Netherlands Cancer Institute, Elekta and UvA launch POP-AART Lab

The Partnership for Online Personalized AI-driven Adaptive Radiation Therapy (POP-AART) is the 28th lab to join ICAI. The lab will focus on the use of artificial intelligence for precision radiotherapy.

It is a major challenge to give patients the right dose of radiation, at the right spot with least damage to healthy tissue, and while the patient and the tumor move and change shape during radiation and over time. Within the POP-AART lab six PhD researchers will develop novel AI strategies for improving the images on which the radiation treatment is based, predicting changes over time of the tumor and incorporating them in automatic treatment planning and adaptation.

POP-AART will run for five years. Research topics range from improving CT images obtained just before radiation to the level of diagnostic quality CT images, predicting deformations and segmentations of the tumor and organs at risk and incorporate these data in online and automated treatment plan optimization for each patient individually at each radiation session.

The lab will be led by scientific directors Efstratios Gavves and Jan-Jakob Sonke. Gavves is assistant professor of Computer Vision and Deep Learning at UvA. Sonke is theme leader image guided therapy at the Netherlands cancer institute and Professor by special appointment of Adaptive Radiotherapy at the Faculty of Medicine at UvA. The Governing Board will consist of academic partners Lodewyk Wessels (NKI-AvL) and Mark de Graef (UvA) and industry partner Rui Lopes (Elekta).

About the Netherlands Cancer Institute

The Netherlands Cancer Institute, founded in 1913, is among the top 10 comprehensive cancer centers, combining world-class fundamental, translational, and clinical research with dedicated patient care. Their initiatives to promote excellent translational research have been recognized by the European Academy of Cancer Sciences, when they designated the institute ‘Comprehensive Cancer Center of Excellence in Translational Research’.

About Elektra

For almost five decades, Elekta has been a leader in precision radiation medicine. Their more than 4,000 employees worldwide are committed to ensuring everyone in the world with cancer has access to – and benefits from – more precise, personalized radiotherapy treatments. Headquartered in Stockholm, Sweden, Elekta is listed on NASDAQ Stockholm Exchange. 

Find out more about POP-AART lab.

Tilburg newest ICAI location with MasterMinds Lab

MindLabs recently joined the national Innovation Center for Artificial Intelligence (ICAI). This makes Tilburg one of eight locations with an ICAI lab. Together with the partners in the MasterMinds project, MindLabs collaborates in this public-private research lab, named MasterMinds AI Lab. The MasterMinds AI Lab is one of the many initiatives within MindLabs and is dedicated to the development and evaluation of new technologies, focusing on the cross-fertilization between artificial minds and human minds.

Artificial Intelligence and Human Behavior

The ICAI is a national collaboration of several universities, companies and the Dutch government with 27 labs on eight locations. The goal  of the Dutch government and universities is to remain at the forefront of AI by knowledge development and nurturing young talent.  MasterMinds collaborates in research at the intersection of robotics and avatars, serious gaming, decision making, and virtual and augmented reality. The results of these studies are applied to realize AI solutions for the benefit of society.

Max Louwerse

Professor Max Louwerse, scientific director of the MasterMinds AI Lab: “The future of AI increasingly lies at the intersection between artificial intelligence and human behavior. The MasterMinds project works at this interface to develop new technologies and will be able to apply them immediately. This is entirely in the nature of MindLabs.”

Five MasterMinds research projects

The MasterMinds project consists of five innovative research projects, aiming to develop breakthroughs with interactive AI technologies such as serious gaming, augmented and virtual reality, intelligent tutoring systems and natural language processing and data science. Research questions include: Can we train and improve complex decision-making using serious gaming? What is the learning effect of training pilots using virtual reality? How do we effectively design AR and VR training modules? How can we develop and use intelligent tutoring systems? The project is funded to stimulate regional ecosystems to develop a resilient, sustainable, and future-proof economy with a central role for SME’s.

