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Adam Lally is the primary developer of the
WatsonPaths system architecture as well as
the original Watson question-answering
system architecture. His background
includes developing natural language-pro-cessing algorithms and frameworks for a
variety of applications.
Sugato Bagchi is a research staff member at
IBM Research and IBM Watson Group. He
works on decision support systems based on
unstructured information analytics. Currently, he is part of a team that is working
with leading medical institutions on developing analytics that can help physicians
make clinical decisions using content from
medical textbooks, evidence-based guidelines, and patient consultation notes.
Michael A. Barborak has been a technical
leader of the WatsonPaths project, which
has as its mission to advance cognitive com-
puting through the application of Watson
question answering to complex decision
support tasks. He has an entrepreneurial
background in software development and
technical services. His education is in elec-
trical engineering with degrees from the
University of Texas at Austin (BSEE 1989
and MSEE 1992).
David W. Buchanan is interested in joint
inference problems in large AI systems,
especially using Bayesian approaches. He
built the core inference system for WatsonPaths and other systems. He has published
in causal inference, graphic models, and
hierarchical Bayesian models. He earned his
Ph.D. in Cognitive Science from Brown
University in 2011.
Jennifer Chu-Carroll serves on the editorial boards of the Journal of Dialogue Systems
and the ACM Transactions of Intelligent Systems and Technology. She previously served
on the executive board of the North American Chapter of the Association for Computational Linguistics and as general chair of
the 2012 Conference of the North American
Chapter of the Association for Computational Linguistics — Human Language
Technologies. Her research interests include
question answering, semantic search, and
natural language discourse and dialogue.
David A. Ferrucci is an award-winning AI
researcher and IBM Fellow. He worked at
IBM Research from 1995–2012 where he
built and led a team of researchers to create
the open-source UIMA framework and Watson, the landmark open-domain question-answering system. In 2012, after initiating
the work on WatsonPaths and its application to medicine, he joined Bridgewater
where he is exploring ways to combine
machine learning and semantic technologies to accelerate the discovery, application,
and continuous refinement of interpretable
Michael R. Glass is a software engineer at
IBM Research. His research focuses on deep
learning in natural language processing and
probabilistic joint inference. Glass completed his doctorate in computer science at the
University of Texas at Austin in 2012.
Aditya A. Kalyanpur’s primary research
interests include knowledge representation
and reasoning, natural language processing,
machine learning, and question answering.
He has served on W3C working groups, as
program chair of several international
workshops, and is currently a coeditor of
the International Journal of Web Information
Systems. Kalyanpur earned his Ph.D. from
the University of Maryland, College Park in
Erik T. Mueller’s books include
Commonsense Reasoning, Daydreaming in Humans and
Machines, and Natural Language Processing
with Thought Treasure. He received an S.B. in
computer science and engineering from the
Massachusetts Institute of Technology and
an M.S. and Ph.D. in computer science from
the University of California, Los Angeles.
J. William Murdock is a research staff
member in IBM Watson Group. Before joining IBM, he worked at the United States
Naval Research Laboratory. His research
interests include question answering, natural language semantics, analogical reasoning, knowledge-based planning, machine
learning, and computational reflection. In
2001, he earned his Ph.D. in computer science from the Georgia Institute of Technology.
Siddharth Patwardhan pursues research in
natural language processing, with interests
spanning a variety of topics, including
information extraction, question answering, and computational representation of
lexical semantics. He has investigated these
topics as a researcher at IBM, the University
of Utah, and the Mayo Clinic and at the
University of Minnesota. He was conferred
a Ph.D. in computer science by the University of Utah in 2009, and is the coauthor of
more than 30 peer-reviewed technical publications.
John M. Prager is a research staff member
at IBM Research. His background includes
natural language–based interfaces and
semantic search, and his current interest is
on incorporating user and domain models
to inform question answering, in particular
in the medical domain. He is a member of
the TREC program committee.