NEWS + Paper in SIGMOD'19.
+ Paper in VLDB'19.
+ Book in Morgan & Claypool Synthesis Lectures on Data Management.
+ 2 Papers in TKDE'19 & '18.
+ Paper in SIGMOD'18.
+ Demo in VLDB'18.
+ Paper in USENIX ATC'18.
+ Paper in ICDE'18.
+ 2 Papers in IEEEBigData'18.
+ Book chapter in Encyclopedia of Big Data Technologies'18.
+ Tutorial in VLDB'17.
+ ACM SIGMOD blog post.
Data management for the emerging problems in large graphs, with a focus on user-friendly, efficient, and approximate 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, algorithms, crowdsourcing.
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.