|
Justin
Dauwels
Office phone:
+65-6790-5410
Address:
50 Nanyang Avenue,
Singapore 639798
|
Short Biography
Justin Dauwels
is an Assistant Professor with School of Electrical &
Electronic Engineering at
Nanyang
Technological University (NTU).
His
research interests are in Bayesian statistics, iterative signal
processing, and computational neuroscience. He enjoys working on
real-world problems, often in collaboration with medical practitioners.
He also tries to bring real-world problems into the classroom.
Prior to joining NTU, Justin was a research scientist during 2008-2010 in the Stochastic Systems Group (SSG)
at the
Massachusetts Institute of
Technology, led by
Prof.
Alan Willsky. He received postdoctoral training during 2006-2007
under the guidance of
Prof.
Shun-ichi Amari and Prof.
Andrzej Cichocki at the RIKEN
Brain Science Institute in Wako-shi, Japan.
He obtained a PhD degree
in
electrical engineering at the Swiss
Polytechnical Institute of Technology (ETH) in Zurich in December
2005, supervised by Prof.
Hans-Andrea
Loeliger, and was a
teaching
and research assistant at
the
Signal and Information Processing
Laboratory (ISI) of the Department
of Information Technology and Electrical Engineering at ETH Zurich
from 2000 to 2005. In 2000
he received the
engineering physics degree
from the
University of Ghent. From
1999 to 2000, he was an exchange student at ETH, and completed his
master's
thesis at the
Institute of Neuroinformatics in
Zurich.
Justin was a
visiting
researcher at the MIT Media Lab
(Physics and Media Group)
in Fall 2003 and the University of Ghent (Digital Communications Research
Group) in January 2004.
In Spring 2004 he
was an intern
at the
Mitsubishi Electric Research Lab
(Cambridge, MA) under supervision of Dr. Jonathan Yedidia.
He has been a JSPS
postdoctoral fellow (2007), a
BAEF fellow
(2008), a
Henri-Benedictus Fellow of the King Baudouin
Foundation (2008), and
a JSPS invited fellow (2010).
He is a member of the IEEE
and the IMS. He is a
research affiliate with Stochastic Systems Group (SSG)
at the
Massachusetts Institute of
Technology,
the Neurology Department
at
Massachusetts
General Hospital, and the
RIKEN
Brain Science Institute.
News
- I'm recruiting
outstanding and motivated PhD students
and postdoctoral researchers
to
conduct research at the interface of biology and electrical
engineering.
Topics include:
- modeling of epileptic seizures (from
abstract network models to detailed biophysical models),
- neural implants for seizure
suppression (from control/game theoretic analysis to hardware design),
- diagnosis of brain disorders from EEG
and other brain signals (Alzheimer's disease and epilepsy),
- graphical models and nonparametric
statistical models for analyzing electrophysiological data (e.g., spike
sorting and decoding),
- principled statistical models for
merging different brain imaging modalities
(EEG/MEG/fMRI/DTI/single-unit recordings/...),
- compression of brain signals, with
application to brain-computer interfaces and monitoring of epileptic
patients (from information theoretic analysis to practical algorithms)
Besides the above positions, I'm also recruiting
students and postdocs
for projects within the Singapore-MIT
Alliance for Research &
Technology (SMART), to be supervised by myself and MIT
faculty.
In those projects we apply mathematical engineering to problems
in bioengineering and biochemistry, for
example:
- Bayesian multiscale modeling of cell physiology,
- stochastic
modeling and control engineering in the context of tissue generation.
Please contact me if you're interested. More
information on living in Singapore can be found here.
Information about various scholarships
can be found here
and also here.
Research
Interests
- Bayesian
statistics and graphical
models for signal
processing, machine
learning, and digital
communications
- Computational neuroscience
(biophysical models of
brain disorders; analysis
of spike data, EEG, MEG etc. using state-of-the-art methods
of statistical inference, signal processing and combinatorial
optimization)
- Machine learning (e.g.,
Monte
Carlo methods)
- Theoretical statistics
(information geometry,
higher-order asymptotic theory)
Journal Papers and Book
Chapters
Signal
Processing, Machine Learning, and
Applied Information Theory
- J. Dauwels, A. Eckford, S. Korl, and H.-A. Loeliger,
Expectation maximization as message passing - Part I:
principles and Gaussian messages,
submitted to IEEE Transactions on Information
Theory.
arXiv:0910.2832.
