Bert de Vries's CV
Author:
Bert de Vries
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6 years ago
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Abstract:
Bert de Vries's CV
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Bert de Vries's CV
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\moveleft.5\hoffset\centerline{\large\bf Bert de Vries} % Your name at the top
\moveleft\hoffset\vbox{\hrule width\resumewidth height 1pt}\smallskip % Horizontal line after name; adjust line thickness by changing the '1pt'
\moveleft.5\hoffset\centerline{GN Hearing and Eindhoven University of Technology (\href{http://biaslab.org}{BIASlab})} % Your address
\moveleft.5\hoffset\centerline{Het Eeuwsel 6, 5612 AS, Eindhoven, the Netherlands}
\moveleft.5\hoffset\centerline{+31-619-222-046}
\moveleft.5\hoffset\centerline{bdevries@gnresound.com}
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\begin{resume}
\section{PRINCIPAL \\ INTERESTS}
Signal processing, (Bayesian) machine learning, computational neuroscience, biomedical engineering, research management, technical writing; applications to multimedia processing, medical devices, hearing rehabilitation and clinical trial design/analysis.
\section{ACADEMIC \\BACKGROUND}
{\sl Ph.D. Electrical Engineering} \hfill 1991 \\
\href{https://www.ece.ufl.edu/}{University of Florida}, Gainesville, FL
\begin{itemize}
\item Ph.D. research in signal processing under direction of prof. \href{http://www.cnel.ufl.edu/people/people.php?name=principe}{Jose C. Principe}.
Dissertation title: Temporal processing with neural networks--the development of the gamma model.
\end{itemize}
{\sl M.Sc. Electrical Engineering} \hfill 1986 \\
\href{http://tue.nl}{Eindhoven University of Technology} (TU/e), Eindhoven, the Netherlands
\begin{itemize}
\item Focus areas: medical engineering (thesis: intelligent alarms during anesthesia) and digital communications.
\end{itemize}
\section{EMPLOYMENT \\HISTORY}
{\sl Professor} \hfill 2012 - Present \\
\href{http://tue.nl}{Eindhoven University of Technology}, \href{http://biaslab.org}{BIASlab}, Eindhoven, Netherlands
\begin{itemize}
\item Founder/director \href{http://biaslab.org}{BIASlab} research laboratory
\item Research on \emph{Personalization of Medical Signal Processing Systems}
\item Teach graduate class on \href{http://bertdv.github.io/teaching/AIP-5SSB0/}{Adaptive Information Processing}
\item Inaugural lecture: \href{https://pure.tue.nl/ws/files/3682681/vries2013.pdf}{In Situ Personalization of Signal Processing Systems}; lecture at \href{http://goo.gl/EoU0SE}{ youtube}, 2013
\item previous TU/e engagement: Research Fellow ('04-'11)
\end{itemize}
{\sl Principal Scientist} \hfill 1999 - Present \\
\href{http://www.gn.com/}{GN Hearing} (Philips Hearing Technologies until 2001), Eindhoven, Netherlands
\begin{itemize}
\item Research PI on low-power signal processing technology for the next generation of digital hearing aids
\item Leadership/management tasks include(d) all aspects of team and project management (teams of about 10 engineers); (responsible for) the corporate DSP research track, including the roadmap, budget and management; initiating and managing key studies at academic institutions and contract research organizations
\item Other engagements at GN include(d): Key Opinion Leader ('14-pres.), DSP Functional Leader ('11-'14), Head DSP Research ('08-'11), Manager External Research ('01-'08), Technology Leader ('99-'01, Philips)
\end{itemize}
{\sl Member Technical Staff} \hfill 1992 - 1999 \\
\href{https://www.sri.com}{SRI International} (previously Sarnoff Corporation), Princeton, NJ
\begin{itemize}
\item Research in advanced signal processing algorithms, initiating new technical and commercial thrusts, technical proposal writing and project management
\item Principal investigator of funded projects on keyword spotting, digital hearing aids signal processing, speech enhancement and noise-robust speech recognition (co-PI)
\item Co-initiated and developed signal processing in financial markets program at Sarnoff
\item Member medical image processing research team. Funded projects include blind signal processing for breast mammography and perceptually optimized image coding
\item Other engagements at SRI included: Postdoctoral fellow ('92-'93)
\end{itemize}
\section{SPECIAL \\ ACHIEVEMENTS}
{\sl Awards}
\begin{itemize}
\item \emph{TU/e EE dept. Innovation Research Award} for ``research on Bayesian Intelligent Agents'', TU Eindhoven, EE department, Jan. 2019
\item \emph{Return-on-Performance Award}, for ``technical work on Speech Enhancement technology'', Sarnoff Corporation, 1998
\item \emph{David Sarnoff Achievement Award}, for ``leadership and technical contributions in the area of adaptive speech enhancement'', Sarnoff Corporation, 1997
\item \emph{David Sarnoff Event Focus Award} for ``Winning Sarnoff's First Commercial Contract for Speech Processing'', David Sarnoff Research Center, 1996
\item \emph{Presidential Recognition Award}, University of Florida, 1988
\item $\delta$\emph{-Butterweck Award} (awards top GPA), Technical University Eindhoven, 1984
\end{itemize}
{\sl Invited Lectures (selection)}
\begin{itemize}
\item AI Insight Talk at Google Amsterdam, "Automated Natural Design of Signal Processing Algorithms", Amsterdam, 17 May 2019
