I am an Assistant Professor in Computer Science at Emory University. Before that, I received my Ph.D. in Computer Science at University of Illinois, Urbana Champaign, where I was working in the Data Mining Group led by Prof. Jiawei Han. Further before, I received my B.Eng. in Computer Science in 2014, from the Chu Kochen Honors College, Zhejiang University, where I was working in the State Key Lab of CAD&CG under Prof. Xiaofei He.

My research interests lie in graph data mining, applied machine learning, information systems and federated learning, as well as their applications in taxonomic knowledge graphs, recommender systems, biomedical informatics, neurocience and healthcare.

Motivated students interested in machine learning and data mining are welcome to get in touch for brainstorms and discussions :)


Latest News!

[2022.04] Our benchmark paper on GNNs for brain network analysis can be accessed on arXiv and the benchmark website is also fully available!

[2021.09] Our four papers got accepted by NeurIPS 2021. Three of them were under my supervision-- FedSage (subgraph-level federated learning), GCFL (graph-level federated learning) and EGI (GNN transferability). FedSage was selected for a spotlight presentation (3%). Great work, team!

[2021.04] Our three papers on graph neural networks (secure graph generation, embedding dimension selection and robust neighborhood aggregation) have been accepted by IJCAI 2021.

[2020.12] Our survey and benchmark paper on heterogeneous network representation learning has been accepted by IEEE TKDE. All code and data are available at

[2020.10] We are honored to receive the Best Paper Award from ICDM 2020! (1 out from 930 submissions and 91 acceptances)

[2020.05] Our work in collaboration with researchers in Pinterest and Stanford on web-scale contextualized graph neural networks has been accepted by KDD 2020 ADS track (oral 5.8%).

[2020.05] I am honored to receive the UIUC 2020 Doctoral Dissertation Completion Fellowship ($20,000), which is awarded to 20 candidates (from 20 departments) out from 74 nominations (from 48 departments) across the whole university.

[2020.05] I will be joining Emory University Dept. of Computer Science as a tenure-track Assistant Professor in September this year. Cor prudentis possidebit scientiam!

[2020.04] I am visiting University of Oxford and collaborating with Prof. Thomas Lukasiewicz and his team on structured information extraction from multi-media data this summer.

[2020.02] I will deliver research talks in Northwestern University, Simon Fraser University, and University of British Columbia, Emory University, University of Florida and University of Sydney.

[2020.01] I am visiting my alma mater, Zhejiang University, for the first time after my graduation five years ago.

[2019.09] I will give a talk in the Great Lakes Workshop on Data Science.

[2019.07] The Han Family will get together in San Francisco. Happy birthday Prof Han!

[2019.05] I am working in Pinterest Lab this summer with the Applied Science team led by Prof. Jure Leskovec.

Peer-reviewed Papers
Funded Projects
Countries Visited

Selected Publications

Since 2021 (Tenure-Track)

Before 2021 (Ph.D. Graduation)

Services and Activities

Journal Editing, Conference Organizing and Proposal Reviewing

  • [2021-2022] Web Chair, KDD 2022.
  • [2021-2022] Workshop Chair, CIKM 2022.
  • [2021-date] Associate Editor, IEEE Transactions on Big Data.
  • [2021-date] Associate Editor, Big Data Journal, Mary Ann Liebert, Inc..
  • [2021-date] Guest Editor, Frontiers in Big Data and Artificial Intelligence.
  • [2021] Session Chair, Graph Algorithms, KDD 2021, Virtual Event.
  • [2021] Session Chair, Special Networks and Dynamics, WWW 2021, Virtual Event.
  • [2021] Session Chair, Recommender Systems, ICDE 2021, Virtual Event.
  • [2018] Session Chair, Embedding and Learning, ASONAM 2018, Barcelona, Spain.
  • [2021] Panelist, NSF.

