Manos Papagelis

• Graph & Information Network Mining
• (Big) Data Mining & Analysis
• Databases & Knowledge Discovery
• Recommendation Algorithms, Trust & Personalization
• City Science/ Urban Informatics

Manos Papagelis is an Assistant Professor of Electrical Engineering  and Computer Science (EECS) at York University, Toronto, Canada. His  research falls is 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 & personalization, city science/urban informatics. Manos  holds a Ph.D. in Computer Science from the University of Toronto,  Canada, 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,  Canada.

• 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.