INTRODUCTION

This course gives students insights into the recent developments in a fast-growing research line: the integration of techniques from machine learning (ML) and optimisation (OPT).  The lectures cover different aspects of the integration of ML and optimisation. Example topics include:

• Machine learning, including deep learning and reinforcement learning, to solve combinatorial optimisation problems; black-box optimisation; neural combinatorial optimisation; and handling uncertainties of prediction models for decision-making
• Using optimisation algorithms for the development of transparent ML models, such as learning optimal decision trees
• Computing explanations for ML model via techniques developed for optimisation or constraint reasoning systems

Lectures are complemented by lab sessions with hands-on exercises during the course.
The two-day course will be held in person.  To participate, students should have basic knowledge on machine learning and some basic knowledge on optimisation (i.e., mathematical programming, or (meta-) heuristics).

DATES:

1 & 2 October 2026

LOCATION:

The course will take place at hotel Landgoed Huize Bergen in Vught, near Den Bosch. Please note that overnight accommodation is not provided for this course. Should you wish to stay at Landgoed Huize Bergen, you will be able to book a room at a discount by contacting them on +31 73 658 04 00 or receptie@huizebergen.nl and informing them you are a SIKS PhD student.

SCIENTIFIC DIRECTORS:

Dr Neil Yorke-Smith, TU Delft
Dr Yingqian Zhang, TU/e

REGISTRATION

Registration for this course is now open. If you have any questions, please email Renée.