Kevin Mets academic interim staff postdoc - tenure track asst. professor - guest professor

Research Kevin Mets

Research team

Expertise

The development and application of new artificial intelligence techniques. More specifically, I focus on deep learning (graph neural networks) and (multi-agent) deep reinforcement learning, with an emphasis on continual learning.

A-budget IMEC 2026. 01/01/2026 - 31/12/2026

Abstract

This project is part of the IMEC Frame Agreement and is being given as structural investment for fundamental research based on yearly set KPIs from the group to IMEC. This A-budget is defined within the IMEC Way of Working and part of the frame agreement of the University of Antwerp and IMEC.

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  • Research Project

Predicting Actions and Detecting Real-time Errors (PADRE). 01/11/2025 - 31/10/2027

Abstract

The rapid evolution of technology is reshaping the job market, creating an urgent need for reskilling and upskilling across sectors. Traditional training methods, often reliant on human trainers, fall short in technical domains where precise manual actions are essential. Companies report that experienced workers spend disproportionate time training novices, diverting them from their operational tasks. This issue is particularly acute in high-risk industries such as industrial chemistry, semiconductor production, pharmaceuticals, and advanced medical fields, where even small mistakes can have severe financial, safety, or life-threatening consequences. While educational technologies such as augmented and virtual reality training, AI-driven feedback, and cognitive state monitoring offer promising advances, current solutions largely remain limited to procedural knowledge. They fail to capture nuanced manual actions or assess cognitive readiness and skill acquisition over time. No reliable systems exist to predict human error in real-world, high-stakes conditions. To address these gaps, the PADRE project proposes a sensor- and AI-driven framework for real-time monitoring, quality evaluation, and error prediction during complex manual and cognitive tasks. Beyond specific use cases, PADRE aims to develop foundation models applicable across diverse training and on-the-job support contexts, enhancing safety, efficiency, and workforce readiness in critical industries.

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  • Research Project

Airline crew scheduling with multi-agent reinforcement learning. 01/10/2025 - 30/09/2029

Abstract

The goal of this project is to accelerate and make the personnel planning process in the aviation sector more cost-efficient by, on the one hand, improving existing planning algorithms with ML methods, and on the other hand, developing a fully autonomous RL-driven planning solution using Reinforcement Learning (RL) and Multi-Agent Reinforcement Learning (MARL), leveraging the latest advancements in neural architectures.

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  • Research Project

IMEC-Embedded AI Systems and Applications (ANT). 01/02/2025 - 31/01/2029

Abstract

Embedded Artificial Intelligence (AI) has emerged as a transformative technology with immense potential to revolutionise various domains, spanning from robotics and healthcare to environmental monitoring and the Internet of Things. This Doctoral Network (DN) project ANT aims to train a network of 15 excellent Doctoral Candidates (DCs) by addressing the fundamental challenges of Embedded AI and accelerating the development of Embedded AI systems and applications through an innovative and interdisciplinary research and training program. ANT consists of four interconnected Work Packages (WPs) that encompass different aspects of Embedded AI. WP1 tackles the challenges in designing low-footprint standalone Embedded AI models under resource constraints and with diverse contexts and evolving environments. WP2 goes beyond standalone Embedded AI and designs innovative distributed and scalable learning solutions for heterogeneous Embedded AI networks under energy and bandwidth constraints. WP3 enhances the trustworthiness of Embedded AI with explainability, robustness, security, and privacy. ANT concludes in WP4 with a concerted effort to transfer fundamental research contributions to industry-relevant applications in autonomous robotics, underwater IoT, mobile healthcare, and smart farming, boosting Europe's position in the global AI market both from a talent and a technological perspective. These interdisciplinary and inter-domain research training, along with the comprehensive soft-skills training (spanning from presentation skills to intellectual property, marketing, and economics, etc.) will make ANT's 15 DCs highly employable in various industries, academia, or public government bodies, and will position the EU at the forefront of the emerging revolution of Embedded AI on Things.

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  • Research Project

Flanders Artificial Intelligence Research program (FAIR) – second cycle. 01/01/2024 - 31/12/2028

Abstract

The Flanders AI Research Program is a strategic basic research program with a consortium of eleven partners: the five Flemish universities (KU Leuven, University of Ghent, University of Antwerp, University of Hasselt, Vrije Universiteit Brussel) and six research centers (imec, Flanders Make, VIB, VITO, Sirris and ILVO). The program brings together 300+ researchers on new AI methods that can be used in innovative applications in health, industry, planet&energy and society. This way, the program contributes to a successful adoption of AI in Flanders. The ambition is for Flanders to occupy a strong international position in the field of strategic basic research in AI, and this within a strong and sustainable Flemish ecosystem. Five focus research themes have been selected: responsible AI, human-centered AI, sustainable AI (energy-efficient and high-performance), productive and data-efficient AI (systems that require little data, which perform by combining data with domain knowledge and experience of experts) and resilient and high-performant AI (robust against changes in the environment). The description of the work packages and their research tasks defines the aspects within these themes that will be investigated in the program. The AI solutions are demonstrated in real-life use cases. These results not only demonstrate the effectiveness, but also inspire companies for adoption and researchers for further research. The Flanders AI Research Program is part of the Flanders AI Policy Plan. More info: www.flandersairesearch.be