- B. Kurkoski and J. Dauwels,
Iterative decoding of lattice codes using
Gaussian mixtures, EEE Communications Letters, vol. 14, no. 5,
May 2010.
- J. Dauwels, and H.-A. Loeliger,
Computing information rates
of continuous channels with memory by particle methods, IEEE Transactions on Information Theory, vol. 54, no. 1,
pp. 406–409, Jan. 2008
PDF file, 219
KB.
- H.-A. Loeliger, J. Dauwels, J. Hu, Li Ping,
S. Korl, and F. Kschischang,
The factor graph approach to model-based
signal processing, Proc. of the IEEE, vol. 95, no. 6, pp.
1295–1322, June 2007 (invited
paper).
PDF file, 1356
KB.
- B. Vigoda, J. Dauwels, N. Gershenfeld, and
H.-A. Loeliger,
Synchronization of
pseudo-random signals by forward-only message passing with application
to electronic circuits,
IEEE
Trans. Inform. Theory, vol. 52, no. 8, pp. 3843–3852, August 2006.
PDF file, 335
KB.
Computational
Neuroscience
- J. Dauwels,
Y. Tsukada, et al.
On the
synchrony of morphological and molecular signaling events in cell
migration, in preparation for BMC BioInformatics.
- J. Dauwels, S.S. Cash et al.
Automated localization of the seizure focus
from interictal intracranial EEG,
in preparation for NeuroImage.
- J. Dauwels, T.
Weber, F. Vialatte, and A. Cichocki,
Quantifying Statistical Interdependence by
Message Passing on Graphs PART III: N > 2 Point Processes, in preparation for Neural Computation.
- F. Vialatte, J. Dauwels, M.
Maurice, and A. Cichocki,
Improving the specificity of EEG for
diagnosing Alzheimer's disease,
submitted to International
Journal
of Alzheimer's Disease, (invited paper).
- J. Dauwels, F.
Vialatte, and A. Cichocki,
Diagnosis of Alzheimer’s Disease from EEG
Signals: Where Are We Standing?,
Current
Alzheimer's Research, (invited paper).
PDF file, 356
KB.
- F. Vialatte, M. Maurice, J.
Dauwels, and A. Cichocki,
SSVEP useful paradigms in neuroscience, and
potential applications in BCI: open questions and challenges, Progress in Neurobiology, 2010,
90:418-438. (invited paper).
link
- F. Vialatte, J. Dauwels, M. Maurice, and A.
Cichocki,
Steady-state visually evoked potentials:
time-frequency analysis and oscillatory event synchrony,
Cognitive Neurodynamics, 2009, 3(3):251-261.
link
(open access)
- F. Vialatte, J. Sole-Casals, J. Dauwels, M.
Maurice, and A. Cichocki,
Bump Time-Frequency Toolbox: a Toolbox for
Time-Frequency Oscillatory Bursts Extraction in Electrophysiological
Signals, BMC Neuroscience, 2009, 10:46.
link
- J. Dauwels, F. Vialatte, T.Weber, and A.
Cichocki,
Quantifying Statistical Interdependence by
Message Passing on Graphs PART I: One-Dimensional Point Processes, Neural
Computation, 2009, 21(8):2152-2202
PDF file, 1512
KB.
- J. Dauwels, F. Vialatte, T.Weber, T.Musha and
A.
Cichocki,
Quantifying Statistical Interdependence by
Message Passing on Graphs PART II: Multi-Dimensional Point Processes, Neural
Computation, 2009, 21(8):2203-2268.
PDF file, 857
KB.
- J. Dauwels, F. Vialatte, M. Vialatte, and A.
Cichocki,
A Comparative Study of Synchrony Measures
for the Early Diagnosis of Alzheimer’s Disease Based on EEG,
NeuroImage, 2010, 49:668-693.
PDF file, 661
KB.
- F. Vialatte, J. Dauwels, T. Rutkowski, and A.
Cichocki,
Oscillatory Event Synchrony during Steady
State Visually Evoked Potentials, Advances in Cognitive
Neurodynamics, Springer, October 2008 (invited paper).
- J. Dauwels, F. Vialatte, T. Rutkowski, and A.