\item Design, Automation and Test in Europe conference (DATE-2019), "Automated Signal Processing Design through Bayesian Model-based Machine Learning", Florence (Italy), 28 March 2019
\item Annual conference Kring Klinische Audiologie, "In-situ Personalization of Hearing Devices", Putten (NL), Nov. 2017
\item University College London (UCL), "A Factor Graph Approach to Active Inference", Nov. 2016
\item Cochlear/ReSound Event, Keynote lecture on "The Future of Hearing Aid personalization", Sep.2016
\item WIC Mid-winter meeting on 'Big Data and Data Analytics', "Design of Signal Processing Algorithms through Probabilistic Inference", Eindhoven, February 2016
\item \href{http://www.cqm.nl/}{CQM}, "In Situ Machine Learning for Signal Processing Systems", Eindhoven, August 2015
\item Radboud University Nijmegen, "Probabilistic Hearing Loss Compensation", Nijmegen, March 2015
\item INCAS3 Institute, "In Situ Personalization of Signal Processing Systems", Assen, October 2014
\item Leiden University Medical Center, New Year's keynote lecture on "Personalization of Medical Signal Processing Systems", Leiden, January 2014
\item Int'l Symposium on Auditory and Audiological Research (ISAAR), "Is Hearing Aid Signal Processing ready for Machine Learning?", Nyborg (DK), August 2013
\item Clinical Physicist Post-graduate school,''The Future of Hearing Aids'', Amersfoort January 2013
\item Delft Univ. of Technology, ''Machine Learning for Hearing Aids Technology'', Delft March 2012
\item International Forum for Hearing Instrument Developers, ''Bayesian Machine Learning for Hearing Aid Design, Fitting and Personalization'', Oldenburg (Germany), June 2011
\item University of Florida, ''Machine Learning Trends in the Hearing Aids Industry'', Gainesville, FL, April 2010
\item SIKS Research School, ''Gaussian mixture models and the EM Algorithm'', Vught, NL, Dec 2008
\item GN Nordic Audiology College, ''Learning technology in hearing aids'', Oslo, Norway, Sep 29, 2006
\item University of Nijmegen, ''Machine learning for hearing aids'', Nijmegen, Netherlands, June 2004
\item University of Florida, ''DSP for modern industrial hearing aids'', Gainesville, FL, January 2004
\item International Forum for Hearing Aid Developers, ''Warped-frequency filterbanks'', Oldenburg, Germany, July 2003
\item Keynote address ''An industrial perspective on intelligent hearing aids'' at 2nd McMaster-Gennum Workshop on Intelligent Hearing Instruments, Niagara-on-the-Lake, ON, Sep 2001
\item NIDCA/NASA/VA Hearing Aids Improvement Conference, May 1997
\item Lucent Technologies, Bell Laboratories, November 1996
\item AT\&T Research, Murray Hill, NJ, July 1996
\item NSA (U.S. Government), June 1993
\item Neural Network Workshop, Rutgers University, October 1992
\item David Sarnoff Research Center, October 1991
\end{itemize}
{\sl Professional Activities (selection)}
\begin{itemize}
\item Associate Editor for \href{http://tnsre.embs.org/}{IEEE Transactions on Neural Systems and Rehabilitation Engineering}, 2012 - 2018
\item Invited member annual European Mathworks Advisory Board meetings, 2012 - 2015
\item Invited jury member for Open Technology Program (OTP) research proposals to Dutch Technology Foundation (STW), 2010
\item Invited DSP expert on IWT (Flemish Institute for Science and Technology) panel to evaluate candidate PhD proposals, Brussels, 2005 and 2006
\item Organizer/chair special session "DSP for Intelligent Hearing Aids", ICASSP 2002, Orlando, FL, 2002
\item Publicity chair, Neural Networks for Signal Processing Workshop, Amelia island, Florida (1997) and Cambridge, UK, 1998
\item Session chair Non-linear Systems Identification, ICASSP-96, Atlanta, GA (1996) and IEEE NNSP-98 Workshop, Cambridge, UK, 1998
\item (Elected) member of ''IEEE Technical Committee on Neural Networks for Signal Processing Society'', 1995-1998
\item Invited researcher in government sponsored ''Robust Speech Processing Workshop'', 1993
\item Member of various professional societies (e.g. IEEE, INNS), 1986 - present
\end{itemize}
{\sl Refereed Publications}
IEEE Transactions on Signal Processing, IEEE Transactions on Neural Networks, NeuroComputing Journal, Neural Networks Journal, EURASIP Journal of Applied Signal Processing, Advances in Neural Information Processing Systems (NIPS) Conferences, Interspeech, ICASSP Conferences and others
%\bigskip
%\moveleft 1.3\hoffset\centerline{\large\bf Activities at Eindhoven Univ. of Technology (TU/e)}
\section{RESEARCH \\FUNDING \\ (at TU/e)}
Research at TU/e focusses on applications of Bayesian machine learning to personalization of hearing aid algorithms.
\begin{itemize}
\item (2018-2022), financial support for 4 PhD students by GN Hearing and TU Eindhoven in the context of a "mini-impulse" research program on \emph{collaborative hearing}.
\item $750$K euro (2018 - 2022), together with \href{https://www.linkedin.com/in/henkjan-huisman-28a7b34b/}{Henkjan
Huisman}
and \href{http://www.es.ele.tue.nl/~heco/}{Henk
Corporaal} to support 3 PhD
students, from \href{https://www.nwo.nl/en}{NWO}
for research on \emph{deep learning for human and animal health},
in the context of \href{https://www.nwo.nl/en/news-and-events/news/2017/32-million-euros-for-top-level-technological-research.html\#zelflerend}{Efficient
Deep Learning}.
