum: Graph Representation Learning and Pre-Training
  27. 2020: Invited Talk at CCF Young Elite Forum
  28. 2019: Invited Talk at Tsinghua University, Computer Science Department

Professional Services

Conference Organizers:

  1. Generative AI Day Co-Chair of KDD'24
  2. Large Language Model (LLM) Day Co-Chair of ACM WWW'24
  3. Large Language Model (LLM) Day Co-Chair of ACM KDD'23
  4. Track Co-Chair of WWW'23 Social Network Analysis and Graph Algorithms Track
  5. Ph.D. Symposium Co-Chair of the 2023 Web Conference (WWW'23)
  6. Program Co-Chair of ECML/PKDD'21 Applied Data Science Track
  7. Program Co-Chair of ACM/IEEE ASONAM'21 Industry Track
  8. Program Co-Chair of ECML/PKDD'20 Applied Data Science Track
  9. Program Co-Chair of National Conference on Social Media Processing (SMP'20)
  10. Workshop Co-Chair of SIAM SDM'20
  11. Deep Learning Day Co-Chair of ACM KDD'20
  12. Deep Learning Day Co-Chair of ACM KDD'19
  13. Deep Learning Day Co-Chair of ACM KDD'18

Journal Editors:

  1. Associate Editor of IEEE Transactions on Big Data (TBD), 2020--
  2. Associate Editor of Springer Social Network Analysis and Mining (SNAM), 2021--
  3. Associate Editor of AI OPEN, 2020--
  4. Guest Editor of Special Issue "AI for COVID-19" at IEEE TBD, 2020

Conference PC members:

  1. 2026: ICLR (Area Chair), NeurIPS (Area Chair), ICML (Area Chair), ARR (Area Chair), KDD (Area Chair)
  2. 2025: ACL (Senior Area Chair), ICLR (Area Chair), KDD (Area Chair), WWW (Area Chair), AAAI (Senior PC)
  3. 2024: ICLR (Area Chair), WWW (Area Chair), AAAI (Senior PC)
  4. 2023: KDD (Senior PC), WWW (Track Co-Chair), AAAI (Senior PC), ECML-PKDD (Area Chair)
  5. 2022: KDD (Senior PC), WWW (Senior PC), AAAI (Senior PC), ECML/PKDD (Area Chair)
  6. 2021: KDD, NeurIPS, AAAI (Senior PC), ECML/PKDD (PC Co-Chair ADS), ASONAM (Industry Track Co-Chair)
  7. 2020: KDD, NeurIPS, WSDM, WWW, SDM, ECML/PKDD (PC Co-Chair ADS), SMP (PC Co-Chair)
  8. 2019: KDD, WSDM, WWW, SDM, ICDM, CIKM, AAAI
  9. 2018: KDD, WSDM, WWW, SDM, ICDM, ECML/PKDD, DSAA
  10. 2017: KDD, WSDM, WWW, SDM, ASONAM, CIKM
  11. 2016: ASONAM, CIKM
  12. 2015: ASONAM

Competition Organizers:

  1. NeurIPS Competition OGB-LSC 2022: A Large-Scale Challenge for ML on Graphs at NeurIPS'22
  2. KDD CUP OGB-LGC: A Large-Scale Challenge for Machine Learning on Graphs at KDD'21

Journal Reviewers:

  1. Nature Machine Intelligence
  2. Nature Human Behavior
  3. Nature Scientific Reports
  4. JMLR, Journal of Machine Learning Research
  5. CSUR, ACM Computing Surveys
  6. TKDD, ACM Transactions on the Knowledge Discovery from Data
  7. TWEB, ACM Transactions on the Web
  8. TKDE, IEEE Transactions on Knowledge and Data Engineering
  9. TMC, IEEE Transactions on Mobile Computing
  10. TBD, IEEE Transactions on Big Data

Contact Info

1-309, FIT Building
Tsinghua University
Beijing 100084, China

Twitter/X: @ericdongyx

yuxiaod@@tsinghua.edu.cn
ericdongyx@gmail.com

*All stats are observed from Google Scholar on Jun. 2022