American Journal of Intelligent Systems

American Journal of Intelligent Systems is a peer reviewed journal in the field of intelligent systems and applications. The aim is to provide a common scientific forum for all the different disciplines contributing to this area, ranging from the social, human and computer sciences to the analysis and application of information technology.

Ramin Pichevar

Editorial Board Member of American Journal of Intelligent Systems

Research Scientist, Communications Research Centre, Canada

Research Areas

Signal Processing, Artificial Intelligence, Neural Networks, Sparse Coding, Audio Coding and Processing, Auditory Scene Analysis, Sound Source Separation

Education

2007-2010MasterBusiness Administration (MBA) (part-time), University of Ottawa, ON, Canada
2000-2004Ph.DElectrical & Computer Eng., University of Sherbrooke, QC, Canada
1996-1999M.Scspecialization in Telecommunication Systems, Iran University of Science and Technology IUST ( Rank: First in class), Tehran, Iran
1992-1996B.Scspecialization in Electronics, Tehran Az. University (Rank: First in class), Tehran, Iran
1992High School DiplomaMathematics and Physics, Tehran, Iran
1991Première ScientifiqueCentre National d'Enseignment à Distance, Rennes, France

Experience

2006-presentResearch Scientist in the Advanced Audio Laboratory, Communications Research Center (CRC), Ottawa, Canada
2006-presentResearch Consultant in the Signal Processing and Computational Neuroscience Laboratory, University of Sherbrooke, QC, Canada
2006-presentAdjunct Professor, Dept. of Electrical & Computer Eng., University of Sherbrooke, QC, Canada
2006Research Professional, CARTEL, Dept. of Surveying & Remote Sensing, University of Sherbrooke, Canada
2004-2006Research Associate in the Signal Processing and Computational Neuroscience Laboratory, University of Sherbrooke
2002-2004Research Assistant, University of Sherbrooke
2000-2002Research Assistant, ERMETIS, UQAC (University of Quebec at Chicoutimi), Canada
1996-1998Windows Programmer at Sinasoft Co., Iran
1996-1999Windows Programmer at Informatics Systems Co., Iran
1996Summer Position at Iran Telecommunication Research Center (ITRC): Realization of a 10K Telephone Switch