\item $550$K euro (2017 - 2021), together with \href{http://www.es.ele.tue.nl/~sander/}{Sander
Stuijk} and \href{http://www.es.ele.tue.nl/~heco/}{Henk
Corporaal}, supporting 3 PhD
students, from \href{http://www.nwo.nl/en}{NWO}
to pursue research on \emph{Autonomous Acoustic
Systems} in the context of
\href{http://www.stw.nl/en/node/8025}{energy-autonomous
systems for IoT}.
\item $500$K euro (2015 - 2019), together with
\href{http://www.sps.ele.tue.nl/members/T.J.Tjalkens}{Tjalling
Tjalkens}, supporting 2 PhD
students, from Dutch Technology Foundation
\href{http://www.stw.nl/en/}{STW} to pursue
research on
\href{http://stw.nl/nl/content/hearscan-towards-data-driven-hearing-aids}{Data-driven
Hearing Aids}.
\item $500$K euro (2014 - 2018), supporting 2 PhD students
at TU/e, from GN ReSound to support research on hearing aids
personalization.
\item $130$K euro (2006 - 2008) from GN ReSound to support 2 PDEng students at TU/e.
\item $650$K euro (2006 - 2010), together with
\href{http://www.cs.ru.nl/staff/Tom.Heskes}{Tom
Heskes} and
\href{http://www.ac-amc.nl/medewerkers/dreschler.html}{Wouter
Dreschler}, from
\href{http://www.stw.nl}{STW} to pursue further
research on
\href{http://www.nwo.nl/en/research-and-results/research-projects/35/2300148635.html}{Personalization
of Hearing Aids through Bayesian Preference Elicitation}.
\end{itemize}
\section{TEACHING \\ (at TU/e)}
\begin{itemize}
\item {\sl \href{http://bertdv.github.io/teaching/AIP-5SSB0/}{Adaptive Information Processing (5SSB0)} \hfill 2005-Present} \\
Together with \href{http://www.sps.ele.tue.nl/members/T.J.Tjalkens}{Tjalling Tjalkens}, core
graduate class on the fundamentals of machine learning.
\item {\sl Development of
(Electro)-technology \hfill 2011-2017} \\
Guest lecturer for introductory EE course
\end{itemize}
\section{STUDENT \\ SUPERVISION \\ (at TU/e)}
\begin{etaremune}
\item Ismail Senoz, {\em Generative
Probabilistic Models for Audio Textures}, M.Sc. thesis, 10/2017
\item Jiyang Li, {\em Online Preference Learning}, M.Sc. internship, 9/2017
\item Anouk van Diepen, {\em A Probabilistic
Modeling Approach to In-situ Trainable Gesture Recognition}, M.Sc. thesis, 5/2017
\item Wouter van Roosmalen, {\em In-situ
Design of Noise Reduction Algorithms}, M.Sc. thesis, 6/2016
\item
Anouk van Diepen, {\em Derivation and
Implementation of Gausssian Mixture Model in a Forney-style Factor
Graph} M.Sc. internship, 6/2016
\item
Pradeep Kumar, {\em On
Discrete-Valued Message Passing in Factor Graphs} M.Sc. practical training project, 10/2015
\item
Rene Duijkers, {\em A Factor Graph
Approach to Hearing Loss Compensation} M.Sc. thesis, 10/2014
\item
Max Schoonderbeek, {\em A Factor Graph
Approach to Gaussian Process Preference Learning} M.Sc. thesis, 10/2014
\item
Art Senders, {\em A Julia
Toolbox for Forney-style Factor Graphs}, M.Sc. practical training project, 6/2014
\item Robert Leenders, {\em Gaussian Process
based Preference Learning as a Classification Problem} B.Sc. final project, 4/2014
\item
Rene Duijkers,
{\em Online
Bayesian Spectral Tracking}, M.Sc. practical training project, 1/2014
\item
Brian Hutama Susilo,
{\em Automated Tuning Algorithm for Low-latency PC-based Audio
Processing} M.Sc. practical training project, 12/2013
\item
Zijian Xu, {\em Fast
Design of Audio Processing Algorithms by Interactive Parameter
Exploration}, M.Sc. thesis, 8/2013
\item
Timur Bagautdinov, \href{https://github.com/bertdv/bertdv.github.io/blob/master/files/bagautdinov-thesis.final.pdf}{A
Machine Learning Framework for Bayesian Signal
Processing}, M.Sc. thesis, 8/2013
\item
Marno van der Maas, {\em Browser-based
Remote Control of Hearing Aids}, B.Sc. research project, 6/2013
\item Timur Bagautdinov, {\em A
MATLAB/C++ toolbox for Factor Graph Modeling}, M.Sc. traineeship project, 12/2012
\item Maarten Thomassen, {\em Spectral Audio Monitoring}, M.Sc. practical training project, 6/2012
\item
Joris Kraak, {\em Computer-Aided
Algorithm Design for Audio Processing}, M.Sc.-thesis, 4/2012
\item Joris Kraak, {\em Optimization of a Spectral Noise Tracking Algorithm}, M.Sc. practical training project, 10/2010
\item
Jianfeng Li, {\em Acoustic
scene-adaptive speech enhancement}, M.Sc.-thesis, 8/2010
\item Jianfeng Li, {\em Spatial defect clustering on
semiconductor wafers using image processing techniques}, M.Sc. thesis, 8/2009
\item Xueru Zhang, {\em Bayesian periodogram
smoothing for speech enhancement}, PD.Eng.-thesis, 9/2008
\item Rene Besseling, {\em Gaussian processes in
Bekesy audiometry}, M.Sc. project, 6/2008
\item Serkan Ozer, {\em Bayesian linear regression for
user-adaptive hearing aids}, M.Sc. thesis, 8/2007
