Tony Jebara is Associate Professor of Computer Science at
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
and Bookt. 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 well over
1000 students (through real physical classes).
Jebara is Associate Editor for the Journal of Machine Learning Research and on the Editorial Board of Machine Learning. Jebara was 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. Jebara will be a Program Chair for the 31st International Conference on Machine Learning (ICML) in 2014.
Curriculum Vitae (PDF)
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.