The MasterMinds project brings together knowledge institutions, industrial partners, and governmental organizations to work together on AI solutions that can be readily used for the partners. The project aims to develop AI technologies combined with the impact on and input from human behavior, across multiple sectors in society in the field of aerospace, logistics, maintenance, and education focusing on robotics and avatars, serious gaming and learning, language and data science technologies and virtual and augmented reality solutions. The project provides a T-shaped profile of explainable AI solutions, where depth is achieved per subproject while breadth is achieved across the five projects. The project answers questions that have been formed by the industrial partners to prepare for the technology-driven future that lies ahead.

The five MasterMinds reseach projects:

  1. Serious Games in logistics – Port of Rotterdam
  2. VR for air force simulations – Dutch Royal Airforce and MultiSIM
  3. AR & VR for production and maintenance – Actemium, Marel en CastLab
  4. Evidence-based prevention: predictive analytics – Interpolis en Gemeente Tilburg
  5. Virtual Reality in Education – WPG Zwijsen, Spacebuzz en Timeaware

MasterMinds brings together the “brightest minds” in artifical and human intelligence.

Read more on the MasterMinds Lab

UvA, TU Delft and launch Mercury Machine Learning Lab

UvA, TU Delft and collaborate on research into better recommendation systems

In the Mercury Machine Learning Lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) will be working together with on various improved recommendation systems. The collaboration provides the unique opportunity to test AI techniques in the real world, allowing new machine learning methods to be safely developed for wide application, for example in mobility, energy or healthcare.

Every day, millions of travellers from all over the world make multiple decisions on related to their upcoming travel plans. With all of these taps and clicks on property photos and scrolling through search results, naturally has a wealth of data insights to help the company make changes on the platform to improve the customer experience.In addition to the responsibility of handling all of this information securely and ethically, how do you analyse all of this data properly and continue to make useful recommendations for customers? Is what works well for a Dutch traveller equally as relevant for a traveller from Japan? And how do you ensure that customers continue to receive interesting travel recommendations that are relevant to them without getting stuck in a filter bubble?

On the road to even better recommendations

One way to understand what constitutes a good recommendation is looking at what previous travellers have chosen and the experiences that their choices yielded. Machine learning techniques are well suited to learning such connections and preferences. However, the problem is that the connections and preferences found in the data are not only informed by the choices of other travellers, but also by the suggestions and selections the system showed them. In the Mercury Machine Learning Lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology will work together with data scientists from to develop methods that will ensure that this type of bias is avoided and that the learned connections remain accurate in a new or different context.

From the classroom to real-time e-commerce
Joris Mooij, scientific director of the Mercury Machine Learning Lab at the UvA: ‘It’s a huge opportunity for us as researchers to have access to a live dataset of global data and be able to experiment on’s platform.’ Frans Oliehoek and Matthijs Spaan, scientific directors from TU Delft, agree. Oliehoek: ‘By testing AI techniques in the real world, we can better understand the limitations of current state-of-the-art methods in the field of reinforcement learning, as well as improve the application of AI in practice.’ Spaan: ‘The lab’s focus on developing better algorithms for recommender systems is highly relevant to our society as these systems guide many of our digital interactions. By addressing fundamental AI challenges, the results of the lab will also be valuable in other domains.’

Onno Zoeter, Principal Data Scientist and scientific director adds: ‘Unlike in a hospital scenario for example, where experimenting with different types of data-driven recommendation systems can have real life-and-death consequences for patients and their suggested treatment protocols, testing approaches, models and hypotheses with travel data from doesn’t come with the same public health implications. This means we can safely test and develop new machine-learning methods together that also have a potential impact far beyond the trips booked on our platform.’

Learnings from other languages

Artificial intelligence and natural language processing are already used to perform many important tasks in different languages, such as categorising reviews and fraud detection. The researchers will look for ways of creating a system with multiple languages in which the smaller languages can benefit from what has been learned in models and rounds of experimentation with languages that are spoken more widely. This should enable to support all 44 languages and dialects in which their platform is available to customers in various new contexts, even more quickly.

