Hynek is affiliated with the Center for Language and Speech Processing, where he served as Director from 2010 to 2022. He is also affiliated with the Human Language Technology Center of Excellence. He is on the faculty of the Brno University of Technology, Czech Republic. Hynek is a Life Fellow of the Institute of Electrical […]
Daniel Khashabi is an assistant professor in computer science at Johns Hopkins University. Khashabi’s work focuses on computational foundations of intelligent behavior within various mediums of communication, particularly natural language. This involves developing formalisms that characterize and result in natural language processing (NLP) systems that are capable of understanding and reasoning with (and about) an […]
Sanjeev Khudanpur, an associate professor of electrical and computer engineering, is known for applying information theory, statistics, and deep learning to human language technologies, including automatic speech recognition, machine translation, and natural language processing. His research was pivotal in the creation of the Amazon Echo/Alexa and several other technological successes, and in advancing the development […]
Koehn’s work is currently focused on statistical machine translation (video), a subject on which he also wrote the textbook and maintains the website. More broadly, his interest is to make use of the vast amount of information that is available in digital form. He was one of the finalists for the 2013 European Inventor Award.
Vishal M. Patel is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at Johns Hopkins University. Prior to joining Hopkins, he was an A. Walter Tyson Assistant Professor in the Department of ECE at Rutgers University and a member of the research faculty at the University of Maryland Institute for Advanced […]
Saria’s interests span machine learning, computational statistics, and its applications to domains where one has to draw inferences from observing a complex, real-world system evolve over time. The emphasis of her research is on Bayesian and probabilistic graphical modeling approaches for addressing challenges associated with modeling and prediction in real-world temporal systems. In the last […]
Dr. Yarowsky’s research focuses on word sense disambiguation, minimally supervised induction algorithms in NLP, and multilingual natural language processing. He earned his bachelor’s (’87) in computer science at Harvard University and his master’s (’93) and PhD (’96) in computer and information science at the University of Pennsylvania.
