Mehdi Elahi (Postdoctoral Researcher)

Google Scholar
Flickr (photography)
SlideShare (presentations)

Short profile:

Mehdi Elahi received M.Sc. degree in Electrical Engineering (Sweden), and Ph.D. degree in Computer Science (Italy), under the supervision of Prof. Francesco Ricci. During the course of the Ph.D., he has researched on Recommender Systems (RSs), mainly focused on the cold start problem. He has designed, developed, and evaluated (offline/online) several personalized techniques for Active Learning in RSs that resulted in significant improvement over the state-of-the-art solutions (Ph.D. Thesis, and Presentation). These techniques were integrated in a mobile context-aware RS for tourism (South Tyrol Suggests), and a health-aware food RS (ChefPad).

As a result of his graduate research work, Mehdi Elahi served as a primary author or co-author on several publications in AI, ML, IR, HCI, UM, and UA related conferences (list of publications and downloadable  PDFs). He was also given the opportunity to publish his research findings in the form of five key publications, i.e., a book chapter in the second edition of Recommender Systems Handbook, an article in a top ACM journal (ACM-TIST), which is ranked #4 among 719 journals in Artificial Intelligence, an article in a top Springer journal (UMUAI), ranked #12 among 1000 journals in Computer Science,  a survey article in Computer Science Review journal, which is ranked #27 among 145 journals in Theoretical Computer Science, and an article in the journal of Data Semantics (JODS).

He also had the opportunity to work on several research projects, during his Ph.D. and Postdoc, comprising SUSDEM (Supporting Sequential Item Selection with Recommendation), SIPAI (Proactive Information Access Systems), and STS (South Tyrol Suggests). Moreover, he has been actively involved in preparation of three set of datasets:

He is currently working at Politecnico di Milano as a Postdoc researcher, under advisory of Prof. Paolo Cremonesi, and in collaboration with Prof. Franca Garzotto, researching on Recommender Systems, mainly focused on Mise-en-scène Project, and coordinating the work of four Ph.D. students. In addition to the research experience obtained during his doctoral work, he has co-invented a US-patent, submitted recently. He served as an organizer of the RecSys challenge 2017, as well as, the proceeding chair of the conference. He has worked as a laboratory instructor for both of the bachelor and master level courses at Libera Universita di Bolzano (1, 2) and Politecnico di Milano (1). He has also been invited to review submissions to various journals, listed below:

Journal Reviews

  • ACM Transactions on Interactive Intelligent Systems (TIIS)
  • ACM Transactions on the Web (TWEB)
  • ACM Journal on Computing and Cultural Heritage (JOCCH)
  • Springer journal of User Modeling and User-Adapted Interaction (UMUAI)
  • Springer journal of Multimedia Tools and Applications (MTAP)
  • Elsevier Expert Systems with Applications
  • Elsevier Information Sciences
  • Elsevier Information Processing and Management
  • Elsevier Journal of Systems and Software
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • IEEE Intelligent Systems
  • Journal of Interaction Studies
  • Journal of Interaction Design and Architecture (IxD&A)


MELAHI at KTH dot SE      or


Recommender systems @ PoliMi