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Tony Jebara is Associate Professor of Computer Science at
Columbia
University. He chairs the Center on Foundations of Data Science as well as directs the Columbia Machine Learning Laboratory. His
research intersects computer science and statistics to develop new
frameworks for learning from data with applications in social
networks, spatio-temporal data, vision and text. Jebara has founded and
advised several startups
including
Sense Networks (acquired by yp.com),
Evidation Health,
Agolo,
Ufora,
MagikEye,
and Bookt (acquired by RealPage NASDAQ:RP). He has published over
100 peer-reviewed papers in conferences, workshops and journals
including NIPS, ICML, UAI, COLT, JMLR, CVPR, ICCV, and AISTAT. He is
the author of the book Machine Learning: Discriminative and Generative
and co-inventor on multiple patents in vision, learning and
spatio-temporal modeling. In 2004, Jebara was the recipient of the
Career award from the National Science Foundation. His work was
recognized with a best paper award at the 26th International
Conference on Machine Learning, a best student paper award at the 20th
International Conference on Machine Learning as well as an outstanding
contribution award from the Pattern Recognition Society in 2001.
Jebara's research has been featured on television (ABC, BBC, New York
One, TechTV, etc.) as well as in the popular press (New York Times,
Slash Dot, Wired, Businessweek, IEEE Spectrum, etc.). He obtained his
PhD in 2002 from MIT. Esquire magazine named him one of their Best and
Brightest of 2008. Jebara has taught machine learning to a total of about
2000 students (through real physical classes).
Jebara will be General Chair for the 34th International Conference on Machine Learning (ICML) in 2017. He was a Program Chair for the 31st International Conference on Machine Learning (ICML) in 2014. Jebara was Action Editor for the Journal of Machine Learning Research from 2009 to 2013, Associate Editor of Machine Learning from 2007 to 2011 and Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence from 2010 to 2012. In 2006, he co-founded the NYAS Machine Learning Symposium and has served on its steering committee since then. Curriculum Vitae (PDF) Awards: IBM Faculty Award, 2013 Yahoo Faculty Award, 2011 Google Faculty Award, 2009 Best Paper Award, Intl. Conf. on Machine Learning, 2009 Esquire Magazine's Best and Brightest, 2008 KDD Challenge ER1B Best Performer, 2005 National Science Foundation Career Award, 2004 Best Student Paper Award, Intl. Conf. on Machine Learning, 2003 Pattern Recognition Society, Outstanding Contribution, 2001 Citation counts via Google Scholar. |
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