Nurturing Dutch talent

The Mercury Machine Learning Lab will be part of ICAI, the Innovation Center for Artificial Intelligence. The Lab will provide world-class opportunities for Machine Learning graduates to stay in the Netherlands and lead innovative research, keeping important talent connected to Dutch universities and industry.

In addition to the existing researchers, the Mercury Machine Learning Lab will comprise six PhD candidates and two postdocs who will work on six different projects related to bias and generalisation problems over the course of the next five years. They will spend two days a week in the office at doing research and actively participating in related streams of experimentation to test their hypotheses.

Find out more about Mercury Machine Learning Lab

Start of new ICAI lab: AI for Oncology

The AI for Oncology Lab is a collaboration between the Netherlands Cancer Institute and the University of Amsterdam. Both institutes join forces in the development of AI algorithms to improve cancer treatment. Join the opening on 24 June 2021.

Sign up for the opening on 24 June

The AI for Oncology lab will officially and festively start and you are invited! After the registration you will receive a link.

Date: Thursday 24 June 2021
Time: 16.00 to 17.00 hrs
Register here for the digital opening

Improved cancer treatment

The goal of the collaboration between the Netherlands Cancer Institute (NKI) and University of Amsterdam (UvA) is improved cancer treatment through the aid of Artificial Intelligence. A lot of complex information is acquired from patients during and prior to the treatment through medical imaging, pathology, DNA, and so on. AI solution can assist medical specialists finding and applying the right treatment based on all this information. Moreover, AI algorithms have the potential to guide medical interventions accurately to the location of the tumor without damaging surrounding healthy tissue.

Through this collaboration, expertise in cancer research and AI technology blend together. The domains are represented by Clarisa Sánchez on behalf of the UvA, as AI&Health expert and Jonas Teuwen and Jan-Jakob Sonke on behalf of the NKI, specialized in oncology research and AI. The first goal is to conduct innovative scientific research. Subsequently, if successful, the lab aims to integrate the results in clinical practice.

The benefits of AI for cancer research

AI technology will play a bigger part in the future of cancer research. Machine learning algorithms can now perform certain tasks that used to require human intelligence. Algorithms based on artificial neural network are used in ‘Deep Learning’. Instead of relying on a programmer to explicitly tell the algorithm what to do, this network only requires an end goal and will learn how to achieve from many examples. The benefits of that is that this ‘Deep Learning’ algorithm can reach insights the programmer would never have considered.

In the case of image recognition for cancer detection, we can use a large database containing images of patients with and without cancer. The computer can use this data to learn and, if the database is sufficiently large, will be able to detect tumors even better than a specialist. In terms of personalized medicine, the images and other data can be used to better predict the most beneficial treatment option for every patient.

Image guided therapy aims to deliver therapeutic interventions with high accuracy. AI algorithms can be trained to automatically analyze medical images acquired during treatment and guide the intervention to the correct location.

In the lab, five research topics will be studied covering important aspects such as early diagnoses and image guided therapy.

Find out more about AI for Oncology lab

AI-RONDO: Greater control over Parkinson’s and Alzheimer’s using apps and avatars

Speaking more softly and poor articulation could be an indication of Parkinson’s or Alzheimer’s, or that these conditions are worsening. Radboud University, Radboud university medical center (Radboudumc) and imec, partners in OnePlanet Research Center, are using artificial intelligence (AI) to analyse signs of this kind. The aim is to detect the disease at an early stage. They are also developing digital aids, such as apps and avatars, for patients already suffering from these diseases, so that they receive an indication at home that the disease is changing and care providers can intervene in time. The institutes are now setting up a new ICAI lab to this purpose: AI-RONDO (Risk Profiling and Decision Support). 

