Bert de Vries
I believe that development of signal processing systems will in the future be largely automated by autonomously operating agents that learn purposeful (signal processing) behavior from situated environmental interactions.
Bert de Vries is Part-time Professor in the Signal Processing Systems group. His research focuses on the development of intelligent autonomous agents that learn from in-situ interactions with their environment. And on using these agents to automate the development of novel signal processing algorithms, see biaslab.org. Our research draws inspiration from diverse fields including computational neuroscience, Bayesian machine learning and signal processing systems. A current major application area concerns personalization of medical signal processing systems such as hearing aid algorithms. In the past, De Vries contributed to research projects over a wide range of signal and image processing topics, such as word spotting, financial market prediction and breast cancer detection from mammograms.
Bert de Vries received M.Sc. (1986) and Ph.D. (1991) degrees in Electrical Engineering from Eindhoven University of Technology (TU/e) and the University of Florida, respectively. From 1992 to 1999, he worked as a research scientist at Sarnoff Research Center in Princeton (NJ, USA). Since 1999, he has been employed in the hearing aids industry, both in engineering and managerial positions. De Vries was appointed part-time professor in the Signal Processing Systems Group at TU/e in 2012.
A parametric approach to Bayesian optimization with pairwise comparisonsNIPS Workshop on Bayesian Optimization (BayesOpt 2017), December 9, 2017, Long Beach, USA (2017)
A probabilistic modeling approach to hearing loss compensationIEEE Poster Contest 2017 (2017)
Variational stabilized linear forgetting in state-space models25th European Signal Processing Conference (EUSIPCO 2017) (2017)
A factor graph description of deep temporal active inferenceFrontiers in Computational Neuroscience (2017)
A Gaussian process mixture prior for hearing loss modelingAnnual machine learning conference of the Benelux (Benelearn2017), 9-10 June 2017, Eindhoven 2017 (2017)
- Adaptive information processing
- Ik ben onbezoldigd deeltijdhoogleraar bij TU/e. GN Hearing is mijn baan., GN Hearing