Cichocki,
Measuring Neural Synchrony by Message
Passing, In Advances in Neural Information
Processing Systems 20,
Edited by Platt J, Koller D, Singer Y, Roweis S,
Cambridge, MA: MIT Press 2008:361-368.
PDF file, 263
KB.
Conference Proceedings
Signal
Processing, Machine Learning, and
Applied Information Theory
- B. Kurkoski, J. Dauwels, and H.A. Loeliger,
Power-Constrained Communications
Using LDLC Lattices,
Proc. IEEE Int. Symp. on Information
Theory (ISIT 2009).
PDF file, 210
KB.
- B. Kurkoski and J. Dauwels,
Gaussian mixture reduction by L2-norm
minimization, with applications
to lattice decoding,
Proc. IEEE Int. Symp. on Information
Theory (ISIT 2008).
PDF file, 519
KB.
- J. Dauwels,
An algorithm to improve and validate
Cramer-Rao Bounds through the fibre bundle theory of local exponential families,
Proc. IEEE Int. Conf. on Acoustics
and Signal Processing (ICASSP), 2007.
PDF file, 79 KB.
- J. Dauwels,
Improving and validating Cramer-Rao bounds
through higher-order asymptotic estimationtheory: a case study,
Proc.
2006 IEEE Int. Symp. on Information Theory and its Applications
(ISITA), Seoul, South-Korea, Oct. 29–Nov. 1, 2006.
- J. Hu, H.-A. Loeliger, J. Dauwels, and F. Kschischang,
A general computation rule for lossy
summaries messages with examples from equalization,
Proc.
44th Allerton Conf. on Communication, Control, and Computing,
Monticello, Illinois, Sept. 27–29, 2006, (invited paper).
PDF file, 194
KB.
- J. Dauwels,
On convergence and stability properties of
decision-based inference algorithms on general graphs,
Proc. IEEE Int. Symp. Information
Theory (ISIT), 2007.
PDF file, 84 KB.
- J. Dauwels,
Variational message passing on factor graphs,
Proc. IEEE Int. Symp. Information
Theory (ISIT), 2007.
PDF file, 85
KB.
- J. Dauwels, Sascha Korl, and H.-A.
Loeliger,
Particle methods as message passing,
Proceedings of 2006 IEEE Int. Symp. Information Theory
PDF file, 84 KB.
- J. Dauwels and Sascha Korl,
A numerical method to compute Cramér-Rao-type bounds for
challenging estimation problems,
International Conference on Acoustics, Speech, and Signal
Processing (ICASSP 2006). (Student
Paper Contest Winner)
PDF file, 68
KB.
- T. Ott, J. Dauwels, and R. Stoop,
Sequential clustering by loopy belief propagation,
Proceedings of the European Conference on Circuit Theory and
Design, 2005.
- J. Dauwels,
Numerical computation of the capacity of continuous memoryless
channels,
Proceedings of the 26th Symposium on Information Theory in the
BENELUX, Brussels, Belgium, May 19 -20, 2005, pp. 221-228.
PDF file, 857
KB.
- J. Dauwels, S. Korl, and H.-A. Loeliger,
Expectation maximization for phase estimation,
Proceedings of the Eighth International Symposium on
Communication Theory and Applications, 2005.
PDF file, 146
KB.
- J. Dauwels, S. Korl, and H.-A.
Loeliger,
Steepest descent on factor graphs,
Proceedings of the IEEE ITSOC Information Theory Workshop 2005 on
Coding and Complexity.
PDF file, 132 KB.
- J. Dauwels, S. Korl, and H.-A. Loeliger,
Expectation maximization as message passing,
Proceedings of IEEE Int. Symp. Information Theory, 2005.
PDF file, 92 KB.
- J. Dauwels,
Computing Bayesian Cramér-Rao bounds,
Proceedings of the IEEE Int. Symp. Information Theory,
2005.
PDF file, 120 KB.
- J. Dauwels, H.-A. Loeliger, P. Merkli, and M.
Ostojic,
On Markov structured summary propagation and LFSR
synchronization,
Proc. 42nd Allerton Conf. on Communication, Control, and
Computing, (Allerton House, Monticello, Illinois), Sept. 29 - Oct.
1, 2004. (invited paper)
PDF
file, 196 KB.
