Andre Vellino

Ahmad Sohrabi

Sanjay Chandrasekharan

Jim Davies

Tony White

Sterling Somers

Ted Lougheed

Neal Leblanc

Kam Kwok

Matthew Kelly

Francis Jeanson

Courtney Humeny

Gordon Griffiths

Jacky Tweedie

More information is being added at this time. In the meantime, you can contact Jacky at:

jstweedie@gmail.com

David Pierre Leibovitz

David is involved with the following projects

• Emergic Network - a computational architecture for cognition harnessing massive feedback (recurrence) and parallelism
• Emergic Cognitive Model - a unified cognitive model (currently for visual processing) based on the Emergic Network
• WikiSilo - a minimalist epistemology for theoretical exploration and a discipline for  progressing science
• Emergic Metaphysics -  an analytic "process philosophy" simplified for cognition but based on modern Physics - it is the only notation that can deal with change under feedback cycles
• Emergic Approach - an epistemology for doing science over complex dynamic systems with massive feedback and parallelism. Based on Emergic Metaphysics.
• Wikimergic - home of the Emergic Approach, and a wiki to articulate its impact to the science of cognition

David's academic home page is at: dpleibovitz.upwize.com, and he can be reach at dpleibovitz@ieee.org

Aryn Pyke

More information is being added at this time. In the meantime, you can contact Aryn at:

aryn.pyke@gmail.com

Terry Stewart

More information to be added. In the meantime, please contact Terry at:

terry.stewart@gmail.com

Edgar Acosta

Most cognitive models try to explain/predict behavior presuming (sometimes unintendedly, and inadvertently) the availability of knowledge and its representation. Whereas such a bias may have different justifications and is useful, it may also mislead our understanding of the studied phenomena.

With this worry in mind, my aim is to build models that are able to discover the relevant properties of the environment for the task at hand, so that they can decide what/where to focus on, to build their own representations in terms of those properties and their relations, and increasingly improve performance as representations become more detailed. I am particularly interested on how humans deal with this problem.

Matthew Rutledge-Taylor

Cognitive Science PhD candidate, Carleton University

Institute of Cognitive Science: http://www.carleton.ca/ics/
Carleton Cognitive Modelling Lab: CCMLab

Contact:
2222 Dunton Tower (ICS) / 5210Q VSim Building (CCMLab)
1125 Colonel By Drive
Ottawa, ON
K1S 5B6
Canada
mrtaylo2@connect.carleton.ca
http://chat.carleton.ca/~mrtaylo2/

Bruno Emond Ph.D.

Research Officer | Agent de Recherche
Tel. | Tél. 1.613.991.5471 Facsimile | Télécopieur 1.613.952.0215
bruno.emond@nrc-cnrc.gc.ca

Institute for Information Technology | Institut de technologie de l'information
http://iit-iti.nrc-cnrc.gc.ca

National Research Council Canada | Conseil National de Recherches Canada
1200 Montreal Rd., M50, Ottawa, ON K1A 0R6
Government of Canada | Gouvernement du Canada

Sylvain Pronovost

Human Factors Specialist - CAE Professional Services
PhD Candidate in Cognitive Science - ICS, Carleton University
Research Assistant - OCE Integrated Command Environment project, V-SIM
Research Assistant - Carleton Cognitive Modeling Laboratory, CACR

Ottawa, Ontario, Canada

http://www.carleton.ca/ics/
http://web.mac.com/doktorsly/

Ronald Laurids Boring Phd

Ronald Laurids Boring (PhD), Principal Scientist
Human Factors, Instrumentation and Control Systems
Idaho National Laboratory
PO Box 1625
Idaho Falls, ID 83415-3605

(208) 757-1514 blackberry
(208) 526-2777 fax
Email: ronald.boring@inl.gov

Robert L. West

Associate Professor at the Institute of Cognitive Science and the Department of Psychology at Carleton University

email: robert_west@carleton.ca