Khaled Ammar


Khaled is a Data Scientist at Thomson Reuters Innovation Labs. He creates innovative applications for legal, governance, regulation and tax use cases. Before joining Thomson Reuters Innovation Labs, he was a research engineer at the Cognitive Computing Center, the R&D technical team for Thomson Reuters.

Khaled’s research interests are motivated by real-life data processing and understanding, specifically data analytics over large and dynamic graphs. His research focuses on three aspects of this problem. The first focus is on identifying potential graph structures in business data, extracting these graphs, and proposing innovative solutions for different use cases. The second is studying dynamic graphs, which are graphs that change over time. He is developing data structures, algorithms, and systems for efficient analytics over multiple releases of a graph. The third aspect is scalability to very large graphs, where he is investigating parallel and distributed systems.

Khaled is also working on his Ph.D. at the Cheriton School of Computer Science at the University of Waterloo under the supervision of Prof. Tamer Ozsu. His thesis studies distributed systems for graph data processing with emphasis on large dynamic graphs. He has published multiple papers in VLDB, SIGMOD, and BigData, spoken at industry conferences such as Strata and won academic awards such as OGS and IBM CAS Fellowship.

Feel free to contact me by email: [after removing all instances of 123]

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