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NEWS
+ Co-organizing LLM+Vector Data workshop in ICDE'25.
+ ACM SIGMOD blog posts: LLM+KG+Vector Data, Graph Query.
+ Keynote talks at FAB@VLDB'24 [talk], GTA3@CIKM24.
+ Papers in SIGMOD'24, ICDE'24, TKDE'24.
+ Co-organizing LLM+KG workshop in VLDB'24.
+ 2 Papers in VLDB'23, 2 Papers in ICDE'23.
+ Paper in ACM SIGMOD Record'23.
+ Tutorial in DSAA'23.
+ Papers in ICDE'22, TKDE'22, TKDD'22.
+ Tutorial in CIKM'22.
+ Papers in VLDB'21, WWW'21.
+ Papers in SIGMOD'20, VLDB'20.
+ Papers in ICDE'20, WWW'20.
+ Papers in SIGMOD'19, VLDB'19.
+ Book in Morgan & Claypool
+ Papers in SIGMOD'18, VLDB'18.
+ Paper in USENIX ATC'18.



SERVICES
+ Editor: WWW Journal Special Issue on Neuro-Symbolic Intelligence: LLM Enabled Knowledge Engineering.
+ Associate Editor: IEEE TKDE (2019-2024), ACM TKDD (2023-present).
+ Co-organizer, Dagstuhl seminar on "Managing Vector Data for Retrieval Augmented Generation: Systems and Algorithms" (2026).
+ KDD 2025 PhD Consortium Track Co-chair, ICDE 2025 Demonstration Paper Track Co-chair, CIKM 2024 Short Paper Track Co-chair, ICDE 2023 TKDE Poster Track Co-chair, EDBT 2020 Proceedings chair.
+ Co-chair, LLM+Vector Data workshop (co-located with ICDE 2025), Co-chair, LLM+KG workshop (co-located with VLDB 2024), Co-chair, KG+Responsible AI workshop (co-located with CIKM 2024).
+ ACM IKDD CODS-COMAD 2024 Senior Program Committee (Distinguished SPC award).
+ 2026 PC: SIGMOD.
+ 2025 PC: SIGMOD, VLDB, KDD.
+ 2024 PC: SIGMOD (Distinguished PC award), VLDB, ICDE.
+ 2023 PC: VLDB, SIGMOD (Demo).
+ 2022 PC: SIGMOD, VLDB (Distinguished Reviewer award), ICDE.

New: I have multiple openings for PhD, Postdoc, and RA positions. Interested candidates can contact me with CV.

PhD Application Link. Postdoc Application Link. RA Application Link.

Research Interests:

    Data management and Artificial Intelligence for the emerging problems in large graphs, with a focus on user-friendly, efficient, approximate, and explainable querying and pattern mining in social and information networks, using scalable algorithms, machine learning techniques, and distributed systems.
    Keywords: big graphs, big data, graph systems, knowledge graphs, uncertain graphs, graph streams, databases, data mining, machine learning, explainable AI, algorithms, blockchain networks analysis.

Education and Work Experience:

 

Honors and Awards:

  • Invited to give keynote talks at FAB@VLDB'24 [talk] and GTA3@CIKM24 workshops.

  • SIGMOD 2024 Distinguished PC award.

  • Invited to give a talk at Machine Learning Theory workshop, co-located with the Danish Digitalization, Data Science and AI conference 2024 (D3A’24).

  • CODS-COMAD 2024 Research Track Distinguished Senior PC Member Award.

  • Appointed as an ACM Distinguished Speaker (2023-2025).

  • Elevated to the grade of IEEE Senior member.

  • PVLDB 2022 Distinguished Reviewer award.

  • Our IEEE Blockchain 2022 paper "Graph Analysis of the Ethereum Blockchain Data: A Survey of Datasets, Methods, and Future Work" is featured in Research Pulse #72 by the Smart Contract Research Forum (SCRF).

  • Invited as a Panel Expert for graph data management in ICDE 2022.

  • Recognized by Aminer among the Most Influential Scholar Award Honorable Mention for outstanding and vibrant contributions to the field of Database between 2010 and 2020.

  • My PhD student Xiangyu Ke, graduated in 2020, is awarded Honourable Mention for the NTU SCSE Outstanding PhD Thesis Award.

  • Invited to lead a panel discussion among industry leaders on synergies between data analytics and machine learning at the 3rd Edition of GFMI Conference Optimizing Data Governance, Quality and Consistency in Financial Services, Singapore (March 2019).

  • Invited for National Institute of Informatics (NII) Shonan Meeting on "Graph Database Systems: Bridging Theory, Practice, and Engineering", 2018, Japan.

  • Invited to contribute a chapter on graph pattern matching in the "Springer Encyclopedia of Big Data Technologies".

  • Invited to present a tutorial in the Asia Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data (APWeb-WAIM 2017).

  • Invited to contribute an article in the ACM SIGMOD Blog.

  • Invited to present a tutorial on uncertain graphs in the International Conference on Management of Data (COMAD 2016).

  • Invited to submit an extended version of our VLDB 2015 tutorial as a book in Morgan & Claypool's Data Management series.

  • Invited to contribute a chapter on big-graphs processing in the "Springer Handbook on Big-Data Technologies".

  • Part of our VLDB 2014 Tutorial on Big-Graphs Systems included in the Large Scale Data Management (CS 848) Course 2015, University of Waterloo.

  • Invited for Dagstuhl Seminar 2014, Schloss Dagstuhl - Leibniz Center for Informatics, Germany [talk].

  • NSF ICDE 2012 Scholarship.

  • IBM Ph.D. Fellowship 2012-13.

  • NSF SDM (SIAM Conference of Data Mining) 2011 Student Travel Award.

  • P1 fellowship 2009-10, Computer Science, University of California, Santa Barbara.

  • CITRIX GO-TO fellowship 2008-2009, Computer Science, University of California, Santa Barbara.

  • TCS-JU Best Student Award 2007-08, an award honoring the best graduting undergraduate in the CS department at Jadavpur University.