Yoav Artzi is a graduate student in the department of Computer Science & Engineering at the University of Washington. His advisor is Luke Zettlemoyer. Yoav received a BSc in Computer Science from Tel Aviv University. In summer 2011, he was an intern at Microsoft Research, where he worked with Patrick Pantel and Michael Gamon. In summer 2013, he will intern with Slav Petrov and Dipanjan Das at Google Research. His current research is in the intersection of natural language processing, machine learning and learning through interaction, with specific interest in situated/grounded language acquisition and natural language dialog.
Andrei Barbu is a Ph.D. student in the School of Electrical and Computer Engineering at Purdue University working with Jeffrey Mark Siskind. He received a BCS from the University of Waterloo. His work focuses on how language can facilitate high-level reasoning across multiple scenarios and modalities as well as the neural representation and manipulation of linguistic concepts. This work combines language, vision, and robotics to understand, describe, and manipulate objects, learn to play games, and recognize actions, and uses neuroimaging to understand the representation of language in the human brain.
Alex Berg's research concerns computational visual recognition. He has worked on general object recognition in images, action recognition in video, human pose identification in images, image parsing, face recognition, image search, and machine learning for computer vision. He co-organizes the ImageNet Large Scale Visual Recognition Challenge, and organized the Large Scale Learning for Vision workshop in 2011. He is currently an assistant professor in computer science at UNC Chapel Hill. Prior to that he was on the faculty at Stony Brook University, a research scientist at Columbia University, and research scientist at Yahoo! Research. His PhD at U.C. Berkeley developed a novel approach to deformable template matching. He earned a BA and MA in Mathematics from Johns Hopkins University and learned to race sailboats at SSA in Annapolis.
Tamara Berg received her B.S. in Mathematics and Computer Science from the University of Wisconsin, Madison in 2001. She then completed a PhD in Computer Science from the University of California, Berkeley in 2007 under the advisorship of Professor David Forsyth as a member of the Berkeley Computer Vision Group. Afterward, Tamara spent one year as a research scientist at Yahoo! Research. In 2008-2013 Tamara was an Assistant Professor in the Computer Science department at Stony Brook University and core member of the consortium for Digital Art, Culture, and Technology (cDACT). This Fall she is moving the University of North Carolina, Chapel Hill. Tamara's research straddles the boundary between Computer Vision and Natural Language Processing with applications to large scale recognition, retrieval, and social network analysis.
Dan Bohus is a Researcher in the Adaptive Systems and Interaction Group at Microsoft Research. The central question that drives his long term research agenda is: how can we develop systems that naturally embed interaction and computation deeply into the flow of everyday tasks, activities, and collaborations? Specifically, in the last few years Dan's work has focused on developing computational models for multiparty engagement, turn taking, interaction planning, and on addressing the challenges in inference and decision making that such models bring to the fore. Prior to joining Microsoft, Dan obtained his Ph.D. degree from Carnegie Mellon University, where he investigated problems of dialog management and error handling in speech interfaces.
Antoine Bordes is a CNRS researcher in the Heudiasyc laboratory of the University of Technology of Compiegne in France. In 2010, he was a postdoctoral fellow in Yoshua Bengio's lab of Universite de Montreal. He received his PhD in machine learning from Pierre & Marie Curie University in Paris in early 2010. From 2004 to 2009, he collaborated regularly with the Machine Learning department of NEC Labs of America in Princeton. He received two awards for best PhD from the French Association for Artificial Intelligence and from the French Armament Agency. Antoine's current research concerns large-scale machine learning applied to natural language processing and information extraction, and is funded by the French National Research Agency.
Elia Bruni is a graduate student in the Language, Interaction and Computation Lab at the University of Trento. His research is in the areas of natural language processing, computer vision and machine learning. He is interested in grounding the meaning of words in the visual world by extracting distributional semantic models from pictures and merging them with traditional text-based semantic representations.
Maya Cakmak is a post-doctoral research fellow at Willow Garage. She received her Ph.D. in Robotics from the Georgia Institute of Technology in 2012. Her research interests are at the intersection of Human-Robot Interaction and Programming by Demonstration. In particular, her research aims to develop functionalities and interfaces for personal robots that can be programmed by their end-users to assist everyday tasks. Maya's work has been published at major Robotics and AI conferences and journals, demonstrated live in various venues and has been featured in numerous media outlets.