\item
Ronnie van Loon, {\em a Probabilistic Approach
to Sound Classification} M.Sc.thesis, 6/2007
\item Anton Vakrushev, {\em Interactive machine
learning for Personalization of hearing aid algorithms}, PD.Eng. thesis, 9/2006
\item Jorik Caljouw, {\em PDA-based
Interfacing to a real-time audio platform}, M.Sc. practical training, 10/2005
\item
Paul Aelen, {\em Determination of the
Intra-Uterine Pressure with electrodes on the abdomen}, M.Sc. thesis, 10/2005
\item
Job Geurts, {\em A PC-based
real-time simulation platform for evaluating hearing aid algorithms}, M.Sc. practical training, 6/2005
\end{etaremune}
\section{SUPERVISOR \\ PhD \\COMMITTEE}
\begin{etaremune}
\item Thijs van de Laar, Ph.D., \emph{Automated Design of Bayesian Signal Processing Algorithms}, TU Eindhoven, 6/2019
\end{etaremune}
\section{MEMBER PhD\\ COMMITTEE}
\begin{etaremune}
\item Chara Papatsimpa, Ph.D. \emph{Performance of Intelligent Lighting Sensor Networks: Analysis, Modelling and Distributed Architectures}, TU Eindhoven, 5/2019
\item Andreas Koutrouvelis, Ph.D., \emph{Multi-microphone Noise reduction for Hearing Assistive Devices}, Delft University of Technology, 12/2018
\item Juan Sebastian Olier, Ph.D., \emph{Dynamic Representations: Building knowledge through an active representational process based on deep generative models}, Eindhoven University of Technology, 10/2018
\item
Henk Kortier, Ph.D., {\em Assessment of Hand Kinematics and
Interactions with the Environment}, University of Twente, 02/2018
\item
Math Verstraelen, Ph.D., {\em The WaveCore - A Scalable
Architecture for Real-time Audio Procesing} University of Twente, 01/2017
\item
Amir Jalalirad, Ph.D., {\em Supervised Learning through
Feature-based Models}, TU Eindhoven, 12/2016
\item
Yuan Zeng, Ph.D., {\em Distributed Speech Enhancement in Wireless
Acoustic Sensor Networks}, Delft University of Technology, 6/2015
\item
Ingeborg Brons, Ph.D., {\em Perceptual evaluation of noise
reduction in hearing aids}, University of Amsterdam, 12/2013
\item
Jelte Vink, Ph.D., {\em Machine Learning for Efficient Object
Recognition}, TU Eindhoven, 9/2013
\item
Adriana Birlutiu, Ph.D., {\em Machine Learning for Pairwise Data},
University of Nijmegen, 10/2011
\end{etaremune}
\section{PROFESSIONAL \\ INTERVIEWS}
\begin{etaremune}
\item
\href{http://www.audiology-worldnews.com/focus-on/1215-introducing-data-science-hearing-aids-on-the-brink-of-a-paradigm-shift}{Introducing
Data Science: Hearing Aids on the Brink of a Paradigm
Shift]}. Interview in
\href{http://www.audiology-worldnews.com}{Audiology Info
Magazine}, Dec 2014
\end{etaremune}
\section{PATENTS}
\begin{etaremune}
\item Bert de Vries, Andrew Dittberner and Joris Kraak, \emph{Hearing System, Accessory Device and Related Method for Situated Design of Hearing Algorithms}, filed by GN, P2048EP00, Nov 2018
\item
Bert de Vries, Marco Cox and Joris Kraak, {\em Hearing Device and Method
for Tuning Hearing Device Parameters}, filed by GN, 2017P00065EP, Dec
2017
\item
Almer van den Berg and Bert de Vries, {\em Sound signal modelling based on
recorded object sound}, filed by GN ReSound, EP16206941.3, Dec.~2016
\item
Bert de Vries and Joris Kraak, {\em Automated Scanning for Hearing Aid
Parameters}, filed by GN ReSound, July 2016
\item
Fredrik Gran et al., {\em Performance-based In Situ Optimization of Hearing
Aids}, filed by GN ReSound, US-2017055090, priority date June 2015, pub
date Dec 2016
\item
Bert de Vries and Erik van der Werf, {\em A Multi-band Signal Processor for
Digital Audio Signals}, filed by GN ReSound, US-2015317995, EP-2941020,
priority date May 2014
\item
Andrew Dittberner, Bert de Vries et al., {\em A Location Learning Hearing
Aid}, filed by GN ReSound, JP-2015130659, US-2015172831, EP-2884766,
priority date Dec.~2013
\item
Bert de Vries and Mojtaba Farmani, {\em A Hearing Aid with Probabilistic
Hearing Loss Compensation}, filed by GN ReSound, CN-105706466,
EP-2871858, priority date Nov.~2013
\item
Bert de Vries et al., {\em Efficient evaluation of hearing ability}, filed
by GN ReSound, US Patent 9,560,991 (granted 2017), priority date April
2009
\item
Alexander Ypma et al., {\em Asymmetric adjustment}, filed by GN ReSound, US
patent 8792659 (granted 7/2014), priority date Nov-2008
\item
Alexander Ypma et al., {\em Learning control of hearing aid parameter settings}, filed by GN ReSound, US patent 9408002 (granted 8/2016),
priority date Mar-2006
\item
Bert de Vries and Alexander Ypma, {\em Optimization of Hearing Aid
Parameters}, filed by GN ReSound, US patent 9084066 (granted 7/2015),
priority date Oct 2005
\item
