- Electrical Engineering & Computer Science
- Graph & Information Network Mining
- (Big) Data Mining & Analysis
- Databases & Knowledge Discovery
- Recommendation Algorithms, Trust & Personalization
- City Science/ Urban Informatics
Dr. Manos Papagelis is an Assistant Professor of Electrical Engineering and Computer Science (EECS) at York University. His research falls in the area of data science, with particular interest in graph and information network mining, (big) data mining and analysis, databases and knowledge discovery, recommendation algorithms and personalization, city science/urban informatics. Dr. Papagelis holds a PhD in Computer Science from the University of Toronto and a M.Sc. and a B.Sc. in Computer Science from the University of Crete, Greece. Before joining York University, he was a postdoctoral research scholar at the University of California, Berkeley. In the past, he has worked at Yahoo! Labs, Barcelona as a research intern and at the Institute of Computer Science, FORTH, Greece as a research fellow. His research has appeared in ACM trans. on knowledge discovery from data (ACM TKDD) and IEEE Trans. on knowledge and data engineering (IEEE TKDE), he has filed three U.S. patent applications and is the software architect of two large-scale online systems - a conference management system and a system for socio-technical analysis of green buildings. He has taught at the University of California, Berkeley and at the University of Toronto.
- Papagelis, M. (2015). Refining social graph connectivity via shortcut edge addition. ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 10(2), 12.
- Papagelis, M., Das, G., & Koudas, N. (2013). Sampling online social networks. IEEE Transactions on knowledge and data engineering (IEEE TKDE), 25(3), 662-676.
- Doerr, M., & Papagelis, M. (2007). A method for estimating the precision of placename matching. IEEE transactions on knowledge and data engineering (IEEE TKDE), 19(8), 1089-1101.