Peer Reviewing

  • [2019-date] The International Conference on Machine Learning (ICML).
  • [2019-date] The Conference on Neural Information Processing Systems (NeurIPS).
  • [2019-date] The AAAI Conference on Artificial Intelligence (AAAI).
  • [2019-date] The International Joint Conference on Artificial Intelligence (IJCAI).
  • [2018-date] The ACM Conference on Knowledge Discovery and Data Mining (KDD).
  • [2018-date] The International World Wide Web Conference (WWW).
  • [2018-date] The IEEE International Conference on Data Mining (ICDM).
  • [2018-date] The ACM International Conference on Web Search and Data Mining (WSDM).
  • [2018-date] The SIAM International Conference on Data Mining (SDM).
  • [2017-date] The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD).
  • [2017-date] The ACM International Conference on Information and Knowledge Management (CIKM).
  • [2017-date] The International Conference on Web Information Systems Engineering (WISE).

  • [2019-date] The IEEE Transactions on Big Data (TBD).
  • [2019-date] The ACM Transactions on Information Systems (TOIS).
  • [2019-date] The ACM Transactions on Intelligent Systems and Technology (TIST).
  • [2018-date] The IEEE Multidisciplinary Open Access Journal (Access).
  • [2018-date] The IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • [2017-date] The IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

Research Seminars

  • [2022.03] Data Science for Mental Health Group, Alan Turing Institution, London, UK.
  • [2022.02] Weill Cornell Medical College, Cornell University, New York, USA.
  • [2021.11] Department of Computer Science, Purdue University, Indiana, USA.
  • [2021.11] DGL User Group, California, USA.
  • [2021.10] Amazon ML Tech Talk, Washington, USA.
  • [2021.07] University of South California, California, USA.
  • [2020.03] University of Sydney, New South Wales, Australia.
  • [2020.03] University of Florida, Florida, USA.
  • [2020.02] University of Simon Fraser University, British Columbia, Canada.
  • [2020.02] Emory University, Georgia, USA.
  • [2020.01] Zhejiang University, Zhejiang, China.
  • [2019.12] University of British Columbia, British Columbia, Canada.
  • [2019.11] Northwestern University, Illinois, USA.
  • [2019.09] Great Lakes Workshop on Data Science in University of Notre Dame, Indiana, USA.
  • [2018.11] Fudan University and Shanghai Jiao Tong University, Shanghai, China.
  • [2018.03] Snap Inc., California, USA.
  • [2017.06] Tsinghua University and University of Science and Technology, Beijing, China.


  • [Fall 2022] Instructor, CS 253: Data Structures and Algorithms, Emory University.
  • [Spring 2022] Instructor, CS 570: Data Mining, Emory University.
  • [Fall 2021] Instructor, CS 253: Data Structures and Algorithms, Emory University.
  • [Spring 2021] Instructor, CS 253: Data Structures and Algorithms, Emory University.
  • [Fall 2020] Instructor, CS 584: Special Topics: Graph Data Mining, Emory University.
  • [Spring 2019] Lead TA, CS 512: Data Mining: Principles and Algorithms, UIUC.
  • [Spring 2018] Lead TA, CS 512: Data Mining: Principles and Algorithms, UIUC.
  • [Spring 2017] TA, CS 412: Introduction to Data Mining, UIUC.
  • [Spring 2016] TA, CS 511: Advanced Data Management, UIUC.
  • [Fall 2015] TA, CS 412: Introduction to Data Mining, UIUC.

Student Mentoring

Current Students

  • [2020-current] Jiaying Lu. PhD candidate in Emory (Advisor).
  • [2020-current] Hejie Cui. PhD candidate in Emory (Advisor).
  • [2020-current] Han Xie. PhD candidate in Emory (Advisor).
  • [2020-current] Xuan Kan. PhD candidate in Emory (Advisor).
  • [2021-current] Ran Xu. PhD candidate in Emory (Advisor).
  • [2020-current] Yanchao Tan. Visiting PhD from Zhejiang University, Hangzhou, China (Advisor).
  • [2020-current] Ke Zhang. Visiting PhD from Hong Kong University, Hong Kong, China (Advisor).
  • [2021-current] Zishan Gu. Master in Columbia (Advisor)
  • [2021-current] Owen Yang. Undergrad in Emory (Advisor).
  • [2021-current] Tony Gu. Undergrad in Emory (Advisor).
  • [2022-current] Sirui Hu. Undergrad in Emory (Advisor).
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Previous Students

