Research Output per year
Organization profile
Introduction / mission
We are an academic research team within the Signal Processing Systems group at Eindhoven University of Technology. Our main research interest focusses on developing autonomous agents that learn through interacting with their environment and using these agents to automate the development of new signal processing systems. Typical application areas include (medical) device personalization, automated vehicle control and robotics.
Our research is strongly inspired by developments in Bayesian machine learning and Computational Neurosciences. An important research focus area is our quest to develop (machine learning) technology to support situated personalization of audio processing systems such as hearing aids.
Highlighted phrase
Developing autonomous agents that learn from their environment.
Fingerprint Dive into the research topics where Bayesian Intelligent Autonomous Systems Lab is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.
Hearing aids
Engineering & Materials Science
Signal processing
Engineering & Materials Science
Audition
Engineering & Materials Science
Acoustic waves
Engineering & Materials Science
Feedback
Engineering & Materials Science
Message passing
Engineering & Materials Science
Speech enhancement
Engineering & Materials Science
Processing
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Profiles
Semih Akbayrak, MSc
- Department of Electrical Engineering, Signal Processing Systems - Doctoral Candidate
- Department of Electrical Engineering, Bayesian Intelligent Autonomous Systems Lab
Person: Prom. : doctoral candidate (PhD), TOIO : PDEng-trainee
Ivan Bocharov, MSc
- Department of Electrical Engineering, Signal Processing Systems - Doctoral Candidate, University Researcher
- Department of Electrical Engineering, Bayesian Intelligent Autonomous Systems Lab
Person: Prom. : doctoral candidate (PhD), OWP : University Teacher / Researcher
Marco G.H. Cox
- Department of Electrical Engineering, Signal Processing Systems - Former Doctoral Candidate
- Department of Electrical Engineering, Bayesian Intelligent Autonomous Systems Lab
Person: Prom. : doctoral candidate (PhD), Unknown
Research Output 1999 2019
A factor graph approach to automated design of Bayesian signal processing algorithms
Cox, M., van de Laar, T. & de Vries, B., 1 Jan 2019, In : International Journal of Approximate Reasoning. 104, p. 185-204 20 p.Research output: Contribution to journal › Article › Academic › peer-review
Open Access
File
Factor Graph
Signal Processing
Signal processing
Message passing
Message Passing
Automated design of Bayesian signal processing algorithms
van de Laar, T., 12 Jun 2019, Eindhoven: Technische Universiteit Eindhoven. 183 p.Research output: Thesis › Phd Thesis 1 (Research TU/e / Graduation TU/e) › Academic
Open Access
File
Signal processing
Performance of intelligent lighting sensor networks : analysis, modeling and distributed architectures
Papatsimpa, C., 27 May 2019, Eindhoven: Technische Universiteit Eindhoven. 141 p.Research output: Thesis › Phd Thesis 1 (Research TU/e / Graduation TU/e) › Academic
Open Access
File
Activities 2017 2017
- 2 Conference
25th European Signal Processing Conference (EUSIPCO 2017)
Anouk van Diepen (Participant)17 Aug 2017 → 2 Sep 2017
Activity: Participating in or organising an event types › Conference › Scientific
Annual machine learning conference of the Benelux (Benelearn 2017)
Anouk van Diepen (Participant)10 Jun 2017
Activity: Participating in or organising an event types › Conference › Scientific
Student theses
A factor graph approach to Gaussian process preference learning
Author: Schoonderbeek, M., 31 Oct 2014Supervisor: de Vries, A. (Supervisor 1)
Student thesis: Master
A Probabilistic Modeling Approach to One-Shot Gesture Recognition
Author: van Diepen, A., 31 May 2017Supervisor: Cox, M. (Supervisor 1) & de Vries, B. (Supervisor 2)
Student thesis: Master
File
Machine learning framework for Bayesian signal processing
Author: Bagautdinov, T., 31 Aug 2013Supervisor: de Vries, A. (Supervisor 1) & Pechenizkiy, M. (Supervisor 2)
Student thesis: Master
File