David Zhao, Bastiaan Kleijn, Alexander Ypma and Bert de Vries, {\em Method
and Apparatus for Improved Estimation of Non-stationary Noise for
Speech Enhancement}, filed by GN ReSound, US patent 7590530 (granted
8/2009), priority date Sep 2005
\item
Bert de Vries and Rob de Vries, {\em Fitting methodology and hearing
prosthesis based on signal-to-noise ratio loss data}, US patent 7804973
(granted 9/2010), priority date 2/2002
\item
L. Parra and B. de Vries, {\em Method and apparatus for adaptive speech
detection by applying a probabilistic description to the
classification and tracking of signal components}, patent registered
for Sarnoff Corporation, LG Electronics, Inc., US patent 6691087
(granted Feb-2004), priority date Nov 1997
\item
Bert de Vries, {\em Noise Spectrum Tracking for Speech Enhancement}, patent
registered for Sarnoff Corporation, no. US6289309, 9/11/2001
\item
J. Lubin et al., {\em Method and apparatus for training a neural network to
learn and use fidelity metric as a control mechanism}, patent
registered for Sarnoff Corporation, no. US6075884, 6/13/2000
\item
Bert de Vries, {\em Method and apparatus for filtering signals using a
gamma delay line based estimation of power spectrum}, patent registered
for Sarnoff Corporation, no. US6073152, 6/6/2000
\item
M. Brill, J. Lubin, B. de Vries, O. Finard, {\em Method and apparatus for
assessing the visibility of differences between two image sequences},
patent registered for Sarnoff Corporation, no. US5974159, 10/26/1999
\item
Bert de Vries, {\em Method and system for training a neural network with
adaptive weight updating and adaptive pruning in principal components
space}, patent registered for David Sarnoff Research Center, no.
5,812,992, 9/22/98
\item
Bert de Vries and Jose Principe, {\em An adaptive filter based on a
recursive delay line}, patent registered for University of Florida, no.
5,301,135, April 1994
\end{etaremune}
\section{JOURNAL \\ARTICLES}
See also \href{https://scholar.google.nl/citations?user=x3EIIHEAAAAJ&hl=en}{my google scholar} page. \\
\begin{etaremune}
\item Thijs van de Laar and Bert de Vries, \href{https://goo.gl/TH9abN}{Simulating Active Inference Processes by Message Passing}, \emph{Frontiers in Robotics and AI}, March 2019
\item Marco Cox, Thijs van de Laar and Bert de Vries,
\href{https://goo.gl/Y9Faz8}{A Factor Graph Approach to Automated Design of Bayesian Signal Processing Algorithms}, \emph{International Journal of Approximate Reasoning}, Nov. 2018
\item
Bert de Vries and Karl J. Friston,
\href{https://www.frontiersin.org/articles/10.3389/fncom.2017.00095/full}{A
Factor Graph Description of Deep Temporal Active
Inference}, {\em Frontiers in Computational Neuroscience}, Oct.~2017
\item
Karl J. Friston, Thomas Parr and Bert de Vries,
\href{http://www.mitpressjournals.org/doi/abs/10.1162/NETN_a_00018}{The
graphical brain: belief propagation and active inference},
{\em Network Neuroscience}, the MIT Press, vol.1, no.1, pp.1-78, 2017
\item
Thijs van de Laar and Bert de Vries,
\href{http://arxiv.org/abs/1602.01345}{A Probabilistic
Modeling Approach to Hearing Loss Compensation}, {\em IEEE
Tr. on Audio, Speech and Language Processing}, Nov.~2016
\item
Rik Vullings et al., An Adaptive Kalman Filter for ECG Signal
Enhancement, {\em IEEE Transactions on Biomedical Engineering},
vol.58, no.4, April 2011
\item
A. Ypma et al.,
\href{http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/183456}{On-line
Personalization of Hearing Instruments}, {\em EURASIP
Journal on Audio, Speech, and Music Processing}, September 2008
\item
Tjeerd Dijkstra et al.,
\href{http://www.hearingreview.com/issues/articles/2007-10_05.asp}{The
Learning Hearing Aid: Common-Sense Reasoning in Hearing Aid
Circuits}, The Hearing Review, October 2007
\item
David Zhao et al., On-line Noise Estimation Using Stochastic-Gain HMM
for Speech Enhancement, {\em IEEE Transactions on Audio, Speech and
Language Processing}, vol.16, no.4, May 2008
\item
Jose Principe et al., Locally Recurrent Networks: The Gamma Operator,
Properties and Extensions, invited book chapter in {\em Neural
Networks and Pattern Recognition}, Omidvar and Dayhoff (eds.),
Academic Press, 1997
\item
Bert de Vries, Short term memory structures for dynamic neural
networks, book chapter in: {\em Artificial Neural Networks for Speech and Vision}, Richard Mammone (ed.), Chapman \& Hall Ltd., 1994
\item
Bert de Vries and Jose Principe, The gamma model--A new neural network
for temporal processing, {\em Neural Networks} vol.~5(4), pp.~565-576,
1992 {\bf {[}240{]}}
\item
Jose Principe and Bert de Vries, The gamma filter--A new class of
