I was an associate research professor in the computer science department. I am on the editorial boards of Computational Linguistics and TACL and I am the Chairman of NAACL. My research focuses on statistical machine translation, crowdsourcing, and broad coverage semantics via paraphrasing. I have contributed to the research community by releasing open source software like Moses and Joshua, and by organizing the shared tasks for the annual Workshop on Statistical Machine Translation. I accepted a tenure-track position at the University of Pennsylvania, which started in September 2013.
I am now at IBM. While at Hopkins I was the Chief Scientist of the Human Language Technology Center of Excellence. I am the president of the Association for Computational Linguistics (ACL), and I was the longest-serving president of SIGDAT (special interest group that organizes EMNLP conferences). Prior to Hopkins, I was a researcher at Microsoft Research in Redmond, and before that I was the head of a data mining department in AT&T Bell Labs. I have worked on many topics in computational linguistics including: web search, language modeling, text analysis, spelling correction, word-sense disambiguation, terminology, translation, lexicography, compression, speech (recognition and synthesis), and optical character recognition. I was present at the dawn of UNIX. It was like 2001:A Space Odyssey but with fewer apes.
I am a research scientist at the HLTCOE and an assistant research scientist with ECE, with my work spanning a number of disciplines. The commonalities are statistical pattern recognition, graph theory, data fusion, semi-supervised learning, and/or computational linguistics. I also tend to shy away from curated and cared-for datasets, instead preferring the wild-west of the real world. This may be in part due to my appreciation for the outdoors, especially water. I am a kayaker, rock climber, photographer, and SCUBA diver.
I am a research scientist at the HLTCOE and an assistant research professor in the ECE department. My research explores various aspects of the speech recognition problem, with a focus on whole word acoustic modeling, sparse representations and models, and unsupervised/semi-supervised learning of words and speech sounds. Lately, I have been focused on developing zero resource speech technologies that require no transcribed speech for training and are thus agnostic to the language of application.
Frederick Jelinek was the director of the Center for Language and Speech Processing from 1993 until his death in 2010. His research laid the foundation for modern speech recognition and machine translation. See this link for details about his life and his work.
I am a now a research scientist at BBN. During my 7 years at Hopkins, I served as a researcher at CLSP and the HLTCOE and as an assistant research professor in the ECE department. My research focuses on statistical and information-theoretic aspects of speech recognition and natural language processing, with an emphasis on language modeling, document categorization, and techniques for cross-instance tuning of statistical models.
I am on the faculty at the University of Edinburgh. I worked in CLSP until November 2014, and I retain a courtesy appointment until May 2015 to continue working with my students there, but I will not be taking new students at JHU. My research focuses on technology that will break the language barrier, in particular systems that learn to translate from big data (like Google Translate, Bing Translator, and SDL Free Translation), and their integration with speech and search technologies. Improvements to these systems depend on extensions and applications of machine learning, formal language theory, linguistics, and algorithms. I am interested in many problems in these fields.
I am a research scientist at the Human Language Technology Center of Excellence at Johns Hopkins University. My research focuses on the understanding and recognition of subjective and opinionated language. I can tell you how many stars your restaurant will get on Yelp.