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  • Research Project

Goal-Oriented Process Control using Constraint-Guided Model-Based Reinforcement Learning. 01/11/2023 - 31/10/2027

Abstract

Due to its strong economic impact, the field of process control has received much research interest over the years. Whilst traditional control methods have been used in the industry for decades, the application of Machine Learning (ML) has not been properly assessed. An interesting novel field withing ML is Reinforcement Learning (RL), which has repeatedly improved the state-of-the-art (SOTA) in the control of complex systems. Consequently, applying this technique to industrial process control has the potential of strongly improving process efficiency. On the one hand, this leads to reduced cost, resource usage and energy requirements for some of the biggest industries worldwide. On the other hand, this opens a new avenue for collaboration between academics and industry. This project aims to research techniques that are centered around applying RL to industrial process control by developing goal-oriented agents that effectively capture the expectations of the user. (1) An agent with an accurate latent world model will be developed with SOTA performance and strong reasoning capabilities. (2) This agent is extended with a reverse imagination model to reconstruct physical states from latent states. State constraints are applied to these physical states based on expert knowledge to create an intuitive framework for guiding the agent. (3) The agent is then transferred from simulation to reality using offline data to align the internal world model with the real-world environment

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  • Research Project

IDLab - Internet and Data Lab 01/01/2021 - 31/12/2026

Abstract

The IOF consortium IDLab is composed of academic supervisors at the IDLab Research Group, a ¶¶Òõ¶ÌÊÓƵ research group with members from the Faculty of Science and the Faculty of Applied Engineering. IDLab develops innovative digital solutions in the area of two main research lines: (1) Internet technologies, focusing on wireless networking and Internet of Things (IoT), and (2) Data science, focussing on distributed intelligence and Artificial Intelligence (AI). The mission of the IDLab consortium is to be the number one research and innovation partner in Flanders and leading partner worldwide, in the above research areas, especially applied in a city and its metropolitan surroundings (industry, ports & roads). To realize its mission, IDLab looks at integrated solutions from an application and technology perspective. From an application point of view, we explicitly provide solutions for all stakeholders in metropolitan areas aiming to cross-fertilize these applications. From a technological point of view, our research includes hardware prototyping, connectivity and AI, enabling us to provide a complete integrated solution to our industrial partners from sensor to software. Over the past years, IDLab has been connecting the city and its surroundings with sensors and actuators. It is time to (1) reliably and efficiently connect the data in an integrated way to (2) turn them into knowledgeable insights and intelligent actions. This perfectly matches with our two main research lines that we want to extensively valorise the upcoming years. The IDLab consortium has a unique position in the Flemish eco-system to realize this mission as it is strategically placed across different research and innovation stakeholders: (1) IDLab is a research group embedded in the Strategic Research Centre imec, a leading research institute in the domain of nano-electronics, and more recently through groups such as IDLab, in the domain of digital technology. (2) IDLab has a strategic link with IDLab Ghent, a research group at Ghent University. While each group has its own research activities, we define a common strategy and for the Flemish ecosystem, we are perceived as the leading partner in the research we are performing. (3) IDLab is the co-founder of The Beacon, an Antwerp-based eco-system on innovation where start-ups, scale ups, etc. that work on IoT and AI solutions for the city, logistics, mobility and industry 4.0 come together. (4) Within the valorisation at ¶¶Òõ¶ÌÊÓƵ, IDLab contributes to the valorisation within the domain 'Metropolitanism, Smart City and Mobility'. To realize our valorisation targets, IDLab will define four valorisation programs: VP1: Emerging technologies for next-generation IoT; VP2: Human-like artificial Intelligence; VP3: Learning at the edge; VP4: Deterministic communication networks. Each of these valorisation programs is led by one of the (co-)promoters of the IDLab consortium, and every program is composed of two or three innovation lines. This way, the IDLab research will be translated into a clear program offer towards our (industrial) partners, allowing us to build a tailored offer. Each valorisation program will contribute to the different IOF objectives, but in a differentiated manner. Based on our current experience, some valorisation programs are focusing more on local partners, while others are mainly targeting international and EU funded research projects.

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  • Research Project