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I am a postdoc in the Data Science and Mining team (DaSciM) of Prof. Michalis Vazirgiannis. The group is part of the Computer Science Laboratory (LIX) of École Polytechnique, in Palaiseau, France.

My interests overspan all aspects of Artificial Intelligence, Deep Learning and applied Machine Learning. I'm especially interested in the relationship between graphs and text. Indeed, graphs can be represented as documents, and documents can be represented as graphs, so methods from graph theory can be applied to NLP and inversely. In particular, my research deals with (un)supervised traditional/neural graph processing and mining, and how using graph structures can boost the performance of various NLP tasks, such as keyword(phrase) extraction, extractive/abstractive summarization, and text categorization.

I received my PhD from the University of Colorado at Boulder in the Spring of 2015, under the supervision of Matt Hallowell (primary advisor) and Balaji Rajagopalan. I applied NLP, predictive modeling and probability theory to raw textual injury reports, in order to better understand and forecast construction injuries. My work was funded by the NSF and major American construction companies. Before that, I obtained a MS in Construction Engineering & Management (CU Boulder 2013) and a MS in Electrical & Mechanical Engineering (ESTP Paris 2011).

I served as a reviewer for CIKM 2016, WSDM 2017 and AAAI 2017.


I have been very fortunate and learned a lot from collaborating with the great persons listed below (in chronological order). Thanks to all of them!

Matt Hallowell (CU Boulder), Alex Albert (NC State), Leaf Van Boven (CU Boulder), Balaji Rajagopalan (CU Boulder), Michalis Vazirgiannis (École Polytechnique), Konstantinos Skianis (École Polytechnique), Fragkiskos D. Malliaros (UC San Diego), Polykarpos Meladianos (AUEB), Giannis Nikolentzos (AUEB), Maria Rossi (École Polytechnique), and Jesse Read (École Polytechnique).