adaptive IIR filters with restricted feedback, IEEE transactions on
signal processing, vol.~41(2), pp.~649-656, 1992
\item
Bert de Vries,
\href{http://ufdc.ufl.edu/UF00082173/00001}{Temporal
processing with neural networks-the development of the Gamma
model}, {\em Ph.D.~dissertation}, University of Florida,
1991
\item
Joachim Gravenstein et al., Sampling intervals for clinical monitoring
of variables during anesthesia, {\em Journal of clinical monitoring}
vol 5(1), 1989
\item
Jan J. van der Aa, Bert de Vries and Joachim Gravenstein, Toward more
sophisticated monitoring alarms, {\em Journal of clinical monitoring}
4 (2), 1986
\end{etaremune}
\section{CONFERENCE \\ CONTRIBUTIONS}
\begin{etaremune}
\item Albert Podusenko, Wouter Kouw and Bert de Vries, Online Variational Message Passing in
Autoregressive Models, \emph{Symposium on Information Theory in the Benelux}, Ghent (Belgium), May 2019
\item Magnus Koudahl, Wouter Kouw and Bert de Vries, Agent Alignment by Active Inference, \emph{Symposium on Information Theory in the Benelux}, Ghent (Belgium), May 2019
\item Patrick Wijnings, Sander Stuijk, Bert de Vries and Henk Corporaal, Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring, \emph{Int'l Conference on Audio, Speech and Signal Processing (ICASSP)}, Brighton (UK), May 2019
\item Marco Cox, Thijs van de Laar, Bert de Vries, ForneyLab.jl: Fast and flexible automated inference through message passing in Julia, \emph{First Int'l conf. on Probabilistic Programming}, Boston (MA), October 2018
\item Thijs van de Laar et al., ForneyLab: A Toolbox for Biologically Plausible Free Energy Minimization in Dynamic Neural Models, \emph{Conference on Complex Systems}, Thessaloniki, Greece, September 2018
\item Ismail Senoz and Bert De Vries, Online Variational Message Passing In The Hierarchical Gaussian Filter, (\emph{Best student paper award}), \emph{Machine Learning for Signal Processing conference (MLSP)}, Aalborg, Denmark, September 2018
\item Ivan Bocharov et al., Acoustic Scene Classification from Few Examples, \emph{EUSIPCO}, Rome, Italy, September, 2018
\item Marco Cox and Bert de Vries, Robust Expectation Propagation in Factor Graphs Involving Both Continuous and Binary Variables, \emph{EUropean SIgnal Processing COnference (EUSIPCO-2018)}, Rome, Italy 2018
\item Thijs van de Laar, Marco Cox, Bert de Vries
, ForneyLab.jl: a Julia Toolbox for Factor Graph-based Probabilistic Programming, \emph{JuliaCon 2018}, \href{https://youtu.be/RS4hJ4oBr9c}{youtube}, London (UK), August 2018
\item
Ivan Bocharov, Bert de Vries and Tjalling Tjalkens, K-shot Learning of
Acoustic Context, NIPS-2017 workshop on
\href{http://media.aau.dk/smc/ml4audio/}{machine learning
for audio signal processing}, Long Beach (CA), Dec 2017
\item
Marco Cox and Bert de Vries, A parametric approach to Bayesian
optimization with pairwise comparisons.
\href{http://bayesopt.com}{NIPS-2017 workshop on Bayesian
Optimization}, Long Beach (CA), Dec 2017
\item
Thijs van de Laar, Marco Cox, Anouk van Diepen and Bert de Vries,
Variational Stabilized Linear Forgetting in State-Space Models,
\emph{EUSIPCO-2017}, KOS Island (Greece), Aug.2017
\item
Marco Cox and Bert de Vries, A Gaussian Process Mixture Prior for
Hearing Loss Modeling, {\em Machine Learning Conference of the
Benelux} (Benelearn), Eindhoven, 2017
\item
Anouk van Diepen et al., An In-situ Trainable Gesture Classifier,
{\em Machine Learning Conference of the Benelux} (Benelearn),
Eindhoven, 2017
\item
Quan (Eric) Nguyen et al., Probabilistic Inference-based Reinforcement
Learning, {\em Machine Learning Conference of the Benelux}
(Benelearn), Eindhoven, 2017
\item
Thijs van de Laar and Bert de Vries, A Probabilistic Modeling Approach
to Hearing Loss Compensation, {\em Machine Learning Conference of the
Benelux} (Benelearn), Eindhoven, 2017
\item
Mojtaba Farmani and Bert de Vries, A Probabilistic Approach To Hearing
Loss Compensation, {\em IEEE Machine Learning for Signal Processing
workshop} (MLSP), Reims, FR, Sep 2014
\item
Bert de Vries et al., Efficient Hearing Aid Spectral Signal Processing
with an Asynchronous Warped Filterbank, {\em Int'l Hearing Aid
Research Conference} (IHCON), Lake Tahoe, CA, August 2014
\item
Bert de Vries and Andrew Dittberner, Is Hearing Aid Signal Processing
Ready for Machine Learning? {\em Int'l Symposium on Auditory and
Audiological Research}, Nyborg, DK, Aug.~2013
\item
Ungureanu C. et al., A Bayesian Network for Detection of Seizures,
{\em 1st Jan Beneken Conference on Modeling and Simulation of Human
Physiology}, Eindhoven, NL, 2013
\item
Petkov P. et al., Discrete Choice Models for Non-Intrusive Quality
