Biography

I am an Assistant Professor of Computer Science at Emory University since 2020. Before that, I received my Ph.D. in Computer Science at the University of Illinois, Urbana Champaign, where I was working in the Data Mining Group, advised by Prof. Jiawei Han. Further before, I received my B.Eng. in Computer Science in 2014, from the Chu Kochen Honors College of Zhejiang University, advised by Prof. Xiaofei He.

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

I am open to discuss research opportunities with motivated students who have strong backgrounds in machine learning and/or health informatics. Please reach out only if you are ready to devote time and effort in a research project.

Contact

Latest News!

[2024.01] My high school student Alexis Li has been named a top 40 finalist in the 83rd Regeneron Science Talent Search-- the nation’s oldest and most prestigious science and mathematics competition for high school seniors, also known as the youth Nobel prize competition. Alexis has also recently been REA accepted by Stanford.

[2024.01] We will be conducting a new tutorial for BrainGB at the ISBI 2024 conference in Athens, Greece at the end of this May.

[2023.10] I am honored to receive a secondary appointment as Assistant Professor in the Department of Biostatistics and Bioinformatics in the Rollins School of Public Health (RSPH) at Emory University.

[2023.10] During my incoming trip to UK for CIKM 2023, I will deliver two seminar talks in the School of Informatics at University of Edinburgh and the Department of Computer Science at University of Oxford.

[2023.09] Our paper on artificial node features for GNNs has been consistently ranked as 1st in the 2023 lists of Most Influential CIKM Papers produced by Best Paper Digest (2023-01, 2023-04, 2023-09).

[2023.09] We thank Microsoft Azure for supporting our research on HealthGPT under the Accelerating Foundation Models Research initiative.

[2023.09] We thank OpenAI for providing us with API credits under the Researcher Access program.

[2023.09] Many thanks to NSF CISE/SBE/EDU for funding our Foundations project Dynamic Brain Graph Mining under the Integrative Strategies for Understanding Neural and Cognitive Systems (NCS) Program.

[2023.08] Many thanks to NSF CISE for funding our Medium project VirtualLab: Integrating Deep Graph Learning and Causal Inference for Multi-Agent Dynamical Systems under the competitive IIS/III Core Program.

[2023.06] It was my pleasure to lead the nomination for Jure Leskovec towards his well-deserved and well-belated KDD Innovation Award.

[2023.04] We will be organizing the 2nd International Workshop on Federated Learning with Graph Data (FedGraph2023) at the ICDM 2023 conference in Shanghai. Please see our call for various types of submissions and co-hosted new data challenge (with cash awards)!

[2023.03] We will be conducting a tutorial for BrainGB during the ICIBM 2023 conference in Tampa, FL, on June 18th.

[2023.02] Many thanks to NIH NIDDK for funding my K25 award on Understanding Diabetes Heterogeneity via Mining Multimodality Interconnected Data. The award could not have been possible without the help from my many colleagues and great mentor team Dr. Vicki Hertzberg, Dr. Mohammed Ali, Dr. Guillermo Umpierrez and Dr. Roy Simpson.

[2022.11] Our paper on EHR-based clinical predictions was selected as one of the two Best Papers at ML4H. Congratulations to Ran Xu and Yue Yu, and many thanks to Joyce Ho and Mohammed Ali!

[2022.09] It was a great pleasure to mentor Ms. Alexis Li from Hamilton High School at Chandler. Alexis will take her work under my mentorship on brain network mixup to the final competition of ISEF this year. Good luck Alexis!

[2022.08] Our research on FedGraph was selected to be funded by Amazon Research Awards.

[2022.08] Congratulations to FederatedScope-GNN on winning the ADS Best Paper Award of KDD 2022, and many thanks for the detailed featuring and integration of our FedSage and GCFL as the most representative FGL models in the platform.

[2022.07] I was happy to serve as a mentor for the KDD 2022 Undergraduate Consortium. Check out this interesting paper on per-node privacy of GCN written by my mentee at University of Virginia.

[2022.07] It was a great pleasure to serve as a mentor for our NSF REU/RET site on Computational Mathematics for Data Science at Emory this summer. Here goes a cute video made by my mentees and also check out their web post, poster and paper!

