FREDERIC PIAT
Publications
Back to main page
DOB: 8/7/68 in Dijon, Burgundy, France. French citizen
Current situation:
Maitre de conférences at ENSIM (Ecole Nationale Supérieure d'Ingénieurs du Mans), Université du Maine.
Graduated with a PhD in Human Development and Communication Disorders at the
School of Human Development at the University of Texas at Dallas.
"ARTIST:
ADAPTIVE RESONANCE THEORY for the INTERNALIZATION of the STRUCTURE of TONALITY"
(almost 1Mb)
Abstract
Languages spoken/written: French, English, Spanish
Programmation languages proficiencies:
- JAVA
- Turbo Pascal
- C++
- Prolog (My favorite!)
- Lisp
- Matlab
- Sas (stastistics package)
- Fortran
- Basic
- Forth
- dBase
- Genesis
- Notions of Assembleur, Ada and MIDI files
University
Education:
Bachelor (1990) and Master's (1991) in Computer Sciences /
Artificial Intelligence from the University of Dijon, France, including the
following classes (can't remember all of them):
- Formal languages and graphs (logic and generative grammars)
- Probabilities / Statistics
- Numerical analysis (optimisation theory)
- Network Systems
- Assembleur
- C++
- Pascal
- Unix
- Infography (including GKS language)
- Algorithmic
- Database
- Productic / Robotic (production sciences)
- Distributed Systems (parallel programming)
DEA (1992) Diplome
d'Etudes Approfondies, (= post-master's degree) in Artificial Intelligence and
Production Sciences from the University of Besancon, France.
M.S. (1998) in Applied Cognition and Neuroscience from the University of
Texas at Dallas.
NEURAL NETWORKS:
Projects during the years 90-92 concerned NEURAL NETWORKS:
- year 1: Programming in C of an all-purpose neural network simulator.
Applied to LETTER RECOGNITION.
- year 2: Application of the neural network to the prediction of chemical
activities for DRUG DESIGN.
- year 3: Architecture optimization and performance optimization of the
neural networks previously used.
Since 1993, student in the PhD
program 'Applied cognition and Neuroscience' at the School of Human Development,
University of Texas at Dallas (UTD). Classes taken (All passed with grade 'A'):
Advanced Research methods, Cognitive Science I & II, Perception, Attention,
Neural Networks, Tools for ANN analysis and design, Seminar of neural computer
simulations (Neuron and Genesis programming), Auditory scene analysis, Natural
Language Understanding.
Professional Experiences: Tutoring, Teaching, Research &
Software Development
Tutoring of many French students in Mathematics,
Physics, Chemistry, English Worked for the software company InovaSys, developing
part of the following softwares (including ALL imagery and user interface
modules):
- CRISTAL: Tool for teaching cristallography: 3D visualization / rotation /
animation of cristals. On Windows.
- RMN: Simulator of a Nuclear Magnetic Resonance machine (visualization of
electron spin, FID curve and spectra). On both windows AND Mac.
Since
1993, teaching assistant for research methods / statistics class for psychology
undergraduates at UTD. This involved teaching labs (including computer labs,
teaching the use of SAS, a software for statistics), grading papers and
tutoring.
I conducted a series of experiments (running human subjects, preparing
stimuli and statistically analysing the results) which results were presented at
conferences (see next section).
Publications:
- 1994: Abdi, H., Piat, F., & Dowling, W.J. Interference in the early
time course of melodies. Paper presented at the 3rd ICMPC (International
Conference of Music Perception and Cognition), Liege, Belgium.
- 1995: Abdi, H., Piat, F., & Dowling, W.J. Memory for melodies and
interfering tasks. paper presented at the SMPC (Society for Music Perception
and Cognition), San Francisco.
- 1996: Piat, F., & Dowling, W.J. Interpolated tasks and memory for
melodies. Poster presented at the 4th ICMPC, Montreal, Canada.
- 1999: Kollias S. and Piat, F. The PHYSTA
project, poster presented at ICMCS'99 (International Conference on
Multimedia Computing and Systems), June 7-11, Florence Italy. (Abstract)
- 1999: Piat, F. and Stamou, G. Refining Rules of
Emotion Recognition in Hybrid Systems. Presented at the 3rd IMACS CSCC'99
(International Multiconference on Circuits, Systems, Communications and
Computers. July 4-8, Athens Greece).
- 2000: W. A. Fellenz, J. G. Taylor, R. Cowie, E. Douglas-Cowie, F. Piat, S.
Kollias, C. Orovas and B. Apolloni. On emotion recognition of faces and of
speech using neural networks, fuzzy logic and the ASSESS system.
IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN),
Como, Italy, 24-27 July 2000.
- 2000: Piat, F. and Tsapatsoulis, N. Exploring the time course of facial expressions with a fuzzy system. IEEE International
Conference on Multimedia and Expo (ICME 2000), July 30 - August 2, 2000,
New-York, USA.
- 2000: Piat, F. ARTIST: A
connectionist model of musical acculturation. 6th International Conference
on Music Perception and Cognition (ICMPC), August 5-10, 2000, Keele
University, UK.
- 2000: N. Tsapatsoulis, K. Karpouzis, G. Stamou, F. Piat and S. Kollias. A Fuzzy
System for Emotion Classification based on the MPEG-4 Facial Definition
Parameter Set. X European Signal Processing Conference (EUSIPCO) 5th-8th
Sept 2000, Tampere, Finland.
- 2001: Piat, F. The
Neural Network Model of Music Cognition ARTIST and Applications to the WWW.
International Conference on Web delivering of music, WEDELMUSIC, Nov.
30th-Dec. 1st 2001, Florence, Italy.
- 2001: Piat, F. What connectionist models can learn from music. Operational
Programmes for Research and technology: 2nd symposium on Human Networks of
Music Informatics. Thessaloniki, June 1st 2001. (Invitation, Abstract)
- 2001: Piat, F. What
connectionist models can learn from music. Mousikotropies. Aristotle
University Thessaloniki - Greece, December 2001.
- 2002: D’Ausilo A., Piat F., Mastacchi A., Olivetti Belardinelli M.
Salience as a fundamental cue to musical pattern recognition: a Parallel
Distributed Processing approach. ICMAI'02 (2nd International Conference of
Music and Artificial Intelligence), 12-15 September 2002, Edinburgh, Scotland.
- 2003: Bidel S., Lemoine L., Piat F., Artières T. and Gallinari P. Apprentissage de
comportements utilisateurs de produits Hypermédias. Journées francophones
d’Extraction et de Gestion des Connaissances. EGC 2003, Jan 22-24, Lyon,
France.
- 2003: Bidel S., Lemoine L., Piat F., Artières T. and Gallinari P.
Statistical machine learning for tracking hypermedia user behavior. 9th
International Conference on User Modeling, UM 2003, June 22-26, Pittsburgh,
U.S.A.
- 2003: D’Ausilio A., Piat F., Londei A. and Olivetti Belardinelli M.
Competitive vs feed-forward modelling of music recognition tasks. 5th ESCOM,
8-13 September 2003, Hanover, Germany.
- 2003: Gallinari P., Bidel S., Lemoine L., Piat F. and Artières T.
Classification and tracking of hypermedia navigation patterns. 13th ICANN
2003, June 26-29, Istanbul, Turkey. (Invited)
- 2004: Piat, F. L'émotion musicale comme propriété émergente de la
perception tonale dans un modèle connexioniste. Journées du CNA2 2004
"Musique et Emotions", Lille, 14-15 Mai 2004.
Abstract
-
2009 : Teutsch P., Piat F. and Reffay, C.
Anonymizing and sharing corpora of online training courses. In Proceedings of the 8th International Conference on Computer Supported Collaborative Learning. Workshop "Interaction Analysis and Visualization for Asynchronous Communication"
, CSCL 2009, Rhodes, Greece, June 2009, 6 p.
-
2014 : Piat F., Carlier F. and Renault V. De Nouvelles Interfaces pour Apprendre la Théorie de la Musique. Technologies de l'Information et de la Communication pour l'Enseignement, TICE 2014, Nov. 22-24, Béziers, France.
Technical Reports:
For NEuroNet
II, the EC-funded "Network of Excellence" in Neural Networks (No.
28103).
- 1999: NEuroNet Roadmap: First Report on the Use of Neural Networks and
Other Computational Intelligence Techniques in Intelligent Multimedia Systems.
S. Kollias, F. Piat and A. Drossopoulos, ICCS-NTUA, 3rd June 1999.
- 1999: NEuroNet Roadmap: Selected Applications - Neural Networks for
Emotion Recognition. S. Kollias and F. Piat, ICCS-NTUA, 17th December 1999.
Unpublished:
2000: Kelley L. Kaye, Frederic Piat, Thomas G.R. Bower. Visual Recognition
of Manually Explored Object Shape in Human Newborns.
See the stimuli and data
Research interests:
Anything that
could help understand better both types of intelligence (natural and artificial)
for their mutual development. Identifying the neurophysiological constraints and
the importance of environmental factors (structural regularities across stimuli
for instance) necessary to achieve learning.