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(suitable for including with talk announcements)
Jason Eisner is Associate Professor of Computer Science at Johns Hopkins University, where he is also affiliated with the Center for Language and Speech Processing, the Cognitive Science Department, and the national Center of Excellence in Human Language Technology. He is particularly interested in designing algorithms that statistically exploit linguistic structure. His 60+ papers have presented a number of algorithms for parsing and machine translation; algorithms for constructing and training weighted finite-state machines; formalizations, algorithms, theorems and empirical results in computational phonology; and unsupervised or semi-supervised learning methods for domains such as syntax, morphology, and word-sense disambiguation.
Jason was born in Ithaca, New York and grew up in suburban New Jersey. His undergraduate major at Harvard University (summa cum laude, junior-year election to Phi Beta Kappa) was in the Cognitive Science track of the Psychology Department.
After a year in South Africa during its political transition, on a Fulbright Scholarship in Creative Writing, he spent two years at Cambridge University on a Herchel C. Smith Scholarship, where he earned a second undergraduate degree, this time in Mathematics (first-class honors).
His Ph.D. in Computer Science (on an NSF fellowship) was at the University of Pennsylvania, under Mitch Marcus. He also spent a good deal of time in Penn's Linguistics Department. He joined the University of Rochester as an assistant professor, then moved to Johns Hopkins University (JHU) soon afterward.
At JHU, he is a (tenured) Associate Professor of Computer Science, with a joint appointment in Cognitive Science. He is also a core member of the Center for Language and Speech Processing, and an affiliate of the national Center of Excellence in Human Language Technology at JHU. He is the recipient of an NSF CAREER Award as well as other funding from NSF and DoD. He has also received JHU's Robert B. Pond, Sr. Excellence in Teaching Award.
Jason has authored over 60 papers (as well as software tools) in several areas of computational linguistics, including parsing, machine learning (including grammar induction), machine translation, weighted finite-state methods, and computational phonology. He is the lead designer of the Dyna programming language, the Dopp programming language parser, and the Dynasty hypergraph browser. His voice can be heard as the top hit for the admittedly rare query parsing song, and he's had some other work-related fun, such as investing in Lernout & Hauspie a week before they crashed in a scandal. His hobbies include playing violin and squash (not at the same time), singing show tunes to his kids Talia and Lev, biking to work, reading, and sometimes rock climbing with his wife Debbie.
Jason has also contributed much to the NLP community's conference and publications practices, and has served in various roles such as program chair, area chair, workshop chair, editorial board member, SIGMORPHON president, NACLO problem committee member, invited speaker, and general kibitzer.
For a "biography" of Jason's technical work, see his research summary and earlier research narrative. His many professional activities and papers are listed on his full CV.
