Jie Tang (Tang, Jie) 唐 杰

NSFC Distinguished Young Scholar

Knowledge Engineering Group (KEG),
Department of Computer Science,
Tsinghua University

E-Mail:  jietang at tsinghua . edu . cn

I am a Professor of Computer Science of Tsinghua University. I am a Fellow of the ACM, a Fellow of AAAI, and a Fellow of the IEEE. My research interests include artificial general intelligence (AGI), data mining, social networks, machine learning and knowledge graph. Our research received the SIGKDD Test-of-Time Award (Ten-year Best Paper). I also received the SIGKDD Service Award.

Recent Research: I put all my efforts into artificial general intelligence with a mission toward teaching machines to think like humans. Similar to Open AI's GPT serials, we, together with a big research team, have developed GLM-130B, ChatGLM, CogView&CogVideo, CodeGeex. Proudly, our pretrained base model has been downloaded by more than 1,000 organizations from 70+ countries, and our open ChatGLM-6b has been downloaded by nearly 10,000,000 times all over the world.

For More: I also invented AMiner.org, which has attracted over 30,000,000 users from 220 countries/regions. I served as GC of WWW'23, PC of WWW'22, and EiC of IEEE T. on Big Data and AI Open J. I also received the 2nd National Award for Science&Technology, and NSFC for Distinguished Young Scholar.

Hiring: I am looking for highly-motivated and fully-devoted students to closely work with me on the exciting area of artificial general intelligence. I also have open Postdoctoral Positions to investigate underlying theory and algorithms in artificial general intelligence.

If you want me to write a recommendation letter for you, please first read this.

*New ICLR'24 Keynote (The ChatGLM's Road to AGI)
Our ArnetMiner paper has been awarded the (SIGKDD Test-of-Time Award)!

I am recently working on artificial general intelligence, graph neural networks, social network mining, and academic knowledge graph.

Large Pre-trained Models   [ChatGLM: 从千亿模型到ChatGPT (in Chinese)]  [Keynote@AIED'22/NetSci'22: Pre-Training the World (in English)]
GLM-130B (ICLR'23) is an open bilingual (English & Chinese) bidirectional dense model with 130 billion parameters, pre-trained using the General Language Model (GLM) algorithm (ACL'22). GLM-130B has been trained on over 1 trillion text tokens and exhibits quite a few unique features.
    Based on GLM-130B, we have developed ChatGLM by applying techniques such as supervised fine-tune and RLHF. The open-sourced version ChatGLM-6B tops the trending of Huggingface for more than three weeks.

Models and codes: [GLM-130B] [ChatGLM-6B] [GLM] [CogView] [CogVideo] [CodeGeex]
Representation Learning on Networks   [GNN&Self-supervised Learning] [人工智能下一个十年]
The goal is to automatically encode network structure into low-dimensional space (embeddings), using techniques such as neural networks.
    We theoretically prove that recent models such as DeepWalk, LINE, PTE, and node2vec can be unified into the matrix factorization framework with closed forms. we present a new method NetMF, which significantly outperforms DeepWalk and LINE for conventional network mining tasks (Qiu et al., WSDM'18). Based on the learned representations, we further propose a multi-head attention network for predicting user behavior (Qiu et al., KDD'18) and NetSMF for large scale networks (Qiu et al., WWW'19). Further, we incorporate user feedback into the prediction and propose a bandit learning model (Qi et al., NeurIPS'18).

Datasets and codes: [NetMF]  [DeepInf]
Social Network Mining  [IC2S2'19 Tutorial]  [KDD'18 Tutorial]   [Book]  [Survey]
Online social networks already become a bridge to connect our physical daily life with the virtual information space, producing huge volume of networked data. We aim to understand the mechanism underlying the dynamics of social interaction between users and information diffusion in the network.
   We propose a new method Topical Affinity Propagation (TAP) to model the topic-level social influence (Tang et al., KDD'09), conformity influence analysis (Tang et al., KDD'13), structural influence (Zhang et al., AAAI'17), inferring social tie (Tang et al., WSDM'12, Tang et al., TOIS'16), and user demographics (Dong et al., KDD'14). At the macro-level, we focus on mining top-k structural hole spanners, who control the information diffusion across different communities (Lou and Tang, WWW'13) and following link diffusion (Zhang et al., TKDE'15).

