Graduate Opportunities at Brandeis University

[Jordan Pollack]

In May 1994 Brandeis University announced the opening of the new Volen
National Center for Complex Systems with the goal of promoting
interdisciplinary research and collaboration between faculty from
Biology, Computer Science, Linguistics, Mathematics, Neuroscience,
Physics, and Psychology.  The Center, whose main mission is to study
the brain, intelligence, and advanced computation, has already earned
accolades from ascientists world wide, and continues to expand.

Brandeis University is located in Waltham, a suburb 10 miles west of
Boston, with easy rail access to both Cambridge and Downtown. Founded
in 1948, it is recognized as one of the finest private liberal arts
and science universities in the United States. Brandeis combines the
breadth and range of academic programs usually found at much larger
universities, with the friendliness of a smaller and more focused
research community.

The Computer Science Department is located entirely in the new Volen
Center building and is the home of four Artificial Intelligence
faculty actively involved in the Center activities and collaborations:
Rick Alterman, Maja Mataric, Jordan Pollack, and James Pustejovsky.

Professor Alterman's research interests are in the areas of artificial
intelligence and cognitive science.  A recent project focused on the
problems of everyday reasoning.  A model was developed where agent
goal-directed behavior is guided by pragmatics rather than by analytic
techniques.  His work with Zito-Wolf developed techniques for skill
acquisition and learning; the focus was on building case
representations of procedural knowledge.  Work with Carpenter was
focussed on building a reading agent that can actively seek out and
interpret instructions that are relevant to a "break down" situation
for the overall system.  Two current projects support the evolution
and maintenance of a collective memory for a community of distributed
heterogeneous agents who plan and work cooperatively, and with
building interactive systems that improve their own performance by
keeping track of the history of interactions between the end-user and
the system.  For more information see 
http://www.cs.brandeis.edu/dept/faculty/alterman.
 
Jordan Pollack's research interests lie at the boundary between neural
and symbolic computation: How could simple neural mechanisms organized
naturally into multi-cellular structures by evolution provide the
capacity necessary for cognition, language, and general intelligence?
This view has lead to successful work on how variable tree-structures
could be represented in neural activity patterns, how dynamical
systems could act as language generators and recognizers, and how
fractal limit behavior of recurrent networks could represent mental
imagery.  He has also worked on evolutionary and co-evolutionary
learning in strategic game playing agents, as well as with teams of
simple agents who cooperate on complex tasks.  Prof. Pollack
encourages students with backgrounds and interests in AI, machine
learning, dynamical systems, fractals, connectionism, and ALife to
apply.  For more information see
http://www.cs.brandeis.edu/dept/faculty/pollack.

Maja Mataric's interdisciplinary research focuses on understanding
systems that integrate perception, representation, learning, and
action.  Her current work is applied to synthesis and analysis of
behavior in situated agents and multi--agent systems, and on learning
and imitation, in software, dynamical simulations, and physical
robots.  Learning new behaviors and behavior selection, as well as
memory and representation are the main thrusts of the research.  The
newest project models learning by imitation, through the interaction
of a collection of cognitive systems, including perception (attention
and analysis), memory (declarative and non-declarative
representations), action sequence planning, motor control,
proprioception, and learning.  Prof. Mataric encourages students with
interests and/or backgrounds in AI, autonomous agents, machine
learning, cognitive science, and cognitive neuroscience to apply.  For
more information see http://www.cs.brandeis.edu/dept/faculty/mataric.

James Pustejovsky conducts research in the areas of computational
linguistics, lexical semantics, information retrieval and extraction,
and aphasiology. The main focus of his research is on the computational
and cognitive modeling of natural language meaning.  More
specifically, the investigation is in how words and their meanings
combine to meaningful texts.  This research has focused on developing
a theory of lexical semantics based on a methodology making use of
formal and computational semantics.  There are several projects
applying the results of this theory to Natural Language Processing,
which in effect, empirically test this view of semantics. These
include: an NSF grant with Apple to automatically construct index
libraries and help systems for applications; a DEC grant to
automatically convert a trouble-shooting text-corpus into a case
library. He also is currently working with aphasiologist Dr. Susan
Kohn on word-finding difficulties and sentence generation in aphasics.
For more information see
http://www.cs.brandeis.edu/dept/faculty/pustejovsky.

The four AI faculty work together and with other members of the Volen
Center, creating new interdisciplinary research opportunities in areas
including cognitive science (http://fechner.ccs.brandeis.edu/cogsci.html)
computational neuroscience, and complex systems at Brandeis University.

To get more information about the Volen Center for Complex Systems,
about the Computer Science Department, and about the other CS faculty, see:
http://www.cs.brandeis.edu/dept

The URL for the graduate admission information is 
http://www.cs.brandeis.edu/dept/grad-info/application.html