“There is already a lot of data on patients suffering from Parkinson’s and Alzheimer’s, which are two common disorders of the brain. By using AI algorithms and models on this information, we can find new links and for example pinpoint groups facing an increased risk of developing complications. Using these enriched data we are able, following diagnosis, to prescribe treatment for a patient specifically designed for their personal risk profile. We can also analyze those signs – such as speaking more softly, articulating less clearly, a change in walking patterns or heart rate – that indicate that something is going wrong,” says Marjan Meinders, one of the lab’s three academic directors. “On the basis of a sign like this, a care provider can prevent further deterioration.”

Digital Tools

AI-RONDO will use digital tools to collect data in the home situation and to provide the patient with customized personal advice. For example an app linked to a bracelet that provides an analysis of how symptoms changed over the course of the day, linked to the taking of medication. Or an avatar, a virtual assistant that engages in conversation with the patient while simultaneously collecting new data on the progression of the disease from their speech. Meinders: “This extra support – in addition to regular care – offers patients more information on and a greater understanding of their own health. This means they have greater control and are able to delay the disease’s progress themselves.”

24th ICAI lab

The research is being conducted in ICAI’s AI-RONDO lab. ICAI (Innovation Center for Artificial Intelligence) is a national network that focusses on technology and talent development between knowledge institutions, industry and government in the field of AI. AI-RONDO is the 24th ICAI lab in the Netherlands and the second in which Radboud University, Radboudumc and imec, partners in OnePlanet Research Center, are collaborating. In February this year, they set up the ICAI lab AI for Precision Health, Nutrition and Behavior along with the 4th partner Wageningen University & Research.


OnePlanet Research Center wants to stimulate innovations in the Dutch province of Gelderland and works closely with industry and societal organizations from the region. Several regional partners are already involved in AI-RONDO, and the research team cordially calls on other interested parties to come forward as well. The current partners are: ANT Neuro, Artinis Medical Systems, imec-NL, InfoSupport, NIVEL, Noldus Information Technology, Orikami Personalized Healthcare, ParkinsonNet, Stichting Open Spraaktechnologie and Virtask.

More information on AI-RONDO

Second Utrecht University AI lab joins ICAI network

After the success of the National Police Lab AI, now the second Utrecht University AI lab joins ICAI: AI & Mobility Lab. Utrecht computer science researchers launched this second AI Lab in January 2021. The new lab focuses on the themes of mobility, transport and logistics. The researchers work with partner organisations NS, ProRail and Qbuzz, to link, strengthen and further expand research into mobility issues.

Transport organisations, distributors and public organisations encounter major challenges, to which AI research can contribute. Public transportation, shared mobility, road traffic, logistics and human movement behaviour raise issues about safety, robustness, accessibility, travel time, health and such. In the AI & Mobility Lab, Utrecht computer science researchers will collaborate with various organisations to develop innovative AI techniques for challenges in mobility and public transportation.

Important role for AI research

Mobility is in full swing. Cities are especially getting busier, and because of increasing concern for sustainability, alternatives for privately-owned petrol or diesel cars are becoming more and more important. Commuters will increasingly use combinations of different forms of mobility and public transportation. Public transportation is becoming more electrified and is expected to play a crucial role in future transport.

Artificial intelligence will make a strong contribution to these developments. There are important challenges in managing and controlling vehicle and passenger flows, infrastructure planning, and the development of new tools and platforms for matching supply and demand such as MaaS (Mobility as a Service). Researchers in the AI & Mobility Lab will work on data-driven techniques, operations research, algorithms, human-centered AI and agent-based simulation.

Marjan van den Akker, coordinator of the AI & Mobility Lab: “The challenges of our stakeholders are complex and require a state-of-the-art approach. Where needed, we collaborate with researchers from different disciplines. By developing knowledge and techniques together, we strive to make a strong societal impact.”


In addition to research, the AI Labs of Utrecht University also play an important role in education for professionals, and programmes where students work together with professionals.

Read more on Utrecht AI & Mobility Lab

e/MTIC AI-Lab becomes fourth TU/e ICAI Lab

In the field of healthcare, AI still has several issues to address. In hospitals, professionals are still hesitant to employ AI-based techniques because of lack of transparency, interpretability and clinical evidence.

Through the e/MTIC AI-Lab, AI will be made available to work in close collaboration with the clinical staff and MedTech industries to help improve personalized treatment. This lab has now also joined ICAI and is the fourth TU/e ICAI lab. ICAI is a network of Dutch research programs that is designed to bring together researchers in the field of AI. e/MTIC is a unique collaboration between Eindhoven University of Technology, Catharina Hospital, Maxima Medical Center, Kempenhaeghe Epilepsy and Sleep Center and Philips to enable a fast track to high-tech health innovations.

AI techniques mostly act as a black box without knowing precisely what part of the data is being used and how. Furthermore, AI tends to be specialized and lacks robustness when small changes to existing procedures are required. In these cases, human doctors are still much better able to handle the complexity of the situation. However, that does not mean that the work of humans is always correct, but they are able to weigh up when it is necessary to ask for help from someone else, for example, something AI cannot do today.

New Healthcare Systems

In healthcare, systems are continuously evolving and the ability of specialists to fully understand the complex inter-relationships of the various components is becoming more difficult. It will be particularly important for this information to be organized, not just using new forms of presentation such as virtual reality and digital twins but also by linking models of information to predict what the doctor should see next.

These new systems must be designed in a manner to protect people, the environment and the economy. ‘Responsible AI’ is a term that is usually applied to dealing with consumers or private individuals. For healthcare, this encompasses responsible use and storage of sensitive personal data, but also promotion of patient empowerment, avoidance of harm and bias, and protection against misuse.

E/MTIC ICAI Research Focus

Many of the e/MTIC researchers are currently working on and implementing analysis techniques and (prediction) algorithms for improved (patient) monitoring and diagnosis and to help optimize individual treatment strategies in collaboration with many medical specialists. Due to the many complexity and heterogeneities in medical data, these approaches and other innovations will be further developed, implemented and automated through projects in e/MTIC. The research focus is on robustness and improved stability of algorithms and methods.

In the e/MTIC ICAI lab, AI will be mainly used for the following application areas:

  • Imaging: strongly enhanced Ultrasound, MRI and CT imaging by embedding task-adaptive AI across the imaging chain
  • Patient monitoring: strongly enhanced monitoring of vital signs both in clinical and in extramural settings
  • Clinical decision support systems: Use AI to combine various data streams (e.g. EMR, images, spot checks) to produce explainable and patient-specific advice, early warning and alarms.

The academic directors of the lab are professors Frans van de Vosse and Jan BergmansCarmen van Vilsteren is the lab manager.

Fast Track to Clinical Innovation

Given that the main purpose of e/MTIC is to provide a “Fast track to clinical innovation”, Artificial Intelligence is an extremely important instrument to support this goal. Both in clinical decision support in general, and in-patient monitoring and image analysis in particular, novel AI techniques provide powerful approaches to identify patient deterioration at an earlier stage, diagnose conditions more accurately, better guide treatment, and improve secondary prevention.

Eindhoven Medtech Innovation Center

Bringing technical innovations all the way from early research to implementation and commercialization can often take a long time. In healthcare innovation, in particular, this lost time can often equate to lost lives. The goal of the Eindhoven MedTech Innovation Center (e/MTIC) is to create and expand an ecosystem that strongly increases the speed of high-tech health innovation, maximizing value for patients. We consider such an ecosystem to be an unmet need and a unique opportunity for the Brainport region to make significant contributions to visionary new developments in healthcare.

e/MTIC is a large-scale research collaboration between the Catharina Hospital (CH), the Maxima Medical Center (MMC), Kempenhaeghe Epilepsy and Sleep Center (KH), Eindhoven University of Technology (TU/e) and Royal Philips Eindhoven (RPE) in the domains cardiovascular medicine, perinatal medicine and sleep medicine. The partnership has evolved over several decades, has a strong scientific and valorization track record and currently encompasses around 100 PhD students, supervised by a similar number of experts from the various partners.

