Jason Eisner, a professor of computer science, is affiliated with the Center for Language and Speech Processing and the Human Language Technology Center of Excellence, and leads JHU’s cross-departmental machine learning group. His goal is to develop the probabilistic modeling, inference, and learning techniques needed for a unified model of all kinds of linguistic structure. Eisner has written more than 100 papers in several areas of computational linguistics, especially parsing, grammar induction, machine translation, computational phonology, computational morphology, and weighted finite-state methods. He is also the lead designer of Dyna, a new declarative programming language that provides an infrastructure for AI research. He joined Johns Hopkins University in 2000.
He has a secondary appointment in the Department of Cognitive Science at the Krieger School of Arts and Sciences.
Eisner received an AB in Psychology from Harvard University in 1990; a BA/MA in Mathematics at the University of Cambridge (UK) in 1993; and a PhD in Computer Science at the University of Pennsylvania in 2001.