Research Position in Statistical Learning

[John Moody]

                       Research Position
                              in
                   Nonparametric Statistics,
             Neural Networks and Machine Learning
                              at
          Department of Computer Science & Engineering
        Oregon Graduate Institute of Science & Technology


I am seeking a highly qualified researcher to take a leading role on a
project involving the development and testing of new model selection
and input variable subset selection algorithms for classification,
regression, and time series prediction applications.

Candidates should have a PhD in Statistics, EE, CS, or a related
field, have experience in neural network modeling, nonparametric
statistics or machine learning, have strong C programming skills,
and preferably have experience with S-Plus and Matlab.  The
compensation and level of appointment (Postdoctoral Research
Associate or Senior Research Associate) will depend upon experience.
The initial appointment will be for one year, but may be extended
depending upon the availability of funding.  Candidates who can
start by April 1, 1997 or before will be given preference, although
an extremely qualified candidate who is available by June 1 may
also be considered.

If you are interested in applying for this position, please mail,
fax, or email your CV (ascii text or postscript only), a letter of
application, and a list of at least three references (names,
addresses, emails, phone numbers) to:

Ms. Sheri Dhuyvetter
Computer Science & Engineering          
Oregon Graduate Institute       
PO Box 91000                    
Portland, OR 97291-1000        

Phone: (503) 690-1476
FAX: (503) 690-1548
Email: sherid at cse.ogi.edu
 
Please do not send applications to me directly.  I will consider
all applications received by Sheri on or before January 31.

OGI (Oregon Graduate Institute of Science and Technology) has over
a dozen faculty, senior research staff, and postdocs doing research
in Neural Networks, Machine Learning, Signal Processing, Time Series,
Control, Speech, Language, Vision, and Computational Finance.
Short descriptions of our research interests are appended below.
Additional information is available on the Web at 
http://www.cse.ogi.edu/Neural/ and http://www.cse.ogi.edu/CompFin/ .

OGI is a young, but rapidly growing, private research institute
located in the Silicon Forest area west of downtown Portland,
Oregon.  OGI offers Masters and PhD programs in Computer Science
and Engineering, Electrical Engineering, Applied Physics, Materials
Science and Engineering, Environmental Science and Engineering,
Chemistry, Biochemistry, Molecular Biology, Management, and
Computational Finance.

The Portland area has a high concentration of high tech companies
that includes major firms like Intel, Hewlett Packard, Tektronix,
Sequent Computer, Mentor Graphics, Wacker Siltronics, and numerous
smaller companies like Planar Systems, FLIR Systems, Flight Dynamics,
and Adaptive Solutions (an OGI spin-off that manufactures high
performance parallel computers for neural network and signal
processing applications).


	+++++++++++++++++++++++++++++++++++++++++++++++++++++++

	   Oregon Graduate Institute of Science & Technology
             Department of Computer Science & Engineering
                 Department of Electrical Engineering

      Research Interests of Faculty, Research Staff, and Postdocs in

   Neural Networks, Machine Learning, Signal Processing, Control, Speech, 
         Language, Vision, Time Series, and Computational Finance

Etienne Barnard (Associate Professor, EE):

Etienne Barnard is interested in the theory, design and implementation
of pattern-recognition systems, classifiers, and neural networks.
He is also interested in adaptive control systems -- specifically,
the design of near-optimal controllers for real- world problems
such as robotics.


Ron Cole (Professor, CSE):

Ron Cole is director of the Center for Spoken Language Understanding
at OGI. Research in the Center currently focuses on speaker-
independent recognition of continuous speech over the telephone
and automatic language identification for English and ten other
languages. The approach combines knowledge of hearing, speech
perception, acoustic phonetics, prosody and linguistics with neural
networks to produce systems that work in the real world.


Mark Fanty (Research Assistant Professor, CSE):

Mark Fanty's research interests include continuous speech recognition
for the telephone; natural language and dialog for spoken language
systems; neural networks for speech recognition; and voice control
of computers.


Dan Hammerstrom (Associate Professor, CSE):

Based on research performed at the Institute, Dan Hammerstrom and
several of his students have spun out a company, Adaptive Solutions
Inc., which is creating massively parallel computer hardware for
the acceleration of neural network and pattern recognition
applications.  There are close ties between OGI and Adaptive
Solutions.  Dan is still on the faculty of the Oregon Graduate
Institute and continues to study next generation VLSI neurocomputer
architectures.


Hynek Hermansky (Associate Professor, EE);

Hynek Hermansky is interested in speech processing by humans and
machines with engineering applications in speech and speaker
recognition, speech coding, enhancement, and synthesis. His main
research interest is in practical engineering models of human
information processing.


Todd K. Leen (Associate Professor, CSE):

Todd Leen's research spans theory of neural network models,
architecture and algorithm design and applications to speech
recognition. His theoretical work is currently focused on the
foundations of stochastic learning, while his work on Algorithm
design is focused on fast algorithms for non-linear data modeling.


John Moody (Associate Professor, CSE):

John Moody does research on the design and analysis of learning
algorithms, statistical learning theory (including generalization
and model selection), optimization methods (both deterministic and
stochastic), and applications to signal processing, time series,
economics, and computational finance.


David Novick (Associate Professor, CSE):

David Novick conducts research in interactive systems, including
computational models of conversation, technologically mediated
communication, and human-computer interaction. A central theme of
this research is the role of meta-acts in the control of interaction.
Current projects include dialogue models for telephone-based
information systems.


Misha Pavel (Associate Professor, EE):

Misha Pavel does mathematical and neural modeling of adaptive
behaviors including visual processing, pattern recognition, visually
guided motor control, categorization, and decision making.  He is
also interested in the application of these  models to sensor
fusion, visually guided vehicular control, and human-computer
interfaces.


Hong Pi (Senior Research Associate, CSE)

Hong Pi's research interests include neural network models, time series
analysis, and dynamical systems theory.   He currently works on the
applications of nonlinear modeling and analysis techniques to time
series prediction problems and financial market analysis.


Pieter Vermeulen (Senior Research Associate, CSE):

Pieter Vermeulen is interested in the theory, design and implementation
of pattern-recognition systems, neural networks and telephone based
speech systems.  He currently works on the realization of speaker
independent, small vocabulary interfaces to the public telephone
network. Current projects include voice dialing, a system to collect
the year 2000 census information and the rapid prototyping of such
systems.


Eric A. Wan  (Assistant Professor, EE):

Eric Wan's research interests include learning algorithms and
architectures for neural networks and adaptive signal processing.
He is particularly interested in neural applications to time series
prediction, adaptive control, active noise cancellation, and
telecommunications.


Lizhong Wu (Senior Research Associate, CSE):

Lizhong Wu's research interests include neural network theory and
modeling, time series analysis and prediction, pattern classification
and recognition, signal processing, vector quantization, source
coding and data compression.  He is now working on the application
of neural networks and nonparametric statistical paradigms to
finance.