- J. Dauwels, H. Wymeersch, H.-A. Loeliger and M. Moeneclaey,
Phase
Estimation and Phase Ambiguity Resolution by Message Passing,
Proc. 11th International Conference
on Telecommunications and Networking, pp. 150–155, Fortaleza, Brazil,
August 1–6, 2004.
- J. Dauwels and H.-A. Loeliger,
Computation
of Information Rates by Particle Methods,
Proc. 2004 IEEE International
Symposium on Information Theory, p. 178, Chicago, USA, June 27–July 2,
2004.
PDF
file, 160 KB.
- J. Dauwels and H.-A. Loeliger,
Phase
Estimation by Message Passing,
Proc. 2004 IEEE Int. Conf. on
Communications, pp. 523–527, Paris, June 20–24, 2004.
PDF
file, 196 KB.
- H.-A. Loeliger, J. Dauwels, V. M. Koch, S. Korl,
Signal
processing with factor graphs: examples,
First International Symposium on
Control, Communications and Signal Processing (ISCCSP 2004), Hammamet,
Tunisia, March 21–24, 2004. (invited
paper)
PDF
file, 148 KB.
- J. Dauwels, H.-A. Loeliger, P. Merkli, and M. Ostojic,
On
Structured-Summary Propagation, LFSR Synchronization, and
Low-Complexity Trellis Decoding,
Proc. 41st Allerton Conf. on
Communication, Control, and Computing, (Allerton House, Monticello,
Illinois), Oct. 1–3, 2003. (invited
paper)
PDF
file, 213 KB.
- J. Dauwels and H.-A. Loeliger,
Joint
Decoding and Phase Estimation: an Exercise in Factor Graphs,
Proc. 2003 IEEE Int. Symp.
Information Theory, p. 231, Yokohama, Japan, June 29 – July 4 , 2003.
PDF
file, 72 KB.
Computational
Neuroscience
- J. Dauwels, F.Vialatte, and A. Cichocki,
On the Early Diagnosis of Alzheimer's
Disease from EEG Signals: A Mini-Review,
Proc. 2nd International Conference
on Cognitive Neurodynamics (ICCN09), submitted.
- F. Vialatte, J. Sole-Casals, A. Hazart, D. Prvulovic, J. Dauwels,
J. Pantel, and C. Haenschel,
Modeling transient oscillations in the EEG
of patients with mild cognitive impairment,
Proc. 2nd International Conference
on Cognitive Neurodynamics (ICCN09), submitted.
- J. Dauwels, F. Vialatte, C. Latchoumane, J. Jeong, and A.
Cichocki,
Loss of EEG Synchrony in Early-Stage AD
patients: a Study with Multiple Synchrony Measures and Multiple EEG
Data Sets,
Proc. 31th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society
(EMBC09), in press (invited
paper)..
PDF file, 1007 KB.
- J. Dauwels, S. Cash, and E. Eskandar,
Localization of Seizure Onset Area from
Intracranial Non-Seizure EEG by Exploiting Locally Enhanced Synchrony,
Proc. 31th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society
(EMBC09), in press. .
PDF file, 69 KB.
- J. Dauwels, T. Weber, F. Vialatte, and A. Cichocki,
Analyzing brain signals by combinatorial
optimization,
Forty-Sixth Annual Allerton
Conference on Communication, Control, and Computing, September 23–26, 2008,
Allerton Retreat Center, Monticello, Illinois (invited paper).
- J. Dauwels, F. Vialatte, T. Weber, and A. Cichocki,
On similarity measures for spike trains,
International Conference on Neural
Information Processing, November 25–28, 2008, Auckland, New Zealand
2008.
PDF file, 310 KB.
- J. Dauwels, F. Vialatte, T. Weber, and A. Cichocki,
An Exemplar-Based Statistical Model for the
Dynamics of Neural Synchrony,
International Conference on Neural
Information Processing, November 25–28, 2008, Auckland, New Zealand
2008.
PDF file, 172 KB.
- J. Dauwels, Y. Tsukada, Y. Sakumura, S. Ishii, F. Vialatte, and
A. Cichocki,
On the synchrony of morphological and
molecular signaling events in cell migration,
International
Conference on Neural Information Processing, November 25–28, 2008,
Auckland, New Zealand 2008.
PDF file, 506 KB.
- F. Vialatte, J. Dauwels, J. Sole-Casals, M. Maurice and A.
