AI Colloquium

The Bernoulli Institute AI Colloquium is a regular meeting where faculty and students  can hear and discuss the current research related to the institute's three research themes (Computing and Cognition; Geometry and its Applications; Systems, Data and Society) from inside and outside the University of Groningen. 

Colloquia are scheduled monthly during the teaching blocks, with the exception of December, preferentially on Thursday afternoon. Meetings at the end of the day are followed by the PoCoBo - a post-colloquium borrel.

For external colloquia, there is a limited opportunity to have dinner with the speaker in the evening. If you are interested in this, please contact Harmen or Stephen a few days before the colloquium.

GroningenML MeetUp event

4 April 2024 - 17:30 - 20:30

Linneausborg, room 5173.0055

17:30 - Walk-in & Pizza


18:15 - Welcome by GroningenML, RuG, AI Hub Noord


18:30 - Reducing fuel consumption in platooning systems through reinforcement learning

Rafael Fernandes Cunha


Abstract: Adaptive Cruise Control (ACC) in platooning systems, vital for economic and environmental efficiency in transport, uses a key time gap parameter for vehicle spacing. To optimize fuel consumption, our study employs Reinforcement Learning, specifically the proximal policy optimization (PPO) algorithm, to dynamically adjust this time gap in response to traffic conditions. Simulations demonstrate PPO's superiority in enhancing fuel efficiency over static and threshold-based ACC controls.


19:15 - Uncertainty in Machine Learning

Prof. Matias Valdenegro


Abstract: What if we train a model to classify dogs and cats, but it is later tested with an image of a human? Generally the model will output either dog or cat, and has no ability to signal that the image has no class that it can recognize.

This is because classical neural networks do not contain ways to estimate their own uncertainty (so called epistemic uncertainty), and this has practical consequences for the use of these models, like safety when cooperating with humans, autonomous systems like robots, and computer vision systems. A possible solution is the bayesian neural network.

In this talk I will cover the basic concepts of bayesian neural networks, and how they can help us to produce safer models, including explainable AI and computer vision.


20:00 - Drinks


20:30 - Closing

Upcoming speakers