[2022.06] We will be organizing the 1st International Workshop on Federated Learning with Graph Data (FedGraph2022), at ACM CIKM 2022 in Atlanta this October. Various types of submissions are welcomed!

[2022.05] Our four papers got accepted by KDD 2022, all of which are based on our recent progress in healthcare and neuroscience informatics-- we have successfully applied modern graph learning techniques to electronic health records, mobile health data, brain imaging, and SEEG data. One of them (GraphDNA) was honored to receive the Best Paper Award of Health Day (3 in total). Congratulations, team!

[2022.04] We will be organizing the 1st International Workshop on Neural Network Models for Brain Connectome Analysis (BrainNN2022), at IEEE BigData 2022 in Osaka this December. Various types of submissions are welcomed!

[2022.03] Our benchmark paper on GNNs for brain network analysis can be accessed on arXiv and the benchmark website is also fully available! ([2022.10] Update: the BrainGB paper is now accepted by IEEE TMI.)

[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 https://github.com/yangji9181/HNE.

[2020.10] I am honored to receive the Best Paper Award from ICDM 2020 (1 out from 930 submissions and 91 acceptances)! Check out the TaxoGAN paper.

[2020.05] Our work (MultiSage) in collaboration with researchers in Pinterest and Stanford on web-scale contextualized graph neural networks has been selected as the Best Paper Runner-Up in the Applied Data Science Track of KDD 2020.

[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, 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.

Citations
Selected Honors
Peer-Reviewed Papers
Countries Visited

Selected Honors

  • [2023] NIH K25 (Career) Award (No. K25DK135913).
  • [2023] NSF IIS/III Core Medium Award (No. 2312502).
  • [2023] NSF NCS Foundations Award (No. 2319449).
  • [2023] Microsoft Accelerating Foundation Models Research Award.
  • [2023] OpenAI Researcher Access Award.
  • [2023] DARPA AI Forward Scholarship.
  • [2022] Amazon Research Award.
  • [2022] Emory URC Award.
  • [2021] Halle Global Research Award.
  • [2022] Best Paper Award of ML4H.
  • [2022] Best Paper Award of KDD Health Day.
  • [2022] Best Paper Award of CIKM-FedGraph.
  • [2020] Best Paper Award of ICDM (1 from 930 submissions).
  • [2020] Best Paper Award Runner-Up of KDD Applied Data Science.
  • [2020] UIUC Doctoral Dissertation Completion Fellowship (at most 1 per department).
  • [2019] Yunni & Maxine Pao Memorial Fellowship for research accomplishments and leadership activities.

Peer-Reviewed Publications

Since 2021 (Tenure-Track)


Before 2021 (Ph.D. Graduation)

Services and Activities

Editorial Boards

  • [2022-date] Associate Editor, IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
  • [2021-date] Associate Editor, IEEE Transactions on Big Data (TBD).
  • [2021-date] Associate Editor, Big Data Journal, Mary Ann Liebert, Inc.
  • [2021-2022] Guest Editor, Frontiers in Big Data and Artificial Intelligence.

Event Organizations

  • [2023] Social Media and Publicity Chair, The ACM International Conference on Knowledge Discovery and Data Mining (KDD).
  • [2023] Lead Organizer and General Chair, The 2nd IEEE International Workshop on Federated Learning with Graph Data (FedGraph2023).
  • [2023] Proceedings Chair, The ACM International Conference on Information and Knowledge Management (CIKM).
  • [2023] KDD Cup Chair, The ACM International Conference on Knowledge Discovery and Data Mining (KDD).
  • [2023] Track Chair, The Conference on Health, Inference, and Learning (CHIL).
  • [2022] Lead Organizer and General Chair, The 1st ACM International Workshop on Federated Learning with Graph Data (FedGraph2022).
  • [2022] Lead Organizer and General Chair, The 1st IEEE International Workshop on Neural Network Models for Brain Connectome Analysis (BrainNN2022).
  • [2022] Workshop Chair, The ACM International Conference on Information and Knowledge Management (CIKM).
  • [2022] Web Chair, The ACM International Conference on Knowledge Discovery and Data Mining (KDD).
  • [2023] Session Chair, Transfer Learning 2, CIKM 2023, Birmingham, UK.
  • [2023] Session Chair, Knowledge and Reasoning I, KDD 2023, California, USA.
  • [2023] Session Chair, Data Mining and Knowledge Discovery V, ICDE 2023, California, USA.
  • [2022] Session Chair, Federated Learning, CIKM 2022, Georgia, USA.
  • [2022] Session Chair, Few Shot Learning, KDD 2022, Washington DC, USA.
  • [2022] Session Chair, GNN Methods, WWW 2022, Virtual Event.
  • [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.

