(412) 268-1198
noelle@acm.org
http://www.cnbc.cmu.edu/~noelle/
Interdisciplinary focus on connectionist cognitive psychology. Thesis advisor was Garrison W. Cottrell. Dissertation research on modeling integrated implicit/explicit learning, entitled A Connectionist Model Of Instructed Learning.
M.S., Computer
Science
University of California, San
Diego
La Jolla,
California
June, 1992
GPA 4.00
Computer science comprehensive examination passed with distinction.
B.S., cum laude, Computer Science &
Engineering
University of California, Los Angeles
Los Angeles,
California
June, 1987
GPA 3.62
Curriculum encompassed foundations of computer science and electrical engineering. Courses included artificial intelligence, natural language processing, and psychobiology.
Conducted research on instructed category learning, confidence reports, and connectionist models of instruction following, category learning, cognitive control, working memory, conflict monitoring, and prefrontal cortex. Advised by James L. McClelland and Jonathan D. Cohen.
January, 1999 - May, 1999
Instructor
Carnegie Mellon University
Department of
Psychology
Pittsburgh,
Pennsylvania
Taught the combined undergraduate and graduate course "Introduction to Parallel Distributed Processing" which covers the fundamentals of artificial neural network modeling and the application of such modeling techniques to the understanding of cognitive processes.
April, 1997 - June, 1997
Seminar Leader
UCSD
Cognitive Science
Department
San Diego,
California
Organized and led a ten week research seminar on the dynamical systems hypothesis in cognitive science.
April, 1993 - September, 1996
Senior Teaching Assistant
UCSD
Computer Science & Engineering
Department
San Diego,
California
Produced and maintained instructional resources for computer science teaching assistants. Actively participated in hiring, training, and evaluation of teaching assistants. Student member of faculty committee on graduate education.
September, 1991 - December, 1996
Teaching Assistant
UCSD
Computer Science & Engineering
Department
San Diego,
California
Taught courses on Artificial Intelligence, Computer Graphics, Programming In C, Introduction to Computer Science Using C++, Basic Data Structures and Object-oriented Programming, graduate level Computer Architecture, Digital Systems Design.
June, 1994 - September, 1995
Staff Scientist
HNC Software
San Diego,
California
Developed statistical models for the Falcon artificial neural network based system for early detection of credit card fraud. Investigated modular network architectures and preprocessing strategies for time series data.
July, 1993 - August, 1993
Instructor
UCSD Summer
Session
San Diego,
California
Taught upper division Computer Science & Engineering core course on the "Design and Analysis of Algorithms", a ten week class condensed to five weeks for Summer Session.
September, 1990 - September, 1992
Senior Consultant
David Noelle Consulting
San Diego,
California
Generated software system components for expert system shells, using proprietary OOP languages and Lisp.
September, 1987 - September, 1990
Senior Computer Scientist
Inference
Corporation
Los Angeles,
California
Developed and maintained components of the ART (Automated Reasoning Tool) expert system shell including the object-oriented programming subsystem, code for rule/object integration, and user-interface development tools. (This technology became the core of the software products sold by Brightware, Inc..)
July, 1986 - September, 1986
Agency Intern
Great American Life Insurance
Company
Los Angeles,
California
Diagnosed and corrected errors in agent payment system using CICS and TSO on an IBM mainframe.
July, 1985 - September, 1985
Software Developer
MAL Associates
Goleta,
California
Generated routines for database access and data preprocessing for IBM PC compatible expert system for armored vehicle fire control system design.
July, 1984 - September, 1984
Summer Intern
Raytheon
Company
Goleta,
California
Performed system administration duties for electronic counter-measures software development project.
Noelle, D. C. and Cottrell, G. W. (1994). Towards instructable connectionist systems. In R. Sun & L. A. Bookman (Eds.), Computational Architectures Integrating Neural And Symbolic Processes (pp. 187-221). Boston: Kluwer Academic Publishers. (cover page)
Noelle, D. C. and Cottrell, G. W. (1995). A connectionist model of instruction following. In J. D. Moore & J. F. Lehman (Eds.), Proceedings of the 17th Annual Conference Of The Cognitive Science Society (pp. 369-374). Pittsburgh: Lawrence Erlbaum. (cover page) (HTML version available)
Noelle, D. C. and Cottrell, G. W. (1995). A unified connectionist model of instruction following. In R. Sun & F. Alexandre (Eds.), Working Notes of the Workshop On Connectionist-Symbolic Integration: From Unified To Hybrid Approaches (pp. 44-49). Montréal: AAAI Press. (cover page)
Noelle, D. C. (1995). The neurophilosophy of Patricia Smith Churchland. [interview] Free Inquiry, 15(4), 22-25.