  • [2022] Helen Zeng. Honors undergrad in Emory (Committee); MS in Yale.
  • [2021-2022] Leisheng Yu. Honors undergrad in Emory (Advisor); PhD in Rice.
  • [2021-2022] David Wei. Honors undergrad in Emory (Advisor); MS in Stanford.
  • [2021-2022] Olivia Song. Honors undergrad in Emory (Advisor); MS in Harvard.
  • [2021-2022] Sophy Huang. Honors undergrad in Emory (Committee); MS in Harvard
  • [2021-2022] Yanqiao Zhu. Master in CAS (Supervisor); PhD in UCLA.
  • [2021-2022] Eric Lee. PhD in Emory (Supervisor).
  • [2021-2022] Chen Ling. PhD in Emory (Supervisor).
  • [2021-2022] Ramraj Chandradevan. PhD in Emory (Supervisor).
  • [2021] Yuyang Gao. PhD in Emory (Committee).
  • [2021] Payam Karisani. PhD in Emory (Committee).
  • [2021] Ali Ahmadvand. PhD in Emory (Committee).
  • [2020-2021] Oliver Li. Undergrad in Emory (Supervisor); Undergrad in UMich.
  • [2020-2021] Celia Hu. Undergrad in Emory (Supervisor); MS in UPenn.
  • [2020-2021] Mingyue Tang. Master in USC (Supervisor); PhD in UVA.
  • [2020-2021] Ramraj Chandradevan. PhD in Emory (Committee).
  • [2020-2021] Xiangjue Dong. Master in Emory (Committee); PhD in TAMU.
  • [2020-2021] Yidan Xu. Master in UW (Supervisor); PhD in UMich.
  • [2018-2020] Jieyu Zhang. Undergrad in UIUC (Supervisor); PhD in UW.
  • [2018-2020] Haonan Wang. Undergrad in UIUC (Supervisor); PhD in UIUC.
  • [2018-2020] Yuxin Xiao. Undergrad in UIUC (Supervisor); PhD in MIT.
  • [2019] Peiye Zhuang. PhD in UIUC (Supervisor).
  • [2019] Wenhan Shi. Master in UIUC (Supervisor); SDE in LinkedIn.
  • [2018-2019] Siyang Liu. Master in UIUC (Supervisor); SDE@ in ServiceNow.
  • [2018] Sayantani Basu. Master in UIUC (Supervisor); PhD in UIUC.
  • [2018] Xikun Zhang. Undergrad in UIUC (Supervisor); PhD in Stanford.
  • [2018] Yichen Feng. Master in UIUC (Supervisor); Founder of QuestionBank, Shanghai.
  • [2017-2018] Mengxiong Liu. Undergrad in UIUC (Supervisor); Master in CMU.
  • [2017-2018] Zongyi Wang. Undergrad in UIUC (Supervisor); SDE in Google.
  • [2017] Lanxiao Bai. Undergrad in UIUC (Supervisor); SDE in Cerner.
  • [2016-2017] Hanqing Lu. Master in CMU (Supervisor); Applied scientist in Amazon.


University of Oxford, 2020-2021
Research interests: multi-modality knowledge extraction, question answering, commonsense reasoning
University of Illinois, Urbana Champaign, 2014-2020
Advisor: Prof. Jiawei Han
GPA 3.95/4.0; Research interests: graph data mining, network data science, applied machine learning
  • Thesis: Multi-Facet Graph Mining with Contextualized Projections.
  • Coordinated the SocialCube research project with DARPA under Agreement No. W911NF-17-C-0099.
  • Collaborated on the Intelligent Social Media and Sensor Stream Summarization and Situation Analysis research program with US Army Research Lab (ARL) under Cooperative Agreement No. W911NF-09-2-0053.
  • Collaborated on the Multi-Dimensional Structuring, Summarizing and Mining of Social Media Data research program with US National Science Foundation (NSF) under grant No. IIS 16-18481.
  • Contributed to the revision of Prof. Han’s popular textbook Data Mining: Concepts and Techniques for the 4th Edition.
  • Won the Yunni & Maxine Pao Memorial Fellowship for research accomplishments and leadership activities.
  • Received the Best Paper Award from ICDM 2020 (1 out from 930 submissions across the world).
  • Received the UIUC 2020 Doctoral Dissertation Completion Fellowship (awarded to 20 candidates from 20 departments out from 74 nominations from 48 departments across the whole university).
  • Received the KDD Dissertation Award Nomination (11 in total world-wide).
Chu Kochen Honors College, Zhejiang University, 2010-2014
Advisor: Prof. Xiaofei He
GPA: Major: 3.97/4.0, Overall: 3.86/4.0; Ranking: Top 2% of 201 students
  • Developed novel manifold learning algorithms for dimension reduction and image retrieval.
  • Won Chinese National Scholarship for Outstanding Merits, Zhejiang University (Top 1%).
  • Won Chinese National Fellowship for Excellent Intellects in Research, Zhejiang University (Top 1%).
NOI Coach: Mr. Zhongyou Wen
  • Won Yu Shouzhi scholarship (Top 1 among 800+).
  • Won First Prize in National Olympic in Informatics in Provinces.