Conference Reviews

  • [2024-date] The Annual Meeting of the Association for Computational Linguistics (ACL).
  • [2024-date] The ACM International Conference on Multimedia (MM).
  • [2024-date] The International Conference on Machine Learning (ICML).
  • [2023-date] The International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI).
  • [2023-date] The ACM International Conference on Research and Development in Information Retrieval (SIGIR).
  • [2022-date] The International Conference on Learning Representations (ICLR).
  • [2021-date] The IEEE International Conference on Data Engineering (ICDE).
  • [2021-date] The IEEE International Conference on Data Mining (ICDM).
  • [2020-date] The Conference on Neural Information Processing Systems (NeurIPS).
  • [2020-date] The ACM International Conference on Web Search and Data Mining (WSDM).
  • [2019-date] The AAAI Conference on Artificial Intelligence (AAAI).
  • [2019-date] The International Joint Conference on Artificial Intelligence (IJCAI).
  • [2018-date] The ACM International Conference on Knowledge Discovery and Data Mining (KDD).
  • [2018-date] The International World Wide Web Conference (WWW).
  • [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).

Journal Reviews

  • [2023-date] Psychiatry Research, Elsevier.
  • [2023-date] Medical Image Analysis, Elsevier.
  • [2023-date] The IEEE Journal of Biomedical and Health Informatics (JBHI).
  • [2022-date] Bioinformatics, Oxford Academic.
  • [2020-date] The IEEE Transactions on Network Science and Enginieering (TNSE).
  • [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).

Grant Reviews

  • [2021-date] Emory University Research Committee (URC).
  • [2021-date] National Science Foundation (NSF).

Research Seminars

  • [2023.12] Invited talk at the Asia Conference on Cognitive Engineering and Intelligent Interaction (CEII2023), Hong Kong, China.
  • [2023.10] Department of Computer Science, University of Oxford, UK.
  • [2023.10] School of Informatics, University of Edinburgh, UK.
  • [2023.08] Keynote speech at the International Workshop on Federated Learning for Distributed Data Mining, KDD 2023, California, USA.
  • [2023.04] Digital and Data Science Group, Kaiser Permanente, Georgia, USA.
  • [2023.04] ScAi Lab, University of California, Los Angeles, California, USA.
  • [2023.03] Trustworthy Machine Learning Class, Yale University, Connecticut, USA.
  • [2023.03] Data Science Team, Home Depot Headquarter, Georgia, USA.
  • [2022.12] Natural Language Processing Laboratory, Nara Institute of Science and Technology, Japan.
  • [2022.11] Secchia Center, Michigan State University, Michigan, USA.
  • [2022.10] Rollins School of Public Health, Emory University, Georgia, USA.
  • [2022.09] Nell Hodgson Woodruff School of Nursing, Emory University, Georgia, USA.
  • [2022.05] The Computational Neuroimage Science (CNS) Lab, Stanford University, California, USA.
  • [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.

Teaching

  • [Fall 2023] Instructor, CS 253: Data Structures and Algorithms, Emory University.
  • [Spring 2023] Instructor, CS 570: Data Mining, Emory University.
  • [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 Mentees

