Bayesian Intelligent Autonomous Systems Lab

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.

Research Output 1999 2019

2 Citations (Scopus)

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 journalArticleAcademicpeer-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: ThesisPhd 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: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)Academic

Open Access
File

Activities 2017 2017

25th European Signal Processing Conference (EUSIPCO 2017)

Anouk van Diepen (Participant)
17 Aug 20172 Sep 2017

Activity: Participating in or organising an event typesConferenceScientific

Annual machine learning conference of the Benelux (Benelearn 2017)

Anouk van Diepen (Participant)
10 Jun 2017

Activity: Participating in or organising an event typesConferenceScientific

Student theses

A factor graph approach to Gaussian process preference learning

Author: Schoonderbeek, M., 31 Oct 2014

Supervisor: de Vries, A. (Supervisor 1)

Student thesis: Master

A Probabilistic Modeling Approach to One-Shot Gesture Recognition

Author: van Diepen, A., 31 May 2017

Supervisor: 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 2013

Supervisor: de Vries, A. (Supervisor 1) & Pechenizkiy, M. (Supervisor 2)

Student thesis: Master

File