Symposium: Uncertainty in Research | Engineers of Tomorrow

When?

2026

9:00

This event is already over.

Where?

University of Antwerp, Middelheim Campus

Price

125 euros per person, including coffee breaks, lunch, and networking reception
Free for doctoral students and postdoctoral researchers

Our cancellation policy applies.

Just like last year, we’re organizing an inspiring event that brings together people from a wide range of fields and backgrounds.

This year, we’re giving the floor to industry. Throughout the day, we’ll be hosting talks on the role of uncertainty in research and industrial applications, as well as on the various ways in which uncertainty can be understood, modeled, and leveraged. Topics covered will include simulation, Bayesian inference, machine learning, optimization, reinforcement learning, and robust system design. The lectures demonstrate that uncertainty is not only a challenge to be mitigated, but can also be a source of insight for developing more reliable, more interpretable, and more effective solutions to real-world problems.

The event is aimed at researchers and professionals from the business world, as well as PhD students and postdoctoral researchers from all applied and exact sciences. At the same time , we warmly welcome participants from other disciplines who are interested in uncertainty, machine learning, and practical applications. The lectures will be interspersed with poster sessions, during which we invite all participants to present their work—either from the perspective of a challenge they are facing or as a machine learning solution waiting to be tested on a real-world problem.

We’ll wrap up the day with a networking reception, where participants will have the opportunity to continue their conversations and connect with other attendees in an informal setting.‍

Program

Kurt Sys, M.Eng. - Software Architect, QA Engineer, Tech Lead at Vintecc
- Exploiting Uncertainty Outside the Model: Industrial ML as a Hyperliminal Systems Problem
Dr. Pieter Muyshondt - Senior Engineer, Simulation and Analysis, Cochlear
- Understanding the Variability of Middle-Ear Motion Through Simulation
Prof. Dr. Bram Vervisch - Ghent University, ORBITS
- Beyond Predictive Maintenance: Prioritizing the "Why" Over the "When" in Electric Drivetrains
Gabriel Diaz-Aylwin, M.A. - University of Lancaster, United Kingdom Atomic Energy Authority
- Bayesian Optimization for Fusion Reactor Design
Dr. Dmitry Bagaev - TU/e, former CTO of Lazy Dynamics
- Keep Calm and Trust AI
Dr. Peter Verleijsdonck - TU/e, BiasLab
- Improving Energy Management Systems to Address Congestion Challenges through Deep Reinforcement Learning and Bayesian Inference

Target Audience

As an expert in your field, you know exactly which problems are worth solving.

You know what you need to solve, but not necessarily the best way to do it...
Are you stuck on a problem in your research?
Do you feel like you're just repeating the same steps over and over?
Do you feel like there's probably a smarter way to do things?

As an expert in your field, you work with multivariate distributions on a daily basis.

You just know how to come up with a solution efficiently.
Do you have an amazing machine learning method that has only been demonstrated on test data so far?
Do you need a real-world problem to test your innovative solutions?

If you identify with any of these target groups, be sure to come to this event—you’ll go home inspired and with new contacts!

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