Joyce Chai is a professor of computer science and engineering at Michigan State University. She received Ph.D. in Computer Science from Duke University in 1998. Prior to joining MSU in 2003, she was a Research Staff Member at IBM T. J. Watson Research Center. Her research interests include natural language processing and situated dialogue agents. In particular, she is interested in incorporating the context of language use (e.g., linguistic/visual discourse, non-verbal modalities) into language understanding systems and their applications in situated interaction.
Bill Dolan is a Principal Researcher in Microsoft Research, where he manages the Natural Language Processing group. His undergraduate degree is from UC Berkeley, and his Ph.D. is from UCLA Linguistics. His long-term research interest has been "the paraphrase problem": when do superficially dissimilar strings of words convey essentially the same meaning? Learning to identify and generate such alternations is key to developing applications that appear to understand human language, and we've done some interesting work in this area. He has also been active in helping establishing the Recognizing Textual Entailment challenges, which address a closely related problem. In addition, He's worked extensively on Machine Translation, managing the Microsoft Translator team from its inception until 2011.
Brian Dolhansky is currently a first-year graduate student in the Computer and Information Science Department at the University of Pennsylvania, but will be transferring to UW in the Fall. He is advised by Ben Taskar. He received a BS/MS from Drexel University, where he studied signal processing and large-scale music information retrieval. His interests lie in theoretical machine learning and its applications. Currently he is working on prioritized stochastic gradient descent in addition to eye gaze estimation with the Microsoft Kinect. In the future, he hopes to incorporate this work into the larger framework of grounded perception.
Ali Farhadi is an Assistant Professor in the Department of Computer Science & Engineering at the University of Washington. Before this, he spent a year as a Postdoctoral Fellow in the Robotics Institute at Carnegie Mellon Universiy working with Martial Hebert and Alyosha Efors. Ali got his PhD from the Computer Science Department of the University of Illinois at Urbana-Champaign under the supervision of David Forsyth. During his PhD, he also had the privilege of working closely with Derek Hoiem. He is mainly interested in Computer Vision, Machine Learning, the intersection of Natural Language and Vision, and analysing the role of Semantics in Visual Understandings.
Nicholas FitzGerald is a Ph.D student in Computer Science & Engineering at the University of Washington. His advisor is Luke Zettlemoyer. Nicholas is working on semantic Natural Language Processing and Grounded Language acquisition. He is supported by an Intel Science and Technology Center Fellowship. He received a Bachelor of Science in Cognitive Systems from UBC. During that time, he worked with Giuseppe Carenini and the Summarization Group on abstractive summarization techniques in a variety of domains, including conversations and blogs.
Hanna Hajishirzi is a research scientist at University of Washington. Prior to that, she spent a year as a postdoctoral research associate at Carnegie Mellon University and Disney Research. She received her PhD in 2011 from the Computer Science department at the University of Illinois at Urbana-Champaign. Her research interests are at the intersection of Natural Language Processing, Machine Learning, and Artificial Intelligence. Her current research is mainly focused on semantic language processing, grounded language acquisition, and designing automatic language-based interactive systems. Her prior research was on designing statistical relational frameworks to learn, control, and reason about complex dynamic domains.
Larry Heck is a Distinguished Engineering and researcher in Microsoft Research. His research area is natural conversational interaction, focusing on open-domain NLP and dialog, machine learning, multimodal NUI, and inference/reasoning under uncertainty. From 2005 to 2009, he was Vice President of Search & Advertising Sciences at Yahoo!, responsible for the creation, development, and deployment of the algorithms powering Yahoo! Search, Yahoo! Sponsored Search, Yahoo! Content Match, and Yahoo! display advertising. From 1998 to 2005, he was with Nuance Communications and served as Vice President of R&D, responsible for natural language processing, speech recognition, voice authentication, and text-to-speech synthesis technology. He began his career as a researcher at the Stanford Research Institute (1992-1998), initially in the field of acoustics and later in speech research with the Speech Technology and Research (STAR) Laboratory.
Julia Hockenmaier is an assistant professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Her main area of research is computational linguistics or natural language processing. Before coming to Illinois, she was a postdoc with Aravind Joshi at the Institute for Research in Cognitive Science at the University of Pennsylvania, and also a frequent visitor to Ken Dill's research group at UCSF. Before that, she did a PhD in Informatics at the University of Edinburgh with Mark Steedman.
Eric Horvitz is a Distinguished Scientist at Microsoft Research. His interests span theoretical and practical challenges with developing systems that perceive, learn, and reason. His research includes exploration of principles for meshing machine and human intelligence, including the use of machine learning and decision-theoretic procedures in studies of crowdsourcing and human computation. He has been elected a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and of the American Academy of Arts and Sciences. He serves on the NSF Computer & Information Science & Engineering (CISE) Advisory Board and on the council of the Computing Community Consortium (CCC). He received his PhD and MD degrees at Stanford University.
