Episode 17 with Inge Molenaar of Radboud University and the Adaptive Learning Lab

In episode 17 of Snoek op Zolder Inge Molenaar, associate professor at the Behavioural Science Institute (BSI) of Radboud University and leader of the Adaptive Learning Lab, talks about AI, data and learning analytics in education. She discusses the research, use and the didactical and ethical implications of adaptive learning technologies in human learning.

The podcast is in Dutch.

Not sure about your next step as a PhD student in AI? Knock on Kai Lemkes’ door

Kai Lemkes has been a recruiter in the AI domain for ten years. Since a few months he has been a matchmaker within the ICAI Launch Pad program where he coaches PhD students. Lemkes: ‘PhD students have a blind spot when entering the labor market.’

Kai Lemkes

What does the ICAI Launch Pad program look like?

‘After a first introductory meeting with the PhD students, I coach them in how they can best prepare for a job application, how to build a resume, how to present themselves on LinkedIn, et cetera. We evaluate that and then look at how this person can best present themselves and enter the labor market. We can also hold a closing meeting on request. My door is always open.’

Why is there a need for Launch Pad?

‘Many of these PhD students are at a crossroads where they don’t really know what they want next. What I encounter a lot is that students want to stay in the domain they’re already in, purely because they already know it. I recently spoke to a girl who was strongly attached to the research domain. But when I asked her to describe her ideal job, she said that she would prefer to keep improving products, give presentations and a number of things that you see much more in the commercial domain. It is therefore very important to show this group clearly what they actually choose. That’s a blind spot.’

‘The AI ​​domain has exploded in just a few years. At the moment, almost every company I work with – mainly top-500 companies – is investing in AI. For that reason, many young professionals are quickly lured abroad by companies. Foreign companies are sometimes a bit more ‘aggressive’ when it comes to recruiting talent. They proactively approach PhD students and offer them a substantial salary.’

What are Dutch companies not doing well besides less actively recruiting talent?

‘I see the recruitment process go wrong quite often. Candidates have to sell themselves in a very short time and that does not always result in a good match. Based on two or three conversations, it is quite difficult to determine whether someone is a good fit for a company for the long term. Right now, you need the luck to meet someone who likes you. If you’re having a bad day, you’re not going to look good. And especially in the technical domain you will find many specialists who are a bit more introverted or who find it less easy to present themselves, so that they already start such a process quite tense or uncertain.’

How can companies better handle this?

‘It is better to set up a process in which a company really experiences a candidate and to schedule interviews with several people from the company and not just one person. It is also a good idea to let a promising candidate speak with the whole team. Because the demand for AI specialists is so enormous right now, you sometimes see that companies present themselves as super high-tech and that a young professional later finds out that it is not that high-tech at all. Or they find out that there are no other specialists with whom they can consult. And then they can feel terribly alone. Companies need to be honest about what they have to offer.’

What is your solution to this problem?

‘I am developing the digital platform Future Impact. This should become a lively community in which students and young professionals can help each other, have peer-to-peer conversations and give ratings to companies. On this platform, companies can also present themselves and tell what they have to offer as an employer. Virtual appointments can then be scheduled for a first acquaintance. I also want to organize meetups here with people who, as PhD students, have made the step into the commercial world and can coach others in this process.’

How did you get into this job?

‘I really enjoy making matches and connecting people. I like to network and chat. I stumbled into the AI domain by accident, but I really fell in love with it. Such beautiful things happen here; startups working on zero-co2 emissions technologies, for example. AI offers so many possibilities.’

What does ICAI mean to you?

‘I am originally a commercial recruiter, but for ICAI I am really more of a coach. And actually, as I found out again, I think that’s the most wonderful job. In this role as a coach, I enter the conversation with a different intention than as a recruiter. That gives me a great deal of satisfaction. In addition, my network is growing. My highest goal is to get to know the entire AI ecosystem of the Netherlands.’

Kai Lemkes is a matchmaking expert within AI. He is the founder of several matchmaking platforms including Future Impact.

Interested as a PhD student or organization to participate in ICAI Launch Pad? Register here or send an email to kai@future-impact.io.

Nine Veni grants for AI researchers

The Dutch Research Council (NWO) has awarded nine Veni grants to researchers involved in groundbreaking AI research. The recipients can use the grants – up to a maximum of 280,000 per researcher – to further develop their research ideas over the next three years. ICAI wants to congratulate these colleagues for their achievements!

The AI recipients of a Veni grant:

  • Continual Learning under Human Guidance
    dr. E.T. Nalisnick (M), Universiteit van Amsterdam
    Artificial intelligence (AI) systems need to adapt to new scenarios. Yet, we must ensure that the new behaviours and skills that they acquire are safe. The researcher will develop AI techniques that allow autonomous systems to adapt but to do so cautiously, under the guidance of a human.
  • