Newsletter April 2024

Message from the DISC Office

Dear all,

In this newsletter, we are happy to invite you to participate in our DISC Summer School on “Learning, sensing and control with application to agriculture”, which will be jointly organized with the graduate school for Production Ecology & Resource Conservation (PE&RC) of University of Wageningen.

Fantastic speakers are lined up to give courses for our researchers. I would like to invite all of you to take a look at the program and enroll yourself to the summer school.

With best regards,



DISC-PE&RC Summer School Learning, sensing and control with application to agriculture

This year we organise a Summer School together with PE&RC from Wageningen .  The Summer School takes place from Sunday June 16, 2024 –  Friday June 21, 2024 in Parkhotel ‘de Bosrand’, Ede, the Netherlands. It starts on Sunday at 16:00.


During the past decades, precision technology, robotics and machine intelligence have become increasingly important for farming systems like greenhouses, open field, and animal husbandry. Systems and control methods play a pivotal role in this. Successful and sustainable automation of farm management relies on accurate and reliable monitoring, fault detection, prediction and control.

However, these tasks are generally challenging. A key challenge is providing precise and robust and reliable operation under great variability between and within systems, for example in weather patterns, crop response, soil properties, crop properties, occlusion by leaves, and disease occurrence. Another challenge is formed by great system complexity, comprising physics and biology, large numbers of processes and processes that take place on vastly different time scales. Yet another challenge is to monitor processes for which the variables of interest cannot be measured directly or accurately, such as food quality aspects.

A key opportunity is formed by the combination of control methods and learning methods that employ real-time data streams. Particular areas that have seen substantial development over the past decades are:

  • Control systems that anticipate future events such as weather and market prices
  • Controllers that deal with complex networked systems
  • Controllers that learn from live data streams • Controllers that deal with stochastic uncertainty
  • Robotic systems that navigate and apply input autonomously
  • Automated systems that monitor and control food quality before and after harvest

This Summer School presents the state-of-the-art methods for the above mentioned methods for various farming applications such as irrigation scheduling, food processing, greenhouse management, and plant harvesting and inspection. The course will consist of lectures from worldwide experts, and hands-on practicals with real life examples.

Course set-up
  1. Course Kick-off : The course starts off Sunday afternoon with an introduction to the course, followed by an ice-breaker key-note address in which the invited speaker will give his/her perspective on how models should be adapted to cope with climate change.
  2. Poster Carousel: After the Sunday dinner there will be a poster carousel in which participants introduce themselves via a poster. Each round lasts 15 minutes (5 minutes introduction and 10 minutes questions and discussion). Posters will remain in the lecture room throughout the course.
  3. Lectures and Discussion:Each day will start off with a set of lectures followed by a discussion in which participants challenge the speaker on the presentation and a paper that the speaker provided prior to the course.
  4. Hands on exercises/practicals:After the morning lectures and discussion, time is reserved for exercises and practicals in which participants can acquaint themselves with novelties in the domain of sensing and control with application to agriculture.
  5. Group work:Afternoons will primarily be spent on group work in which groups of approximately 5 participants will work on tackling a challenge within the domain of  sensing and automation which have been brought forward by the invited speakers. Output of the group work will be presented on Friday morning in 15-minute presentations per group followed by 15 minutes discussion.
Course Speakers
Course Organisers
General information
Target Group PhD candidates or junior researchers
Course duration 5 days
Language of instruction English
Number of credits 1. 5 ECTS
Prior knowledge Participants should have knowledge of robotics, sensing and control
Location Hotel de Bosrand, Ede
Please visit the DISC website for more information. You can register via the registration form.
More information

Claudius van de Vijver (PE&RC)


ECC’24 Pre-conference workshop on “Navigating uncertainty: online multi-agent control, optimization and learning”

Dear All,

You are cordially invited to the workshop “Navigating uncertainty: online multi-agent control, optimization and learning”, that we are organizing for ECC24, Stockholm, on June 25.

The workshop aims to provide insight into recent advances and open challenges in multi-agent systems, with focus on online and uncertain scenarios. We have an exciting lineup of keynote speakers. Program and up-to-date info can be found on the workshop website.

Registration information can be found here.

Do not hesitate to contact us for any information, and feel free to share the invitation with all the interested colleagues and students.

The organizers

Mattia Bianchi (ETH, Zürich)
Nicola Bastianello (KTH, Stockholm)
Florian Dörfler (ETH, Zürich)

New people

Delft University of Technology

Name: Bart Wolleswinkel
Starting date: 01-02-2024
Function: Phd
Group: TUD – ME – DCSC
Supervisor: Riccardo Ferrari

Hi everyone, my name is Bart, and I am a recent System and Control graduate at DCSC. I am joining Riccardo Ferrari’s group, where I will be working on secure control of wind farms in a optimal and distributed fashion. My research interest are cybersecurity, game theory, information theory and optimization, whilst in my free time I enjoy sailing and graphic design.

Name: Liam Cools
Starting date: 15-02-2024
Function: PhD
Group: TUD – ME – DCSC
Supervisor: Dr. Carlas Smith and Prof. dr. Michel Verhaegen

My name is Liam Cools. I was born and raised in Antwerp, Belgium, but came to Delft for my higher education in 2018. Since then, I have gotten my BSc degree in Aerospace Engineering, followed by an MSc in Systems & Control at the DCSC where my thesis research was in the field of numerical optical phase retrieval.

Now I have embarked on a new journey in my PhD under supervision of dr. Carlas Smith and prof. dr. Michel Verhaegen, where I will be performing research in the field of smart microscopy and imaging control as a member of Team Carlas Smith.

Name: Aleksandr Dekhovich
Starting date: 15-04-2024
Function: postdoc
Group: TUD – ME – DCSC
Supervisor: Dr. Soloviev and Prof. Verhaegen

I am Aleksandr and I will be working as a postdoc researcher under the supervision of Dr. Soloviev and Prof. Verhaegen. My project is related to machine learning applications in metrology using control tools.

Before joining DCSC, I was a PhD Candidate at MSE (also (3)ME), where my PhD topic was in deep learning and continual learning in particular. I also worked on some continual learning applications to computational mechanics.


Groningen University

Name: Ashutosh Jindal
Starting date: 01-05-2024 (tentative)
Function: Postdoc
Group: RUG- DTPA
Supervisor: Ming Cao
Project: controllability of hypergraphs

I did my Masters of Technology in Electrical Engineering from IIT Gandhinagar, and my PhD in Systems and Control Engineering, from IIT Bombay, under the supervision of Ravi Banavar and Debasish Chatterjee.  The topic of my Ph.D. thesis is “Feedback Linearization of Sampled Time Sytems”.

Wageningen University & Research

Name: Monique Mul
Starting date: 01-04-2024
Function:  Postdoc & Lecturer
Group: Agricultural Biosystems Engineering
Supervisor: PWG Groot Koerkamp
Project: IPM voor vogelmijt op praktijkbedrijven, Synergia

Name: Jianglin Lan
Starting date: 01-03-2024
Function:  visiting researcher
Group: Agricultural Biosystems Engineering
Supervisor: EJ van Henten
Project: DurableCase


Eindhoven University of Technology

Name: Tren Baltussen
Starting date: 01-03-2024
Function: PhD
Group: TU/e – ME – CST
Supervisor: Maurice Heemels
Project: Safe, Learning-based MPC With Applications in Autonomous Driving

My name is Tren Baltussen and I started my PhD with the Control Systems Technology group under the supervision of Alexander Katriniok and Maurice Heemels, in March of this year. My research focuses on safe, learning-based MPC for autonomous driving. I finished my bachelor’s degree in Automotive Engineering at the Hogeschool van Arnhem en Nijmegen in 2020. Subsequently, I started pursuing the MSc. degree in Systems and Control at TU/e which I completed last February.

Name: Tjeerd Ickenroth
Starting date: 01-03-2024
Function: PhD
Group: TU/e – ME – CST
Supervisor: Tom Oomen
Project: Learning in Motion

My name is Tjeerd Ickenroth and I recently started my PhD at the Control Systems Technology department. I did my master’s thesis in the same department exploring the field of Fault Diagnosis, particularly the design of a robust fault detection system for precision mechatronics. However, since my interests in control systems are broad, I am excited to announce that I have become a new member of the Learning in Motion project, where I will be exploring the field of iterative learning and repetitive control under the supervision of Prof. Tom Oomen. My project will be in collaboration with Canon Production Printing where I will be working at least one day a week under the guidance of Dr. Ir. Sjirk Koekebakker.

Name: Sander Doodeman
Starting date: 01-04-2024
Function: PhD
Group: TU/e – ME – CST
Supervisor: Duarte Antunes
Project: Autonomous aerial radiography inspections of offshore wind turbine blades

My name is Sander Doodeman and since April 2024 I have started as a PhD candidate within the CST group of Mechanical Engineering. Under the supervision of Duarte Antunes, Paula Chanfreut Palacio and Elena Torta. I will join a project in which two drones will be used to autonomously inspect offshore wind turbine blades using radiography, where I will be focusing on hovering control. This project is a collaboration between the TU/e, SpectX B.V. and Avular. I did my Bachelor and Master at the TU/e as well, and especially during my master thesis (where I used Spot the robot dog to map crops within a field using graph-based SLAM), I experienced the positive working atmosphere in the CST group, which is why I am looking forward to spending another four years here.

Name: Julius Krebbekx
Starting date: 15-04-2024
Function: PhD candidate
Group: Control Systems group
Supervisor: Amritam Das

Project: My project aims to develop input-output signal-based performance shaping techniques for nonlinear systems, where the idea is to generalize the well-celebrated techniques for LTI systems to nonlinear systems. Borrowing methods from nonlinear optimization (monotone operators and relative graphs), we aim to connect the time-domain behaviour of nonlinear systems to its frequency-domain characteristics and explore the relation with incremental dissipativity theory. The result should potentially be a unified framework for loop shaping to analyze, compute and optimize the performance of nonlinear systems.

I am Julius and I come from the neighborhood of Eindhoven. I received my BSc Applied Physics from the TU/e and my MSc in mathematics (dynamical systems) and theoretical physics from Utrecht University. My background and interests are quite broad, but I chose control systems specifically because it combines challenging mathematics with often a direct interpretation of the equations. In my spare time I play the piano (contemporary and classical), do some sports (cycling, running, golf) and ride my motorcycle. When on holidays, I spend my time hiking with friends, skiing, or camping.

Name: Hyosang Lee
Starting date: 10.05.2024
Function: university teacher
Group: TU/e – Robotics
Supervisor: A. Saccon
Project: Whole-body Robot Skin for Multi-modal Tactile Perception

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