Elad Yom-Tov is a Principal Researcher at Microsoft Research and a visiting scientist at the Technion, Israel. Before joining Microsoft he was with Yahoo Research, IBM Research, and Rafael. Dr. Yom-Tov studied Electronical Engineering at Tel-Aviv University and the Technion, Israel. He has published three books, over 60 papers (of which 3 were awarded prizes), and filed more than 30 patents (16 of which have been granted so far). He is a Senior Member of IEEE and held the title of Master Inventor while at IBM.

Elad’s primary research interest is in using Machine Learning and Information Retrieval to improve health, through the use of Internet data. Internet data such as social media postings and search engine queries are an important source for medical information, especially when collecting relevant data is hard or impossible using more traditional means, when the relevant activity takes place online, and when a more delicate sensor than that afforded by traditional medical information sources is needed. Examples of his work in this area include the discovery of a new class of side effects of drugs (using search engine logs), linking the portrayal of celebrities with the development of eating disorders (using search engine logs and social media data), and validating the usefulness of vaccination campaigns. 


Selected Publications

  1.  E. Yom-Tov, I. Johansson-Cox, V. Lampos, A.C. Hayward (2015) "Estimating the Secondary Attack Rate and Serial Interval of Influenza-like Illnesses using Social Media" Influenza and Other Respiratory Viruses 9(4): 191-199
  2.  E. Yom-Tov, S. Dumais, Q. Guo (2013) "Promoting civil discourse through search engine diversity" Social Science Computing Review 32(2): 145-154
  3.  E. Yom-Tov, E. Gabrilovich (2013) "Post-market drug surveillance sans trial costs: Discovery of adverse drug reactions via large-scale analysis of Web search queries" Journal of Medical Internet Research (JMIR) 15(6): e124.
  4.  E. Yom-Tov, F. Diaz (2011) "Out of sight, not out of mind: On the effect of social and physical detachment on information need" Proceedings of the 34th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2011), Beijing, China. pp. 385-394 Recipient of an Honourable Mention Award
  5.  E. Yom-Tov, S. Fine, D. Carmel, A. Darlow (2005) "Learning to Estimate Query Difficulty with Applications to Missing Content Detection and Distributed Information Retrieval", 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2005), Salvador, Brazil. pp. 512-219. Recipient of the Best Paper Award
  6. H. Serbi, E. Yom-Tov, and G.F. Inbar (2005) "An improved P300-based brain-computer interface". IEEE Transactions on Neural Systems and Rehabilitation Engineering 13(1): 89-98. Recipient of the TNSRE Best Paper Award 2010


machine learning, information retrieval

user generated content for health and medicine

Contact Info

Room 518 Bloomfield Building