Open positions available

Developing autonomous agents that learn from their environment

Using these agents to develop novel signal processing systems

ForneyLab is a novel Julia package that allows the user to specify a probabilistic model as an FFG and pose inference problems on this FFG. ForneyLab is especially potent when applied to time-series data, where it attains comparable performance to Stan and Edward in significantly less computation time.

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We develop a fully probabilistic approach to pure-tone audiometry. By assuming a Gaussian process based response model for test tones, the hearing threshold estimation problem becomes one of Bayesian inference. This allows the use of information-theoretic criteria to select optimal test tones.

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Gesture recognition enables a natural extension of the way we currently interact with devices. Commercially available gesture recognition systems are usually pre-trained. We propose a method that allows users to define their own gestures using only a few training examples.

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The primary mission of the BIASlab team is to develop in-situ trainable Bayesian Intelligent Agents for applications to wearable technology.

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How do you solve a problem that is only vaguely described? We describe here an engineering approach that guides our research on solving vaguely defined problems such as hearing impairment.

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Bert de Vries

Professor, TU Eindhoven

Tjalling Tjalkens

Associate Professor, TU Eindhoven

Wouter Kouw

Postdoctoral researcher, TU Eindhoven

Thijs van de Laar

PhD candidate, TU Eindhoven

Marco Cox

PhD candidate, TU Eindhoven

Anouk van Diepen

PhD candidate, TU Eindhoven

Ismail Senoz

PhD candidate, TU Eindhoven

Ivan Bocharov

PhD candidate, TU Eindhoven

Magnus T√łnder Koudahl

PhD Candidate, TU Eindhoven

Semih Akbayrak

PhD candidate, TU Eindhoven

Albert Podusenko

PhD candidate, TU Eindhoven

Joris Kraak

Senior Software Engineer, GN Hearing

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This position is aimed at developing intelligent autonomous agents that learn from interacting with their environmnent.

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In this project you are challenged to develop a software demonstrator for an intelligent agent that learns how to read text.

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We gratefully acknowledge financial support from our sponsors:

GN Resound