Assessment, {\em Interspeech 2011}, Florence, Italy, 2011
\item
Rob de Vries et al., A software suite for automatic beamforming
calibration, {\em Int'l Hearing Aid Research Conference}, Lake Tahoe,
CA, August 2010
\item
S.I. Mossavat et al., A Bayesian hierarchical mixture of experts
approach to estimate speech quality, {\em QoMEX 2010}, Trondheim,
Norway, June 2010
\item
Jos Leenen and Bert de Vries, Current DSP and Machine Learning Trends
in the Hearing Aids Industry, {\em IEEE Benelux Signal Processing
Symposium: Signal Processing for Digital Hearing Aids}, Delft, NL,
April 2010
\item
Xueru Zhang et al., Bayesian periodogram smoothing for speech
enhancement, {\em European Symposium on Artificial Neural Networks
(ESANN-09)}, Bruges, April 2009
\item
Adriana Birlutiu et al., Towards hearing aid personalization:
preference elicitation from audiological data, {\em Scientific
ICT-Research Event Netherlands (SIREN)}, Amsterdam, Sep.~2008
\item
Tjeerd Dijkstra et al., HearClip: an Application of Bayesian Machine
Learning to Personalization of Hearing Aids, Presentation at
{\em Dutch Society for Audiology Meeting}, Sep.~2008
\item
Bert de Vries, Fast Model-Based Fitting through Active Data Selection,
{\em Int'l Hearing Aid Research Conference}, Lake Tahoe, CA, August
2008
\item
Rolph Houben et al., Construction of a virtual subject response
database to reduce subject testing, {\em Int'l Hearing Aid Research
Conference}, Lake Tahoe, CA, August 2008
\item
Bert de Vries et al., The Complexity of Hearing Aid Fitting, presented
at {\em International Symposium on Auditory and Audiological Research
2007}, Helsingor, Denmark, August 2007
\item
Jos Leenen et al., Learning Volume Control for Hearing Aids, presented
at {\em International Symposium on Auditory and Audiological Research
2007}, Helsingor, Denmark, August 2007
\item
Alexander Ypma et al., Bayesian Feature Selection for Hearing Aid
Personalization, {\em MLSP-07}, Thessaloniki, Greece, 2007
\item
Adriana Birlutiu et al., Personalization of Hearing Aids through
Bayesian Preference Elicitation, {\em NIPS workshop on User Adaptive
Systems}, Whistler, BC, Canada, December 2006
\item
Bert de Vries et al., Bayesian Machine Learning for Personalization of
Hearing Aid Algorithms, {\em Int'l Hearing Aid Research Conference},
Lake Tahoe, CA, August 2006
\item
Alexander Ypma, Bert de Vries and Job Geurts, Robust Volume Control
Personalization from On-line Preference Feedback, {\em IEEE Int.
Workshop on Machine Learning for Signal Processing}, Maynooth,
Ireland, 2006
\item
Bert de Vries, Tom M. Heskes and Tjeerd M. H. Dijkstra, Bayesian
Incremental Utility Elicitation with Application to Hearing Aids
Personalization, {\em Valencia/ISBA 8th World Meeting on Bayesian
Statistics}, Benidorm, Spain, June 2006
\item
Tjeerd M. H. Dijkstra et al., A Bayesian decision-theoretic framework
for psychophysics, {\em Valencia/ISBA 8th World Meeting on Bayesian
Statistics}, Benidorm, Spain, June 2006
\item
Alexander Ypma, Bert de Vries and Job Geurts, A learning volume
control that is robust to user inconsistency, {\em The second annual
IEEE BENELUX/DSP Valley Signal Processing Symposium}, Antwerp, March
2006
\item
Paul Aelen et al., Electrohysterographic Estimation of the
Intra-Uterine Pressure, {\em The second annual IEEE BENELUX/DSP Valley
Signal Processing Symposium}, Antwerp, March 2006
\item
Tom Heskes and Bert de Vries, Incremental Utility Elicitation for
Adaptive Personalization, {\em The 17th Belgian-Dutch Conference on
Artificial Intelligence}, Brussels, Belgium, October 2005
\item
Bert de Vries and Rob de Vries, An Integrated Approach to Hearing Aid
Algorithm Design, {\em Int'l Hearing Aid Research Conference}, Lake
Tahoe, CA, August 2004
\item
Harald Pobloth et al., Speech Coding for Wireless Communication in the
Hearing Aid Environment, {\em Int'l Hearing Aid Research Conference},
Lake Tahoe, CA, August 2004
\item
Bert de Vries and Rob de Vries,An Integrated Approach to Hearing Aid
Algorithm Design for Enhancement of Audibilit y, Intelligibility and
Comfort, {\em IEEE Benelux Signal Processing Symposium}, Hilvarenbeek,
Netherlands, April 2004
\item
Rob de Vries and Bert de Vries, Toward SNR-Loss Restoration in Digital
Hearing Aids, {\em ICASSP 2002}, Orlando, FL, May 2002
\item
Bert de Vries, Jos Leenen, A Low Power Digital AGC Circuit for Dynamic
Range Control of an A/D Converter, {\em International Hearing Aids
Research (IHCON) Conference 2000}, Lake Tahoe (CA), August 2000
\item
Lucas Parra, Clay Spence and Bert de Vries, Convolutive Blind Source
Separation based on Multiple Decorrelation, {\em IEEE workshop on