  • [2020-current] Jiaying Lu. PhD candidate in Emory (Thesis advisor).
  • [2020-current] Hejie Cui. PhD candidate in Emory (Thesis advisor).
  • [2020-current] Han Xie. PhD candidate in Emory (Thesis advisor).
  • [2020-current] Xuan Kan. PhD candidate in Emory (Thesis advisor).
  • [2021-current] Ran Xu. PhD candidate in Emory (Thesis advisor).
  • [2023-current] Keqi Han. PhD candidate in Emory (Thesis advisor).
  • [2023-current] Yuzhang Xie. PhD candidate in Emory (Thesis advisor).
  • [2023-current] Siyu Li. PhD candidate in Emory (Thesis advisor).
  • [2022-current] Louis Lu. Honors undergrad in Emory (Thesis advisor).
  • [2021-current] Eric Lee. PhD candidate in Emory (Thesis committee).
  • [2021-current] Malvern Madondo. PhD candidate in Emory (Thesis committee).
  • [2021-current] Ramraj Chandradevan. PhD candidatein Emory (Thesis committee).
  • [2021-current] Chen Lin. PhD candidate in Emory (Thesis committee).
  • [2021-current] Guangji Bai. PhD candidate in Emory (Thesis committee).
  • [2021-current] Chen Ling. PhD candidate in Emory (Thesis committee).
  • [2022-current] Hong kyu Lee. PhD candidate in Emory (Thesis committee).
  • [2022-current] Tomilola Obadiya. PhD candidate in Emory (Thesis committee).
  • [2022-current] Yuhang Yao. PhD candidate in Carnegie Mellon University (Thesis committee).
  • [2022-current] Jianhui Sun. PhD candidate in University of Virginia (Thesis committee).
  • [2022-current] Yue Yu. PhD candidate in Georgia Institute of Technology.
  • [2022-current] Emir Ceyani. PhD candidate in University of Southern California.
  • [2022-current] Jiachen Zhou. Master student in University of Columbia.
  • [2022-current] Alexis Li, High-school student in Hamilton High School.
  • [2023-current] Ziyang Zhang. Master in Emory University.
  • [2023-current] Tao Li. Master in Stevens Institute of Technology.
  • [2023-current] Kaiqiao Han. Undergrad in Zhejiang University.

Previous Mentees

  • [2023] Allan Zhang. Honors undergrad in Emory (Thesis committee); Master in Georgia Tech.
  • [2022-2023] Owen Yang. Honors undergrad in Emory (Thesis advisor); PhD in Duke.
  • [2022-2023] Tony Gu. Undergrad in Emory; Undergrad in Georgia Tech.
  • [2022-2023] Yongchen Qian. Undergrad in Emory; Master in CMU.
  • [2022-2023] Wenjing Ma. PhD in Emory (Thesis committee); Postdoc in MSU.
  • [2022] Ethan Young. Undergrad in UCLA (REU mentor).
  • [2022] Erica Choi. Undergrad in Columbia University (REU mentor).
  • [2022] Sally Smith. Undergrad in Georgia Institute of Technology (REU mentor).
  • [2022] Edward Wei. Undergrad in University of Virginia (KDD-UC mentor).
  • [2022] Helen Zeng. Honors undergrad in Emory (Thesis committee); Master in Yale.
  • [2021-2022] Zishan Gu. Master in Columbia; PhD in OSU.
  • [2021-2022] Yuyang Gao. PhD in Emory (Thesis committee); Data Scientist in Home Depot.
  • [2021-2022] Junxiang Wang. PhD in Emory (Thesis committee); Research Scientist in NCE Lab.
  • [2021-2022] Leisheng Yu. Honors undergrad in Emory (Thesis advisor); PhD in Rice.
  • [2021-2022] David Dai. Honors undergrad in Emory (Thesis advisor); Master in Stanford.
  • [2021-2022] Olivia Song. Honors undergrad in Emory (Thesis advisor); Master in Harvard.
  • [2021-2022] Sophy Huang. Honors undergrad in Emory (Thesis committee); Master in Harvard
  • [2021-2022] Yanqiao Zhu. Master in CAS; PhD in UCLA.
  • [2021-2022] Gongxu Luo. Master in CAS; PhD in MBZUAI.
  • [2020-2022] Ke Zhang. Visiting PhD from Hong Kong University; Research Scientist in ClusterTech.
  • [2020-2022] Yanchao Tan. Visiting PhD from Zhejiang University; AP in Fuzhou University.
  • [2021] Payam Karisani. PhD in Emory (Thesis committee); Postdoc in UIUC.
  • [2021] Ali Ahmadvand. PhD in Emory (Thesis committee); ML Engineer in Google.
  • [2021] Dheep Dalamal. Undergrad in Emory; Master in Texas A&M.
  • [2020-2021] Sai Vidyaranya Nuthalapati. Master in Oxford; Research engineer in Meta.
  • [2020-2021] Oliver Li. Undergrad in Emory; Undergrad in UMich.
  • [2020-2021] Celia Hu. Undergrad in Emory; Master in UPenn.
  • [2020-2021] Mingyue Tang. Master in USC; PhD in UIUC.
  • [2020-2021] Xiangjue Dong. Master in Emory (Committee); PhD in Texas A&M.
  • [2020-2021] Yidan Xu. Master in UW; PhD in UMich.
  • [2019-2021] Qi Zhu. PhD in UIUC; Applied Scientist in Amazon.
  • [2019-2020] Yiqing Xie. Undergrad in UIUC; PhD in CMU.
  • [2018-2020] Jieyu Zhang. Undergrad in UIUC; PhD in UW.
  • [2018-2020] Haonan Wang. Undergrad in UIUC; PhD in UIUC.
  • [2018-2020] Yuxin Xiao. Undergrad in UIUC; PhD in MIT.
  • [2019] Peiye Zhuang. PhD in UIUC; Research Scientist in Snap.
  • [2019] Wenhan Shi. Master in UIUC; SDE in LinkedIn.
  • [2018-2019] Siyang Liu. Master in UIUC; SDE in ServiceNow.
  • [2018] Sayantani Basu. Master in UIUC; PhD in UIUC.
  • [2018] Xikun Zhang. Undergrad in UIUC; PhD in Stanford.
  • [2018] Yichen Feng. Master in UIUC; Founder of QuestionBank, Shanghai.
  • [2017-2018] Mengxiong Liu. Undergrad in UIUC; Master in CMU.
  • [2017-2018] Zongyi Wang. Undergrad in UIUC; SDE in Google.
  • [2017] Lanxiao Bai. Undergrad in UIUC; SDE in Cerner.
  • [2016-2017] Hanqing Lu. Master in CMU; Applied scientist in Amazon.