Ece Kamar is a researcher in the Adaptive Systems and Interaction group at Microsoft Research, Redmond. Her research interests include human-computer collaboration, decision-making under uncertainty, and mechanism design with a focus on real-world applications that bring people and adaptive agents together. She is in particular interested in building collaborative systems for assisting users in mobile domains and for solving crowdsourcing tasks. Ece received a Ph.D. in computer science from Harvard University in 2010. Her thesis focused on reasoning under uncertainty for successful human-computer teamwork. She received a M.S. from Harvard University in 2007 and a B.S. from Sabanci University in Turkey in 2005.
Geert-Jan Kruijff is an NLP Research Manager at Nuance Communications. In 1995 he obtained his engineering title ("ir") from the University of Twente, in Enschede (The Netherlands), where his degree combined computer science and analytical philosophy. During his studies he spent some time at Texas Tech University, working on abductive reasoning. From about 1995 until 2001 he worked at the School of Informatics, at Charles University in Prague (Czech Republic). During that time he also spent a year and a half in Edinburgh (Scotland). In 2001 he obtained a PhD in informatics/mathematical linguistics from Charles University. From 2001 until 2004 he led a project at the Department of Computational Linguistics at Saarland University. In late 2004 he moved to DFKI, to lead several international projects on human-robot interaction. Besides his academic interests in human-robot interaction, he also has a strong interest in project leadership, R&D strategy development, and financial aspects of R&D portfolio management. In Spring 2013 he joined Nuance Communications Germany GmbH in Aachen.
Mirella Lapata is a professor in the School of Informatics at the University of Edinburgh. She is affiliated with the Institute for Communicating and Collaborative Systems and the Human Communication Research Centre. Her research focuses on probabilistic learning techniques for natural language understanding and generation.
Rebecca Mason is a PhD candidate at Brown University. She works with the Brown Laboratory for Linguistic Information Processing, and her advisor is Eugene Charniak. Rebecca's research aims to bridge the gap between semantic representations of data and how those data are interpreted by users in a given situation. Some particular tasks she is interested in are image caption generation, multi-document summarization, and evaluation of generated text.
Cynthia Matuszek is a Ph.D. candidate in Computer Science and Engineering at the University of Washington. Her research focuses on studying how robots can interact robustly in unconstrained real-world settings, including interactions with non-expert end-users. She received a B.S. from the University of Texas at Austin and an M.Sc. from the University of Washington.
Margaret Mitchell is a postdoctoral researcher at The Johns Hopkins University Center of Excellence working on semantic role labeling and sentiment analysis using graphical models. Previously, she was a postgraduate student in the natural language generation (NLG) group at the University of Aberdeen. As a student, she worked on generating human-like descriptions of real-world objects. She also spent the past few years as a visiting scholar at the Center for Spoken Language Understanding, part of OHSU, in Portland, Oregon. There, she worked on understanding the syntactic and phonetic characteristics in the language of people with neurological disorders.
Raymond J. Mooney is a professor in the Department of Computer Science at the University of Texas at Austin. He received his Ph.D. in 1988 from the University of Illinois at Urbana/Champaign. He is an author of over 150 published research papers, primarily in the areas of machine learning and natural language processing. He was the president of the International Machine Learning Society from 2008-2011 and is a AAAI and ACM Fellow. His recent research has focused on learning for natural-language processing, statistical relational learning, active transfer learning, and connecting language, perception and action.
Louis-Phillippe Morency is a Research Assistant Professor in the Department of Computer Science at the University of Southern California (USC) and Research Scientist at the USC Institute for Creative Technologies where he leads the Multimodal Communication and Machine Learning Laboratory (MultiComp Lab). He received his Ph.D. and Master degrees from MIT Computer Science and Artificial Intelligence Laboratory. His research interests are in computational study of nonverbal social communication, a multi-disciplinary research topic that overlays the fields of multimodal interaction, computer vision, machine learning, social psychology and artificial intelligence. Dr. Morency was selected in 2008 by IEEE Intelligent Systems as one of the Ten to Watch for the future of AI research. He received 6 best paper awards in multiple ACM- and IEEE-sponsored conferences for his work on context-based gesture recognition, multimodal probabilistic fusion and computational modeling of human communication dynamics. His work was reported in The Economist, New Scientist and Fast Company magazines.