Find out more about e/MTIC AI-Lab

ICAI Interview with Rinke Hoekstra: ‘Academics help seeing the big picture.’

Rinke Hoekstra, Lead Architect at Elsevier, is Industry Director of Discovery Lab. This ICAI-lab, a collaboration of Elsevier, University of Amsterdam and Vrije Universiteit Amsterdam, kicked off in April 2020. Hoekstra: ‘Within Elsevier this is already seen as one of the most successful collaborations with academic partners.’

You’re the Industry Director of Discovery Lab. Can you briefly explain what your role is?

‘My role is to intermediate between the company and the partners. I make sure the lab is not overloaded by requests from the company. The lab members have to do research, but as a company, we have to make sure the research is of use to us. That’s a tension. We have to find a good trade-off there.’

What are the challenges involved with that?

‘I communicate the relevance of the lab for the company. The company as a whole is used to deal with a one-year-horizon, but the outcome of the lab will take years. A lot of people in the company don’t think in these terms of long- term innovation. It’s all very academic to them. Another challenge is bringing interesting problems to the academic partners. It’s quite challenging to make sure that we find the right nuggets of data within the organization that are of use to the researchers to play with.‘

‘Our customers are researchers. We feel that it’s our job to help them do research’

How is the lab working out so far?

‘The PhD researchers and the Elsevier data scientists just hit it off and started working. They created a very convincing story in their presentation during the internal kick-off of the lab. I see that internally this is already seen as one of the most successful collaborations with academic partners. The other Elsevier research collaborations are typically at a higher level. They have a couple of meetings every year and then the researchers go off and do their research. But in this lab the data scientists are really working together with the lab members in a self-organized way. They are also bringing in master students who do their research with us. We are creating our own little community. If you don’t have that shared community, you will never have a good collaboration.’

What was the motivation of Elsevier to enter this lab?

‘Our customers are researchers, either in academia, R&D companies or health. We feel that it’s our job to help them do research. We can sell products so they can do their research better, but we can also directly collaborate with them. It is a good opportunity to do research that we don’t necessarily see within our own organization.’

‘We have a longstanding collaboration with Amsterdam Data Science. And we saw this opportunity to work even more closely with our ADS partners. It is so interesting to work with these people. Frank van Harmelen is clearly one of the world leaders in terms of knowledge representation and reasoning knowledge graphs. Paul Groth’s work on provenance and learning knowledge graphs from structured information is well regarded. Maarten de Rijke is obviously big in information retrieval. And the group of Max Welling in machine learning: all world-class researchers. On other universities they have maybe one or two of these fields covered. It is very rare to see that combination in one place.’

What is the most interesting thing about your job?

‘I stay very close to academia and to that kind of free and open thinking. As a lead architect within Elsevier I work with the same technology and problems, but the context is very different. So it’s good to have this more open context where you can freely discuss ideas without somebody saying: ‘what’s the use case?’.’

At the ICAI Lunch Meetup of February 18, 2021, Rinke Hoekstra will present Discovery Lab. More info and sign up here.

OnePlanet opens ICAI Lab ‘AI for Precision Health, Nutrition and Behaviour’

Together with research partners Radboud University, Radboudumc and Wageningen University & Research, OnePlanet Research Center opens the new ICAI Lab. Using AI, they want to improve personalized lifestyle feedback and stimulate healthy behaviour. For example, by developing smart chatbots that motivate people to eat healthier or quit smoking.

The effect of lifestyle changes varies greatly from person to person. It depends on someone’s genetics, eating pattern, activity and the environment in which they live. By combining data on these factors, a deeper insight into the effects of lifestyle feedback is created.

From sensors to coaching

The research team is focusing on three tracks. They develop new sensors to be able to collect more and better health data. Besides that, they also develop smart AI algorithms and machine learning techniques to be able to extract more knowledge, and therefore value, from these data. With this enriched knowledge, lifestyle feedback can be further personalized. This helps in coaching people towards healthier behaviour.