Cichocki,
Improved Sparse Bump Modeling for
Electrophysiological Data,
International
Conference on Neural Information Processing, November 25–28, 2008,
Auckland, New Zealand 2008.
- F. Vialatte, M. Maurice, J. Dauwels, and A. Cichocki,
Steady State Visual Evoked Potentials in
the Delta Range (0.5-5 Hz),
International Conference on Neural
Information Processing, November 25–28, 2008, Auckland, New Zealand
2008.
- J. Dauwels, T. Weber, F. Vialatte, and A. Cichocki,
Stochastic Synchrony, Application to Neural
Signals and Early Prediction of Alzheimer’s Disease,
Proceedings
of the 3rd INFORMS Workshop on Data Mining and Health Informatics
(DM-HI 2008), J. Li, D. Aleman, R. Sikora, eds.
- J. Dauwels, T. Weber, F. Vialatte, and A. Cichocki,
Quantifying the Similarity of Multiple
Multi-Dimensional Point Processes by Integer Programming with
Application to Early Diagnosis of Alzheimer’s Disease from EEG,
Proc. 30th Annual
International Conference of the IEEE Engineering in Medicine and
Biology Society (EMBC08).
PDF file, 219 KB.
- J. Dauwels, T. Rutkowski, F. Vialatte, and A. Cichocki,
On the Synchrony of Empirical Mode
Decompositions with Application to EEG,
Proc.
IEEE Int. Conf. on Acoustics and Signal Processing (ICASSP), 2008.
PDF file, 175 KB.
- J. Dauwels, F. Vialatte, T. Rutkowski, and A. Cichocki,
Machine Learning Methods for Exploring EEG
Dynamics,
NIPS Workshop on Large-Scale Brain
Dynamics, 2007.
- T. Rutkowski, J. Dauwels, F. Vialatte, D. Mandic and A. Cichocki,
Time-Frequency and Synchrony Analysis of
Responses to Steady-state Auditory and Musical Stimuli from
Multichannel EEG,
NIPS Workshop on Music, Brain and
Cognition, 2007.
PDF file, 173 KB.
- J. Dauwels, F. Vialatte, and A. Cichocki,
A Comparative Study of Synchrony Measures
for the Early Detection of Alzheimer’s Disease Based on EEG,
Proc. 2007 International Conference
on Neural Information Processing (ICONIP),
13–16 November, 2007,
Kitakyushu, Japan.
PDF file, 301 KB.
- J. Dauwels, F. Vialatte, and A. Cichocki,
A Novel
Measure for Synchrony and Its Application to Neural Signals,
Proc. IEEE Int. Conf. on Acoustics
and Signal Processing (ICASSP), 2007 (invited paper).
Software
- Sequential Monte-Carlo methods to compute the information rate of
continuous channels with memory. Click here
to download.
- Toolbox
to extract sparse time-frequency models of electrophysiological signals
(e.g., scalp and intracranial EEG).
Invited talks and seminars
- Quantifying statistical
interdependence of point processes with application to spike data and
EEG,
Kyoto University,
November 2008.
PDF file, 8082 KB.
- Machine learning techniques for
quantifying neural synchrony: application to the diagnosis of
Alzheimer’s disease from EEG,
Max Planck Institute
Frankfurt, June 2008.
PDF file, 7490 KB.
- Machine learning techniques for
quantifying neural synchrony: application to the diagnosis of
Alzheimer’s disease from EEG,
ETH Zurich, June 2008.
PDF file, 7793 KB.
- Machine learning techniques for
quantifying neural synchrony: application to the diagnosis of
Alzheimer’s disease from EEG,
Massachusetts General Hospital, Boston, MA, May 2008.
PDF file, 7376 KB.
- Stochastic event synchrony: a
statistical tool for aligning multivariate multi-dimensional point
processes,
Tokyo Institute of Technology, March 2008.
- Machine Learning Techniques for
Quantifying Neural Synchrony: Application to the Early Diagnosis of
Alzheimer’s Disease from EEG,
LIDS, MIT, Feb. 2008.
- Machine
learning methods for exploring EEG dynamics,
Nara Advanced Institute
for Science and Technology (NAIST),
Nara, Dec. 2007.
- Human brain dynamics and synchrony
measures, applications to detection of Alzheimer’s disease,
Symposium on Brain Activity and
Information Integration, RIKEN, Wako-shi, Saitama, Japan, Sept. 13,
2007.