Datasets and codes: [Topic-Influence [Structural hole] [Datasets for SNA]
Academic Knowledge Graph   [Tutorial]  [System]   [Career Trajectory]
We focus on building large-scale knowledge graph, particularly for scholarly data. In this research, we work on various topics including Expert Finding ( Qian et al., IJCAI'18; Tang et al., Machine Learning J'18 ) Career Trajectory Mining ( Wu et al., IJCAI'18 ) Social Recommendation (Tang et al., KDD'12), Information/knowledge Integration (Zhong et al., SIGMOD'09, Wang et al., WWW'12, Wang et al., IJCAI'13), Name Disambiguation (Tang et al., TKDE'12, Zhang et al., KDD'18 ) Summarization (Yang et al., SIGIR'11), Content Alignment (Hou et al., IJCAI'13; Hou et al., TOIS'17 ), Similarity Search (Zhang et al., TOIS'17).
   Based on these research, we have developed a system AMiner (ArnetMiner) (Tang et al., KDD'08 (SIGKDD Test-of-Time Award); Tang et al., TKDD'10), for academic search and mining. The system has over 136 million researchers and 200 million papers. Since 2006, the system has attracted over 10 million independent IP accesses from more than 220 countries/regions.

Datasets and codes: [AMiner Dataset]  [Open Academic Graph]


Summary: Research interest: Artificial Intelligence, Social Networks, Data Mining, Knowledge Graph. I have published 400+ articles in major computer science conferences, including IJCAI / AAAI (30+), NIPS/ICML (10+), KDD (40+), and ~100 articles in the core journals of computer science including TKDE/TKDD/TOIS/TAC (40+).

Social Network / Data Mining / Machine Learning

Knowledge Graph



TALKS   Go Top

  • Keynote about Representation Learning on Networks to be given at ASONAM'19
  • Keynote about AI driven MOOCs given at EDM'17
  • Invited talk about academic knowledge graph given at WSDM'16
  • Keynote about social network mining given at SocInfo'15


Post Doc

  • Zhongyang Zhu
  • Shaojiang Wang
  • Yu Qiu
  • Yunpeng Gao
  • Jing Xu (Graduated)
  • Sha Yuan (Leader @ BAAI)
  • Yutao Zhang(CTO or Recurrent.ai)
  • Huaiyu Wan (Assistant Professor @ Beijing Jiaotong University)
  • Daifeng Li (Associate Professor @ Sun Yat-Sen University)

PhD Students

  • Chenhui Zhang
  • Jiezhong Qiu
  • Wenzheng Feng
  • Fanjin Zhang
  • Aoao Feng
  • Ming Ding
  • Xu Zou
  • Mengyang Sun
  • Ming Zhou
  • Yukuo Cen
  • Zhengxiao Du
  • Xu Cheng
  • Kan Wu (Graduated)
  • Yu Han (Graduated, Alibaba)
  • Yutao Zhang (Graduated)
  • Yang Yang (Assistant Professor @ Zhejiang University)
  • Jing Zhang (Assistant Professor @ Renmin University)

Master Students

  • Qingyang Zhong
  • Kun Zhang
  • Pengcheng Wang
  • Alexandre Boulenger
  • Yonglin Tan
  • Xiaohan Zhang
  • Qingsong Lv
  • Jialin Zhao (graduated in 2021)
  • Gan Luo (graduated in 2021)
  • Vincent Couverchel (graduated in 2019)
  • Valentin Kao (graduated in 2019)
  • Da Yin (graduated in 2021)
  • Yan Wang (M) (graduated in 2020)
  • Runzhi Gao (graduated in 2021)
  • Yan Wang (F) (graduated in 2019)
  • Jie Zhang (graduated in 2019)
  • Zhenhuan Chen (graduated in 2019)
  • Yifeng Zhao (graduated in 2019)
  • Mogford Michael (graduated in 2019)
  • Ben Keller (graduated in 2019)
  • Rytis Kumpa (graduated in 2019)
  • Zhengyang Song (graduated in 2019)
  • Ziwu Sun (graduated in 2018)
  • Chaoyang Li (graduated in 2018)
  • Xiaochen Wang (graduated in 2018)
  • Fang Zhang (graduated in 2018)
  • Tianji Zhao (graduated in 2017)
  • Hong Yang (graduated in 2017, Assistant Professor @ Qinghai University)
  • Zhanpeng Fang (graduated in 2016, Google US)
  • Mu Yang (graduated in 2016, CTO @ Face++)
  • Wenbin Tang (graduated in 2013, CTO @ Face++)
  • Marcel Lee (graduated in 2013)
  • Lenin Mookiah (graduated in 2013, PhD @ Tennessee Technological University)
  • Yongliang Zhu (graduated in 2012, work @ Fuzhou)
  • Wenyuan Xu (graduated in 2012)
  • Zi Yang (graduated in 2011, now PhD at CMU)
  • Limin Yao (co-advisor, graduated in 2008, @Twitter)
  • Duo Zhang (co-advisor, graduated in 2007, @Twitter...)

Undergraduate Students
Here list those working with me for at least 8 months. I may miss some. Please let me know if you found.
If you want me to write a recommendation letter for you, please first read this.