The team focuses mainly on applications in diet coaching, prevention of cognitive decline, prevention of orthostatic hypotension and health-promoting chatbots for smoking addiction and sexual health.

Multidisciplinary approach

These efforts require a multidisciplinary approach. Lab Manager Ruud van Stiphout: “The academic partners will bring domain knowledge and AI expertise to the table, while the industrial partners provide the use cases and innovations that create societal impact. By combining these different disciplines, we can address lifestyle challenges integrally. This ensures optimal impact.”

The research team

The ICAI Lab consists of 7 PhD students and 2 postdocs working on these challenging AI issues. The lab itself is coordinated by Guido Camps (Wageningen University & Research) and Tibor Bosse (Radboud University), the two scientific directors, Ruud van Stiphout (OnePlanet) operates as lab manager and Elena Marchiori and Ton Coolen (Radboud University) coordinate the work packages.

More info on the lab

The Netherlands AI Coalition and ICAI strengthen cooperation

The Netherlands AI Coalition (NL AIC) and the Innovation Center for Artificial Intelligence (ICAI) are strengthening their ties. The organisations are committed to developing the Netherlands into a leading AI country. ICAI has been involved since the foundation of the NL AIC as one of the leading scientific AI communities with research labs throughout the country. It was decided to further strengthen the cooperation by making use of each other’s strengths and expertise. This will allow us to serve companies, government, educational and research institutions and civil society organisations even better.

The cooperation focuses on strengthening AI knowledge and talent in the Netherlands. The first steps will be taken in the areas of Research & Innovation and Human Capital: two important pillars to get the Netherlands in a vanguard position in terms of knowledge and application of Artificial Intelligence (AI) for prosperity and wellbeing.

Research en Innovation

The collaboration should lead to further growth in the number of ICAI labs in 2021. ICAI focuses on the joint development of AI technology by means of industrial labs. These are collaborations between knowledge institutions, industrial partners and/or public organizations. ICAI now has 20 labs, In Amsterdam, Delft, Den Bosch, Eindhoven, Nijmegen, Utrecht, and Wageningen. Work is in progress on the development of another 10 labs, at current locations and at new locations such as Enschede, Maastricht, Rotterdam and Tilburg. Each of the locations has its own area of expertise that match the forces of the region.

Further building up and rolling out the network of ICAI labs is an essential part of the national AI network, which the NL AIC wants to realise together with partners. The choice has been made to work with hubs and spokes, which together form the structure of the AI network. The labs will play an important role within this network’s hub-and-spoke structure. The Netherlands AI Coalition will work to support ICAI in the development of the lab network. Maarten de Rijke, scientific director ICAI: “We are faced with major societal challenges. AI technology can be an important part of the solutions. Spread throughout the country, the ICAI labs strengthen the national and local research and innovation capacity in AI technology. Let’s get to work!”

Human Capital

AI is changing our work and society. By investing in AI in the right way, we can grow as a country and take an important position. This should lead to retention and even expansion of work and jobs if we develop the right expertise. The opportunity for the Netherlands is to prepare for this. Kees van der Klauw, Coalition Manager NL AIC: “Our joint ambition is to develop and retain talent (students and researchers) for the Netherlands and to attract foreign talent to the Netherlands. We do this, for example, by connecting the PhD students in the ICAI labs to the Dutch lmarket. We let them get acquainted with Dutch organisations that are looking for AI talent. We also want to strengthen each other in developing and making available AI courses and training. For example, ICAI contributed to the National AI Course and worked on the development of two AI MOOCs (Massive Open Online Courses) last year. The Human Capital working group of the NL AIC aims to make courses in AI widely available and, where necessary, to develop them further per sector. These are activities in which we can strengthen and support each other.”


By jointly investing in people and talent development, we can make steps towards making the Netherlands ready for the future. Both organisations are convinced of the importance of investing in AI and of taking action to drive research, innovation and talent development around AI. “Through this collaboration, we achieve acceleration and broaden the impact.”