Neural Networks for Signal Processing VIII}, pp.23-32, Cambridge, UK,
1998 {\bf {[}93{]}}
\item
Bert de Vries, Blind Signal Processing for Hearing Aids, {\em NIH
Hearing Aids Improvement Conference}, Bethesda, MA, May 1997
\item
Bert de Vries, Adaptive Gamma Filters for Miniature Hearing Aids,
{\em NIH Hearing Aids Improvement Conference}, Bethesda, MA, May 1997
\item
Bert de Vries, Adaptive rank filtering based on error minimization,
{\em ICASSP-97}, Munich, April 1997
\item
Lucas Parra, Clay Spence, Bert De Vries, Convolutive Source Separation
and Signal Modeling with Maximum Likelihood, {\em International
Symposium on Intelligent Systems} (ISIS'97), Regio Calabria, Italy,
1997
\item
Q. Lin et al., Robust distant-talking speech recognition,
{\em ICASSP-96}, Atlanta,GA, May 1996
\item
Bert de Vries et al., Neural network speech enhancement for noise
robust speech recognition, {\em International Workshop on Applications
of Neural Networks to Telecommunications}, Sweden, May 1995
\item
Lin et al., Experiments on distant-talking speech recognition,
{\em ARPA Workshop on Spoken Language Technology}, Austin, TX, January
1995
\item
Qiguang Lin et al., System of microphone arrays and neural networks
for robust speech recognition in multimedia environments, Proceedings
{\em International Conference on Spoken Language Processing},
Yokohama, Japan, September 1994
\item
Bert de Vries, Gradient-based adaptation of network structure,
{\em International Conference on Artificial Neural Networks 94},
Sorrento, Italy, May 94
\item
Che et al., Microphone Arrays and Neural Networks for Robust Speech
Recognition, {\em ARPA Workshop on Human Language Technology},
Princeton, NJ, March 1994
\item
Bert de Vries et al., An application of Gamma delay lines to
BDG-phoneme classification, {\em Government Microcircuit
Applications Conference proceedings}, New Orleans, LA, November 1993
\item
Bert de Vries, Time-varying neural networks for large tasks,
{\em International Conference on Artificial Neural Networks
proceedings}, Amsterdam, the Netherlands, September 13-16, 1993
\item
J.C. Principe et al., Backpropagation through time with fixed memory
size requirements, {\em Proceedings of Workshop on Neural Networks for
Signal Processing}, Linthicum Heights, MD, USA, Sep.~1993
\item
Bert de Vries et al.,Learning with target trajectory constraints for
sequence classification tasks, {\em ICASSP-93}, Minneapolis, MN, April
1993
\item
Bert de Vries et al.,Short Term Memory Structures for Dynamic Neural
Networks, {\em Asilomar-92} Conference proceedings, Pacific Grove, CA,
1992
\item
T. Oliveira a Silva et al., Generalized feedforward filters with
complex poles, {\em Proceedings of the 1992 IEEE workshop on Neural
Networks for Signal Processing}, Copenhagen, Denmark, 1992
\item
Jyh-Ming Kuo, Jose Principe and Bert de Vries, Prediction of chaotic
time series using recurrent networks, {\em Proc. of the 1992 IEEE
workshop on Neural Networks for Signal Processing}, 1992
\item
Jose Principe, Bert de Vries and Pedro G. de Oliveira, Generalized
feedforward structures: a new class of adaptive filters,
{\em ICASSP-92}, San Francisco, vol.~IV, pp.~245-248, 1992
\item
T. Oliveira e Silva, P. Guedes de Oliveira, J. C. Principe and B. de
Vries, A Complex Pole Extension to the Gamma Filter, {\em The INESC
Journal of Research and Development}, vol.~3, no. 1, pp.~35-41,
Jan./Jun.~1992
\item
Bert de Vries et al., Adaline with adaptive recursive memory,
{\em Proceedings IEEE workshop on signal processing}, Princeton, NJ,
1991
\item
Principe et al., Modeling applications with the focused gamma net,
{\em NIPS-4 proceedings}, Denver, CO, 1992
\item
Bert de Vries et al., Some practical issues concerning the gamma
neural net, {\em Proceedings IJCNN-91}, Seattle, WA, 1991
\item
Bert de Vries and Jose Principe, A theory for neural nets with time
delays, {\em NIPS-3 Proceedings}, Denver, 1991 {\bf {[}63{]}}
\item
Bert de Vries et al., Neural net models for temporal processing,
{\em Proceedings nineth southern biom. eng. conference}, Miami, FL,
1991
\item
Bert de Vries et al., A new neural net model for temporal processing,
{\em 12th ann. int. conf. IEEE on the eng. in medicine and biology
society}, Philadelphia, PA, 1990
\item
Bert de Vries et al., Artificial neural networks as a computational
paradigm for detection of anaesthetic complications, {\em Computers in
Anesthesia 10}, New Orleans, LA, 1989
\item
Bert de Vries et al., Distribution of anesthesia related occurrences
during surgical operations, {\em Anesthesiology review} 14 (6), 1987
\end{etaremune}
\end{resume}
\end{document}