Publications: Conferences/Workshops/Symposiums/Journals/Books

[1]  V. de Ladurantaye, M. Parenteau, J. Lavoie, J. Bergeron, H. Lu, R. Pichevar, and J. Rouat, "A Parallelt Supercomputer Implementation of a Biologically-Inspired Neural Network and Its use in Pattern Recognition", to appear in Journal of Physics.
[2]  R. Pichevar, H. Najaf-Zadeh, L. Thibault, and H. Lahdili, "Auditory-Inspired Sparse Representation of Multimedia Signals with Applications to Audio Coding", Speech Communication (Elsevier), vol. 53, issue 5, pp 643-657, 2011 (pdf).
[3]  R. Pichevar, H. Najaf-Zadeh, and L.Thibault, "New Trends in Biologically-Inspired Audio Coding", Recent Advances in Signal Processing, In-Tech Pub., ISBN 978-953-7619-41-, 2009.
[4]  J. Rouat, S. Loiselle, and R. Pichevar, "Towards Neurocomputational Models of Speech and Sound Processing", Lecture Notes in Computer Science, Springer-Verlag, Vol. 4391, 2007 (invited).
[5]  R. Pichevar, J. Rouat, "Monophonic Source Separation with an Unsupervised Network of Spiking Neurones", Neurocomputing (Elsevier), Dec. 2007, pp 109-120. (pdf).
[6]  R. Pichevar, J. Rouat, and Le Tan Tanh Tai, "The Oscillatory Dynamic Link Matcher for Spiking-Neuron-Based Pattern Recognition", Neurocomputing (Elsevier), vol. 69, Octobter 2006 (pdf).
[7]  J. Rouat, R. Pichevar, and S. Loiselle, " Auditory scene analysis in link with non-linear speech processing and spiking Neural Networks", Lecture Notes in Computer Science, Vol. 3445, Springer-Verlag (invited), 2004 (pdf).
[8]  R.Pichevar, J.Rouat., "A Quantitative Evaluation of a Bio-Inspired Sound Segregation Technique for Two-and Three-Source Mixtures", Lecture Notes in Computer Science, Vol. 3445, Springer-Verlag, 2004 (pdf).
[9]  J. Rouat, R. Pichevar, "Source separation with one ear: Proposition for an anthropomorphic approach", EURASIP Journal on Applied Signal Processing, no.9, pp 1365-1374, 2005 (pdf).
[10]  V. de Ladurantaye, M. Parenteau, J. Lavoie, J. Bergeron, H.-Z. Lu, R. Pichevar, and J. Rouat, "A Parallel Supercomputer Implementation of a Biologically-Inspired Neural Network and its use for Pattern Recognition ", to be presented at HPCS 2011, Montreal, Canada.
[11]  R. Pichevar, H. Najaf-Zadeh, F. Mustiere, C. Srinivasa, and H. Lahdili, " Sparse Object-Based Audio Coding Using Non-Negative Matrix Factorization of Spikegrams", to be presented at SPARS 2011, Edinburgh, Scotland.
[12]  F. Mustiere, H. Najaf-Zadeh, R. Pichevar, H. Lahdili, and M. Bouchard, "Sparse Audio Coding Via Targeted Dithering and Combinatorial Decoding", Eusipco 2010, Aalborg, Denmark (pdf).
[13]  R. Pichevar, H. Najaf-Zadeh, and F. Mustiere, " Neural-Based Approach to Perceptual Sparse Coding of Audio Signals", IEEE Joint Conference on Neural Networks, 2010, Barcelona, Spain (pdf).
[14]  R. Pichevar, H. Najaf-Zadeh, and H. Lahdili, "Biologically-Inspired Sparse Coding of Music", International Conference on Machine Learning's workshop on sparse methods for music audio, 2009, Montreal, Canada.
[15]  R. Pichevar and H. Najaf-Zadeh, "Pattern Extraction in Sparse Representations with Application to Audio Coding", European Signal Proc. Conf. (EUSIPCO), 2009, Glasgow, Scotland.
[16]  R. Pichevar, H. Najaf-Zadeh, L. Thibault, H. Lahdili, "Entropy-Constrained Spike Modulus Quantization in a Bio-inspired Universal Audio Coder",European Signal Proc. Conf. (EUSIPCO), 2008, Lausanne, Switzerland (pdf).
[17]  R. Pichevar and J. Rouat, "An Improved Sparse Non-Negative Part-Based Image Coder via Simulated Annealing and Matrix Pseudo-Inverse", ICASSP 2008, Las Vegas, USA (pdf).
[18]  R. Pichevar, H. Najaf-Zadeh, L. Thibault, H. Lahdili, "Differential Graph-Based Coding of Spikes In A Biologically-Inspired Universal Audio Coder", AES 2008 convention, Amsterdam, The Netherlands (pdf).
[19]  H. Najaf-Zadeh, R. Pichevar, L. Thibault, H. Lahdili, "Perceptual Matching Pursuit", AES 2008 convention, Amsterdam, The Netherlands (pdf).
[20]  J. Rouat, S. Loiselle, and R. Pichevar, ""Networks of spiking neuron models for speech processing", Workshop on Mathematical Neuroscience, Montréal, QC, Canada, Sept. 2007.