- Channel estimation by passing
messages in graphical models,
Deepening and Expansion
of Statistical Mechanical Informatics Workshop, The Institute of
Statistical Mathematics, Tokyo, Japan, August 27–28, 2007.
- Factor graph based signal processing,
Nara Advanced Institute
for Science and Technology (NAIST), Nara, Japan, Oct. 12, 2006.
PDF file, 914 KB.
- Factor graph-based inference:
algorithms and
bounds,
Workshop on Machine Learning
and
Optimization, The Institute of Statistical Mathematics, Tokyo, Japan,
August 16th, 2006.
- Computation
of
the capacity of continuous memoryless channels and the rate distortion
function of continuous memoryless sources,
2006 Hawaii, IEICE, and SITA Joint Conference on Information
Theory, Nara, Japan, May 23-26, 2006.
- On applications of
information geometry to
signal processing, digital communications, and related areas,
The 5th Workshop on Differential Geometry and Information
Geometry, Nagoya University, Japan, February 17-18, 2006.
- On
Information-geometric aspects of graphical models and kernel machines,
NIPS Workshop,
Whistler, Canada, December 9-10, 2005. PDF
file, 207KB.
- On
various
applications of message passing on factor graphs,
MIT (CSAIL/RLE/LIDS),
Cambridge, MA, December 13, 2005. PDF
file, 3.775KB.
- On
Cramér-Rao-bound paradoxes (and how to circumvent them),
University of Gent,
Belgium, June 03, 2005.
- Phase
estimation
by EM and steepest descent,
University of Gent, Belgium, May 24, 2005.
University of Louvain-la-Neuve (UCL), Belgium, May 23, 2005.
- RIKEN Brain Science
Institute, Saitama, Japan, Jan
06, 2005.
Part 1. Applications of graphical models in signal processing.
Part 2. An efficient algorithm to compute Cramér-Rao bounds in
graphical
models.
- An
analog circuit
that locks
onto a pseudo-noise signal,
Kanazawa
Institute of Technology, Japan, December 16, 2004.
- Message
Passing,
Factor Graphs and Analog Circuits,
School
and Conference on Fundamental Aspects of Complexity, Abdus
Salam
International Center for Theoretical Physics, Trieste, Sept. 6-9,
2004.
- An
analog circuit
that locks
onto a pseudo-noise signal, Workshop
on Statistical Aspects of Electronic Systems, Lavin,
Switzerland, October 28-30, 2004.
- Towards
Quantum
Algorithms for
Inference,
MediaLab, MIT, May 18, 2004.
- Turbo
Signal
Processing,
University of Gent, Sept. 11, 2003.
- Loeliger's
Universe,
MediaLab, MIT, Dec. 4, 2003.
Recently
Attended Workshops
- Neuro 2007,
Yokohama-shi, Kanagawa, Japan, Sept. 10–12, 2007.
- Retreat of the Picower Institute
for Learning and Memory (MIT), Cape Cod, MA, USA, May 30–June 1,
2007.
- Joint Workshop of RIKEN BSI and
Picower Institute for Learning and Memory, MIT, Cambridge, MA,
USA, May 29, 2007.
- Quantum
Systems
for Information
Technology Workshop, Flums,
Switzerland,
March 5-7, 2004.
Tutorials
- Kernel machines (presented
at ISI, 04/11/2004)
PDF
file, 2.265 KB.
- Posterior Cramér-Rao bounds for
estimation in
graphical models (presented
at ISI,
31/03/2005)
PDF
file, 2.491 KB.
PhD Thesis
Old Projects
- Self-Supervised
Learning of
Hierarchies, Diploma Thesis,
Institute
of Neuroinformatics, ETH Zurich and University of Zurich, Sept.
2000.
- Der
Sprachspielbegriff in Wittgensteins Uber Gewissheit, Hausarbeit
im Fach
Philosophie der FernUniversität Hagen, June 2001. PDF
file, 297 KB.
Teaching
- Teaching assistant for
Adaptive Filters and Neural Networks (Winter 2000, 2001 and 2002)
- Teaching assistant for
Digital Signal Processing
(Winter 2001)
- Teacher of Practical Signal
Processing with DSPs (Summer 2001)
- Teaching assistant for
Algebra, Codes and Signal Processing (Summer 2002)
Last modified: May
24, 2009
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