Noelle, D. C. and Cottrell, G. W. (1996). In search of articulated attractors. In G. W. Cottrell (Ed.), Proceedings of the 18th Annual Conference Of The Cognitive Science Society (pp. 329-334). La Jolla: Lawrence Erlbaum. (cover page) (HTML version available)
Noelle, D. C. and Cottrell, G. W. (1996). Modeling interference effects in instructed category learning. In G. W. Cottrell (Ed.), Proceedings of the 18th Annual Conference Of The Cognitive Science Society (pp. 475-480). La Jolla: Lawrence Erlbaum. (cover page) (HTML version available)
Noelle, D. C. (1996). A connectionist model of instructed learning. Proceedings of the 13th National Conference On Artificial Intelligence (p. 1368). Portland: AAAI Press. (cover page) (HTML version available)
Noelle, D. C., Cottrell, G. W., and Wilms, F. R. (1997). Extreme attraction: The benefits of corner attractors. Technical Report CS97-536, Department of Computer Science & Engineering, University of California, San Diego. (cover page) (A monochome version is available, but it is quite difficult to read compared to the color version.) (HTML version available)
Noelle, D. C., Cottrell, G. W., and Wilms, F. R. (1997). Extreme attraction: On the discrete representation preference of attractor networks. In M. G. Shafto & P. Langley (Eds.), Proceedings of the 19th Annual Conference Of The Cognitive Science Society (p. 1000). Stanford: Lawrence Erlbaum. (cover page) (HTML version available)
Noelle, D. C. (1997). A Connectionist Model of Instructed Learning. PhD thesis, University of California, San Diego, Department of Computer Science and Engineering, Department of Cognitive Science.
Noelle, D. C. (1998). Searching for god in the machine. Free Inquiry, 18(3), 54-56.
Noelle, D. C. (1998). Is the dynamical hypothesis falsifiable? On unification in theories of cognition. [Commentary on Van Gelder, T., The dynamical hypothesis in cognitive science]. Behavioral and Brain Sciences, 21(5), 647-648.
Noelle, D. C. and Zimdars, A. L. (1999). Methods for learning articulated attractors over internal representations. In M. Hahn & S. C. Stoness (Eds.), Proceedngs of the 21st Annual Conference of the Cognitive Science Society (pp. 480-485). Vancouver: Lawrence Erlbaum. (cover page)
Noelle, D. C. (1999). Explicit to whom? Accessibility, representational homogeneity, and dissociable learning mechanisms. [Commentary on Dienes, Z. and Perner, J., A theory of implicit and explicit knowledge]. Behavioral and Brain Sciences, 22(5), 777-778.
Noelle, D. C., Cottrell, G. W., and McKenzie, C. R. M. (1999). Interference effects and individual differences in instructed category learning. Abstracts of the Psychonomic Society (p. 8). Los Angeles.
Noelle, D. C. (2000). Modeling interference between prefrontal cortex and posterior systems during instructed category learning. Cognitive Neuroscience Society Annual Meeting Program (p. 112). San Francisco.
Noelle, D. C. and Cottrell, G. W. (2000). Individual differences in exemplar-based interference during instructed category learning. In L. R. Gleitman & A. K. Joshi (Eds.), Proceedngs of the 22nd Annual Conference of the Cognitive Science Society (pp. 358-363). Philadelphia: Lawrence Erlbaum. (cover page)
Noelle, D. C. (2000). Modeling dynamic modulation of control during instructed category learning. Abstracts of the Psychonomic Society: 41st Annual Meeting (p. 69). New Orleans.
Noelle, D. C. (in press). Exorcizing the homunculus. Free Inquiry.
McKenzie, C. R. M., Wixted, J. T., Noelle, D. C., and Gyudzhyan, G. (in press). Relation between confidence in yes-no and forced-choice tasks. Journal of Experimental Psychology: General.
Noelle, D. C. (in press). Learning from advice. In L. Nadel (Ed.), Encyclopedia of Cognitive Science. London: Macmillan.
Noelle, D. C., Cottrell, G. W., and McKenzie, C. R. M. (submitted). Modeling individual differences in the specialization of an explicit rule.
O'Reilly, R. C., Noelle, D. C., Braver, T. S., and Cohen, J. D. (submitted). Prefrontal cortex and dynamic categorization tasks: Representational organization and neuromodulatory control.
McKenzie, C. R. M., Wixted, J. T., and Noelle, D. C. (submitted). Do participants believe what experimenters tell them? Further tests of the relation between confidence in yes/no and forced-choice tasks.
Noelle, D. C. (in preparation). Interference is optimal: The impact of prior expectations on instructed category learning performance.
Noelle, D. C. and Cottrell, G. W. (in preparation). A connectionist account of instruction following and the application of explicit rules.
Noelle, D. C. and Cottrell, G. W. (in preparation). Learning articulated attractors over internal representations.
"In search of articulated attractors," with Cottrell, G. W. (1995). Invited talk to Workshop On Symbolic Dynamics In Neural Processing at Neural Information Processing Systems 1995, Vail.
"A connectionist model of instructed learning" (1996). Invited talk to the SIGART/AAAI Doctoral Consortium at The 13th National Conference on Artificial Intelligence, Portland.
"Modeling an interference effect in instructed category learning" (1998). Invited talk to the Center for Cognitive Science Spring Colloquium at the State University of New York at Buffalo.
"Modeling an interference effect in instructed category learning" (1998). Invited talk to the Center for Automated Learning and Discovery at Carnegie Mellon University.
"Hybrid strategies for learning: A connectionist perspective" (1999). Invited talk at Hybrid Strategies for Learning: The Symbolic/Connectionist Gap, a CMU Science of Learning Research Seminar.
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