home *** CD-ROM | disk | FTP | other *** search
- Path: sparky!uunet!charon.amdahl.com!pacbell.com!decwrl!spool.mu.edu!yale.edu!qt.cs.utexas.edu!cs.utexas.edu!uwm.edu!rutgers!igor.rutgers.edu!atanasoff.rutgers.edu!lou
- From: lou@cs.rutgers.edu (Lou Steinberg)
- Newsgroups: comp.ai
- Subject: Re: TOP? Graduate Programs in AI
- Message-ID: <LOU.92Nov5135135@atanasoff.rutgers.edu>
- Date: 5 Nov 92 18:51:35 GMT
- References: <1992Nov4.142458.3876@hellgate.utah.edu>
- Sender: lou@atanasoff.rutgers.edu
- Reply-To: lou@cs.rutgers.edu
- Organization: Computer Science Dept., Rutgers University, New Brunswick, NJ
- 08903
- Lines: 48
- In-reply-to: tolman%asylum.cs.utah.edu@cs.utah.edu's message of 4 Nov 92 21:24:57 GMT
-
- In article <1992Nov4.142458.3876@hellgate.utah.edu> tolman%asylum.cs.utah.edu@cs.utah.edu (Kenneth Tolman) writes:
-
- This is an attempt at suggesting the "best" schools for various research.
- ... Schools are "rated" approximately from top
- to bottom. These are all very loose.
-
- 1. ARTIFICIAL INTELLIGENCE best grad programs....
-
- Stanford, MIT, Yale
- Carnegie Melon
-
- Indiana, Illinois, Maryland
-
- Rutgers definitely belongs is this second tier - we are not Stanford or CMU
- (but then does Yale really belong in that group?), but in selected areas we are
- quite good, if I do say so myself (I am on the Rutgers faculty).
-
- My group works on AI applied to design. We focus on both decision
- making/search and on generating/using numerical models of physical
- systems. Current projects include work on design of microprocessors
- and hydrodynamic design of boats. Faculty include Saul Amarel, Lou
- Steinberg (that's me), Tom Ellman, Andrew Gelsey, Jerry Richter, Chris
- Tong, and Haym Hirsh.
-
- Other areas of AI work at Rutgers include (I hope my colleagues will
- forgive me if I distort or omit anything):
-
- - Biomedical problems: diagnosis, medical image interpretation,
- machine learning applied to DNA sequence intepretation, etc.
- Faculty include Kaz Kulikowski, Sholom Weiss (currently
- on leave) and Mick Noordewier
-
- - Machine learning: primarily neural network and more traditional
- approaches to inductive learning. In the past, Rutgers has
- been a hotbed of deductive learning work as well. Haym Hirsh,
- Mick Noordewier, Eduardo Sontag (he's really in Math), Chris
- Tong, me, and Tom Ellman
-
- - AI and data bases: Alex Borgida, Tomasz Imielinski
-
- - AI and legal reasoning: logics of legal reasoning (including
- modalities like "permitted" and "obligatory"), and generation &
- analysis of legal argument. Thorne McCarty
- --
- Lou Steinberg
-
- uucp: {pretty much any major site}!rutgers!aramis.rutgers.edu!lou
- internet: lou@cs.rutgers.edu
-