  • Current
    • Aohan Zeng
    • Wenyi Hong
    • Zhuoyi Yang
    • Ziang Li
    • Zeyi Chen
    • Shiyu Zhao
    • Wendi Zheng
    • Hanyu Lai
    • Xiao Xia
    • Xueyi Liu
    • Xinghao Wang
    • Haoyun Hong
    • Yijia Xiao
    • Yuxiang Chen
    • Xingjian Zhang
    • Zhibing Li
  • Graduated in 2021
    • Xiao Liu
    • Zhenyu Hou
    • Tianshu Yu
    • Haojun Yu
    • Shangqing Xu
    • Niuniu Zhangli
    • Kaiyuan Chen
  • Graduated in 2020
    • Zhengxiao Du
    • Qingyang Zhong
    • Yihan Wang
    • Jiaqi Wang
    • Han Yu
    • Xiao Liu
    • Kaiyuan Xu
    • Li Mian
    • Zijun Yao
  • Graduated in 2019
    • Peiran Yao
    • Qibin Chen
    • Yonglin Tan
    • Minda Hu
    • Zhicong Fang
    • Zhuoyue Xiao
    • Yuhui Ding
    • Jianan Yao
    • Chenyu Wang
    • Junlin Song
    • Xi Chen
    • Tong Xiao
  • Graduated in 2018
    • Da Yin
    • Peiran Yao
    • Gan Luo
    • Ming Ding
    • Yijian Qin
    • Xinyang Zhang
    • Yukuo Cen
    • Yuanhang Zheng
    • Lemeng Wu
    • Yifan Liu
  • Graduated in 2017
    • Xiaotao Gu (PhD @ UIUC)
    • Yujie Qian (PhD @ MIT)
    • Shaoxiong Wang (PhD @ MIT)
    • Miao Ren (MS @ CMU)
    • Qian Zhang (MS @ UCLA)
    • Sida Gao (MS @ CMU)
  • Graduated in 2016
    • Yuan Yuan (PhD @ MIT)
    • Honghao Wei (MS @ Stanford)
    • Fei Xia (PhD @ Stanford)
    • Jingqing Zhang (PhD @ Imperial College London)
    • Tianrun Li
    • Jiaqi Ma (PhD @ Mitch)
    • Shan Han
    • Yu Xia (PhD @ MIT)
  • Graduated in 2015
    • Zhilin Yang (PhD at CMU)
    • Xinyu Zhou (@Face++)
    • Weiran He
    • Cong Ma (PhD at Princeton)
    • Xunkai Zhang (@Google US)
    • Zhelun Wu
    • Wei Huang (PhD @ Tsinghua)
    • Ye Cao
  • Graduated in 2014
    • Qianru Zhu (MS at CMU)
    • Yang Liu
    • Yihan Sun (PhD at CMU)
    • Yaohui Ye
    • Ning Jiang (U Mitch)
    • Chenran Guan (MS at CMU)
    • Jingyuan Liu
  • Graduated in 2013
    • Honglei Zhuang (PhD at UIUC)
    • Sen Wu (MS at Stanford)
    • Zhanpeng Fang (MS at THU)
    • Liangtao Zhang (Work)
    • Bo Ma (MS at CMU)
    • Wei Chen (MS at CMU)
  • Graduated in 2012
    • Xiaowen Ding (MS at CMU)
    • Yanting Zhao (PhD at Columbia U.)
    • Yu Zhao (MS at CMU)
    • Cheng Chen (PhD at MIT)
    • Lin Xu
    • Hang Su (PhD at Georgia Tech.)
    • Tian Li (Dartmouth College)
    • Yuxiao Dong (PhD at Notre Dame U.)
    • Yubing Dong (MS at USC)
  • Graduated in 2011
    • Yuan Zhang (PhD at MIT)
    • Lixin Shi (PhD at MIT)
    • Tao Lei (PhD at MIT)
    • Xuezhi Wang (PhD at CMU)
    • Yuan Du (MS at Columbia U.)
    • Yiran Chen (PhD at MSU)
    • Jingyi Guo (PhD at UMass)
    • Rui Du (MS at CMU)
    • Wenjing Yu (MS at USC)
    • Haoquan Guo (MS at NYU)
  • Graduated in 2010
  • Graduated in 2009
    • Chi Wang (PhD at UIUC)
    • Fengjiao Wang (PhD at UIC)
  • Graduated before 2009
    • Liu Liu (CMU and now Google, US)
    • Yize Li (UCSC, and now StumbleUpon, US)

Other students collaborated with me

  • Ming Yin (2011, PhD at Havard)
  • Yajie Miao (2011, PhD at CMU)

Last updated date: April 12, 2023, by Jie Tang.