Hoifung Poon is a researcher at Microsoft Research. His research interests are in advancing machine learning and natural language processing to automate discovery in genomics and personalized medicine. His most recent work focuses on advancing semantic parsing to extract biological pathways from Pubmed with indirect supervision, and on developing probabilistic methods to integrate pathways with high-throughput genomics data in cancer systems biology. He has received Best Paper Awards in NAACL, EMNLP, and UAI.
Chris Quirk is a senior researcher at MSR. After studying Computer Science and Mathematics at Carnegie Mellon University, he joined Microsoft in 2000 to work on the Intentional Programming project, an extensible compiler and development framework. He moved to the Natural Language Processing group in 2001, where his research has mostly focused on statistical machine translation powering Microsoft Translator, especially on several generations of a syntax directed translation system that powers over half of the translation systems. Chris is also interested in semantic parsing, paraphrase methods, and very practical problems such as spelling correction and transliteration.
Dan Roth is a Professor in the Department of Computer Science and the Beckman Institute at the University of Illinois at Urbana-Champaign and a University of Illinois Scholar. Roth is a Fellow of the ACM, AAAI, and ACL, for his contributions to the foundations of machine learning and inference and for developing learning centered solutions for natural language processing problems. He has published over 250 articles in machine learning, natural language processing, knowledge representation and reasoning and learning theory, and has developed advanced machine learning based tools for natural language applications that are being used widely by the research community. Professor Roth received his B.A Summa cum laude in Mathematics from the Technion, Israel and his Ph.D in Computer Science from Harvard University in 1995.
Bryan Russell is a Research Scientist/Researcher-in-Residence as part of the Intel Science and Technology Center for Visual Computing (ISTC-VC) and holds a courtesy Affiliate Professor appointment in the Department of Computer Science & Engineering at the University of Washington. He received his Ph.D. from MIT in the Computer Science and Artificial Intelligence Laboratory in 2008 under the supervision of Professors William T. Freeman and Antonio Torralba. He was a post-doctoral fellow from 2008-2010 in the INRIA Willow team at the Departement d'Informatique of Ecole Normale Superieure in Paris, France.
Steve Seitz is a Professor in the Department of Computer Science & Engineering at the University of Washington. He also directs an imaging group at Google's Seattle office. He received his B.A. in computer science and mathematics at the University of California, Berkeley in 1991 and his Ph.D. in computer sciences at the University of Wisconsin in 1997. Following his doctoral work, he spent one year visiting the Vision Technology Group at Microsoft Research and the subsequent two years as an Assistant Professor in the Robotics Institute at Carnegie Mellon University. He joined the faculty at the University of Washington in July 2000. He was twice awarded the David Marr Prize for the best paper at the International Conference of Computer Vision, and he has received an NSF Career Award, and ONR Young Investigator Award, and an Alfred P. Sloan Fellowship, and is an IEEE Fellow. His work on Photo Tourism (joint with Noah Snavely and Rick Szeliski) formed the basis of Microsoft's Photosynth technology. Professor Seitz is interested in problems in computer vision and computer graphics. His current research focuses on 3D modeling and visualization from large photo collections.
Jeffrey M. Siskind received the B.A. degree in computer science from the Technion, Israel Institute of Technology, Haifa, in 1979, the S.M. degree in computer science from the Massachusetts Institute of Technology (M.I.T.), Cambridge, in 1989, and the Ph.D. degree in computer science from M.I.T. in 1992. He did a postdoctoral fellowship at the University of Pennsylvania Institute for Research in Cognitive Science from 1992 to 1993. He was an assistant professor at the University of Toronto Department of Computer Science from 1993 to 1995, a senior lecturer at the Technion Department of Electrical Engineering in 1996, a visiting assistant professor at the University of Vermont Department of Computer Science and Electrical Engineering from 1996 to 1997, and a research scientist at NEC Research Institute, Inc. from 1997 to 2001. He joined the Purdue University School of Electrical and Computer Engineering in 2002 where he is currently an associate professor. His research interests include machine vision, artificial intelligence, cognitive science, computational linguistics, child language acquisition, and programming languages and compilers.
Ben Taskar received his bachelor's and doctoral degree in Computer Science from Stanford University. After a postdoc at the University of California at Berkeley, he joined the faculty at the University of Pennsylvania in 2007. He joined the University of Washington Computer Science & Engineering Department in the spring of 2013. His research interests include machine learning, natural language processing and computer vision. He has been awarded the Sloan Research Fellowship, the NSF CAREER Award, and selected for the Young Investigator Program by the Office of Naval Research and the DARPA Computer Science Study Group. His work on structured prediction has received best paper awards at NIPS and EMNLP conferences.