[21]  J. Bergeron, A. Ho Angh, S. Loiselle, J. Lavoie, R. Pichevar, J. Rouat, V. Lapointe, and J. Bélanger, "RN-SpikesRN-SPIKES for invariant pattern recognition ",Workshop on Mathematical Neuroscience, Montréal, QC, Canada, Sept. 2007.
[22]  R. Pichevar, H. Najaf-Zadeh, and L. Thibault, "A Biologically-Inspired Low-Bit-Rate Universal Audio Coder",Audio Engineering Society Convention, Vienna, Austria, 2007 (pdf).
[23]  H. Najaf-Zadeh, R. Pichevar, and L. Thibault, "Audio Masking of Gammatone/Gammachirp-Generated Spikes ", Technical Memorandum, CRC, 2007.
[24]  R. Pichevar, H. Najaf-Zadeh, and L. Thibault, "An Acoustic-Event-Based Audio Coding with Spikes", Technical Memorandum, CRC, 2006.
[25]  J. Rouat, S. Loiselle, R. Pichevar, "Acoustic Representation and Processing: It is time!", Neural Information Processing Systems' (NIPS) Workshop on Acoustic Processing 2006, Vancouver, Canada.
[26]  S. Loiselle, R. Pichevar, and J. Rouat, "Toward computational models of sound processing", Computational Neuroscience Symposium, Montreal, Canada, May, 2006.
[27]  R. Pichevar and J. Rouat, "The Dimensionally-Reduced Oscillatory Dynamic Link Matcher", Computational Neuroscience Symposium, Montreal, Canada, May, 2006.
[28]  R. Pichevar, J. Rouat, "Sound Separation in Natural Environments: A Bio-Inspired Approach", Sensory Coding And The Natural Environment Workshop, Queen's College, Oxford, UK.
[29]  R. Pichevar, J. Rouat, " Oscillatory Dynamic Link Matcher: A Bio-Inspired Neural Network for Pattern Recognition ", BICS'2004, Stirling, UK (invited paper, selected by the organizing committee for publication in the special journal issue, nominated for the best paper award).
[30]  R. Pichevar, J. Rouat, C. Feldbauer, and G. Kubin," A Bio-Inspired Sound Source Separation Technique Based On a Spiking Neural Network in Combination with an enhanced Analysis/Synthesis filterbank", EUSIPCO 2004, Vienna, Austria (Sound Demos).
[31]  R. Pichevar and J. Rouat, "Streaming of Audio Objects on 2D Spectral Maps Through Multiplicative Synaptic Connection Neurons", APCAM 2003, Vancouver, BC, Canada.
[32]  R. Pichevar and J.Rouat, "Cochleotopic/AMtopic (CAM) and Cochleotopic/Spectrotopic (CSM) Map based Sound Source Separation using Relaxation Oscillatory Neurons", IEEE NNSP 2003, Toulouse, France.
[33]  R. Pichevar and J. Rouat, "Oscillatory Dynamic Link Matching for Pattern Recognition", NCWS 2003 (Neural Coding Workshop), Aulla, Italy (pdf).
[34]  R. Pichevar and J. Rouat, "Binding of Audio Elements in the Sound Source Segregation Problem via a Two-Layered Bio-Inspired Neural Network", IEEE CCECE 2003, Montréal, QC, Canada (pdf).
[35]  R. Pichevar and J. Rouat, "Double-vowel Segregation Through Temporal Binding: A Bio-inspired Neural Network Paradigm", NOLISP'03 (Nonlinear Signal Processing), Le Croisic, France (pdf).
[36]  R. Pichevar, J. Rouat, and R. Balleraud, "Binding of audio elements in the sound source segregation problem via a two-layered bio-inspired neural network: Preliminary examples". In COST277 meeting, Edinburgh, U.K., 2002.
[37]  R. Pichevar and J. Rouat, " Vowel Segregation based on a Cochleotopic/AMtopic Map using a Biological Neural Network", APCAM 2002, Kansas City, USA.
[38]  J. Rouat and R. Pichevar, "Nonlinear Speech Processing techniques for source segregation", EUSIPCO 2002 (invited paper), Toulouse, France.
[39]  R. Pichevar and J. Rouat, " Traitement de processus spatio-temporels via un réseau de neurones à décharges", ACFAS, Sherbrooke, Canada (2001). (in English: "Spatio-temporal process analysis using spiking neurons ").
[40]  R. Pichevar, "Encryptage par réseaux de neurones", Technical report, UQAC, June 2001.
[41]  R. Pichevar and V.Tabataba Vakili, "Channel Equalization Using Neural Networks", IEEE International Conference on Personal Wireless Communications, ICPWC'99, Jaipur.
[42]  R. Pichevar and V.Tabataba Vakili, "Channel Equalization Using a Fuzzy Controlled Backpropagation Network", FAST IEEE Conference on CS & IT. (FISC'98).