Industry Experiences

Research Intern, Research Lab, Pinterest Inc., San Francisco
Supervisors: Dr. Aditya Pal, Prof. Jure Leskovec, Summer 2019

Empowered GraphSage for web-scale contextualized recommendation through context-aware aggregation and Hadoop-based stream training on heterogeneous pin-board networks.

Research Intern, Places Data & AI Research, Facebook Inc., New York
Supervisors: Dr. Do Huy Hoang, Dr. Tomas Mikolov, Summer 2018

Developed a two-step data-driven pipeline of feature generation and metric learning for place embedding to leverage ad-hoc place attributes and noisy training data towards efficient place deduplication.

Remote Research Contractor, Economics Graph Research, LinkedIn Co., Sunnyvale
Supervisors: Dr. Myungwan Kim, Dr. Shipeng Yu, 2018-2019

Developed a relation profiling algorithm based on multiple signals including user attributes, link structures and diffusive messages in the social network with novel multi-modal graph autoencoders.

Research Intern, Big Data Research, Didichuxing Inc., Beijing
Supervisors: Prof. Xuewen Chen, Prof. Jieping Ye, Summer 2017

Constructed the transportation HIN (heterogeneous information network) based on DiDi's travel data and developed a pattern-aware HIN embedding algorithm for passenger experience prediction.

Research Intern, Research Lab, Snap Inc., Los Angeles
Supervisors: Dr. Jie Luo, Dr. Li-Jia Li, Summer 2016

Developed a joint learning framework of user links and attributes for friend recommendation and interest targeting. Implemented a Spark pipeline and scaled it to networks with millions of nodes and billions of edges.

Software Engineer Intern, Demographics ads serving, Google LLC, Seattle
Supervisor: Dr. Tianyi Wu, Summer 2015

Implemented data extraction and inventory analysis pipeline using flume C++. Implemented an online simulation of ads serving and an offline optimal algorithm based on max flow to analyze the inventory.



home, family, best food


Alaska, road trip, national parks, corn fields


cold and vast, magnificent mountains and lakes


tequila, hearty people, colorful and vivid towns


peaceful, adventurous, aow, kite surf, island hopping, 7 countries


Easter island, moai, peaseful, diverse views, volcano, gobi, glacier


Amazon jungles, Machu Picchu, Inca trail, black beach


Galapagos, equatorial, overnight buses, lack of order


Uyuni, altitude, salt laguna, flamingo, geyser, dead sea


nostalgia, no internet, vintage car, carriage, cigar, rum, chill


magnificent ocean view, seafood, beef, mines, kangaroo


Semporna, scuba diving, jalan alor night food, massage


Mont Saint-Michel, Eiffel, Musee du Louvre, Notre Dame, Loire valley castles, Eze


great cocktails, speakeasy, gin, rain, Oxford, Edinburgh, Scotch whiskey


Antoni Gaudi, paella, tapas, Sangria


green, Guinness, windy, lively night life


Acropolis of Athens, white and blue, expensive and inefficient


kebab, sheesha, Rome, Muslim, everyone knows Chinese, balloon


namaste, temples, buddha, harshish


college graduation trip, vikings, motorcycle, rain, lovely old times