Academic Backgrounds

Research interests: graph data mining, applied machine learning, knowledge graphs, federated learning; recommender systems, social networks, neuroscience, healthcare.
University of Oxford, 2020-2022
Research interests: multi-modality knowledge extraction, question answering, commonsense reasoning.
University of Illinois, Urbana Champaign, 2014-2020
Advisor: Jiawei Han
Doctoral Committee: Jiawei Han (chair), Jian Peng, Chengxiang Zhai, Jure Leskovec
GPA 3.95/4.0; Research interests: graph data mining, network data science, applied machine learning.
  • Thesis: Multi-Facet Graph Mining with Contextualized Projections.
  • KDD 2021 Dissertation Award Nomination (9 world-wide).
  • 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.
Chu Kochen Honors College, Zhejiang University, 2010-2014
Advisor: Xiaofei He
GPA: Major: 3.97/4.0, Overall: 3.86/4.0; Ranking: Top 2% of 201 students
  • Chinese National Scholarship for Outstanding Merits, Zhejiang University (Top 1%)
  • Chinese National Fellowship for Excellent Intellects in Research, Zhejiang University (Top 1%)
NOIP Coach: Zhongyou Wen
  • Yu Shouzhi Scholarship for Academic Excellence (Top 1 among 800+).
  • First Prize in National Olympic in Informatics in Provinces.

Industrial 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.

Traveling

China

Keywords:
home, family, best food

USA

Keywords:
Alaska, road trip, national parks, corn fields

Canada

Keywords:
cold and vast, magnificent mountains and lakes

Mexico

Keywords:
tequila, hearty people, colorful and vivid towns

Caribbean

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

Chile

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

Peru

Keywords:
Amazon jungles, Machu Picchu, Inca trail, black beach

Ecuador

Keywords:
Galapagos, equatorial, overnight buses, lack of order

Bolivia

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

Cuba

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

Australia

Keywords:
magnificent ocean view, seafood, beef, mines, kangaroo

Qatar

Keywords:
rich, clean, dry-hot

UAE

Keywords:
oil, camel, artificial but great

Japan

Keywords:
snow powder, asian architecture, quiet people, omakase

Indonesia

Keywords:
swings, rice fields, hindu temples, instagram pictures

Malaysia

Keywords:
Semporna, scuba diving, jalan alor night food, massage

France

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

UK

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

Spain

Keywords:
Antoni Gaudi, paella, tapas, Sangria

Ireland

Keywords:
green, Guinness, windy, lively night life

Greece

Keywords:
Acropolis of Athens, white and blue, expensive and inefficient

Turkey

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

Nepal

Keywords:
namaste, temples, buddha, harshish

Thailand

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