User:Jason Eisner

[January 2024] Jason Eisner is Professor of Computer Science at Johns Hopkins University, as well as Director of Research at Microsoft Semantic Machines. He is a Fellow of the Association for Computational Linguistics. At Johns Hopkins, he is also affiliated with the Center for Language and Speech Processing, the Mathematical Institute for Data Science, and the Cognitive Science Department. His goal is to develop the probabilistic modeling, inference, and learning techniques needed for a unified model of all kinds of linguistic structure. His 170+ papers have presented various algorithms for parsing, machine translation, and weighted finite-state machines; formalizations, algorithms, theorems, and empirical results in computational phonology; and unsupervised or semi-supervised learning methods for syntax, morphology, and word-sense disambiguation. He is also the lead designer of Dyna, a declarative programming language that provides an infrastructure for AI algorithms. He has received two school-wide awards for excellence in teaching, as well as recent Best Paper Awards at ACL 2017, EMNLP 2019, and NAACL 2021 and an Outstanding Paper Award at ACL 2022.