Stefanie Tellex is a Research Scientist at the MIT Computer Science and Artificial Intelligence Laboratory. She will start a tenure-track position in the Brown University Department of Computer Science in September, 2013. She completed her Ph.D. at the MIT Media Lab in 2010, where she developed models for the meanings of spatial prepositions and motion verbs. She has published at SIGIR, HRI, AAAI, IROS, and ICMI, winning Best Student Paper at SIGIR and ICMI. Her research interests include probabilistic graphical models, human-robot interaction, and grounded language understanding.
David Traum is a principal scientist at ICT and a research faculty member at the Department of Computer Science at USC. At ICT, Traum leads the Natural Language Dialogue Group. Traum's research focuses on dialogue communication between human and artificial agents. He has engaged in theoretical, implementational and empirical approaches to the problem, studying human-human natural language and multi-modal dialogue, as well as building a number of dialogue systems to communicate with human users. He has pioneered several research thrusts in computational dialogue modeling, including computational models of grounding (how common ground is established through conversation), the information state approach to dialogue, multiparty dialogue, and non-cooperative dialogue. Traum is author of over 200 technical articles, is a founding editor of the Journal Dialogue and Discourse, has chaired and served on many conference program committees, and is currently the president emeritus of SIGDIAL, the international special interest group in discourse and dialogue. He earned his Ph.D. in computer science at University of Rochester in 1994.
Dan Weld is the Thomas J. Cable / WRF Professor of Computer Science & Engineering at the University of Washington. After formative education at Phillips Academy, he received bachelor's degrees in both Computer Science and Biochemistry at Yale University in 1982. He landed a Ph.D. from the MIT Artificial Intelligence Lab in 1988, received a Presidential Young Investigator's award in 1989, an Office of Naval Research Young Investigator's award in 1990, was named AAAI Fellow in 1999 and deemed ACM Fellow in 2005. Dan was a founding editor for the Journal of AI Research, was area editor for the Journal of the ACM, guest editor for Computational Intelligence and Artificial Intelligence, and was Program Chair for AAAI-96. Dan has published two books and scads of technical papers.
Jason Weston is a research scientist at Google NY since July 2009. He earned his PhD in machine learning at Royal Holloway, University of London and at AT&T Research in Red Bank, NJ (advisor: V. Vapnik) in 2000. From 2000 to 2002, he was a research scientist at Biowulf technologies, New York. From 2002 to 2003 he was a research scientist at the Max Planck Institute for Biological Cybernetics, Tuebingen, Germany. From 2003 to June 2009 he was a research staff member at NEC Labs America, Princeton. Jason's interests are in statistical machine learning and its application, particularly to text, audio and images.
Jason Williams is with Microsoft Research. His interests include spoken dialog systems, planning under uncertainty, spoken language understanding, and speech recognition. He is vice-president of SigDial (the Special Interest Group on Dialog and Discourse), and serving as Co-program chair of the SigDial Conference 2013 and also IEEE workshop on speech recognition and understanding (ASRU) 2013. From 2010-2012 he served on the board of directors of the Association for Voice Interaction Design (AVIxD). From 2009-2011, he served on the IEEE Speech and Language Technical Committee (SLTC) in the area of spoken dialogue systems. He holds a PhD and Masters in Speech and Language Processing from Cambridge University (UK), and a BSE in Electrical Engineering from Princeton University (USA). Prior to Microsoft, Jason was Principal Member of Technical Staff at AT&T Labs - Research from 2006-2012. Jason has also held several positions in industry building spoken dialog systems, including at Tellme Networks (now Microsoft) as Voice Application Development Manager.
Mark Yatskar is a a 3rd year PhD student at UW. He is advised by Luke Zettlemoyer. Mark is interested in Natural Language Processing and Machine Learning. He is currently work on grounding problems like how computers can learn to describe images or avatars.
Luke Zettlemoyer is an Assistant Professor in the Department of Computer Science & Engineering at the University of Washington. Previously, I did postdoctoral research at the University of Edinburgh and was a Ph.D. student at MIT. His current research is in the intersections of natural language processing, machine learning, and decision making under uncertainty. He is particularly interested in designing, building and evaluating algorithms for recovering and making use of representations of the meaning of natural language text.
Larry Zitnick is a senior researcher in the Interactive Visual Media Group at Microsoft research. His current areas of interest include object detection, semantic scene understanding, and human debugging. He also enjoys researching stylus-based applications that assist in creating creative content.
Last updated: 12 July 2013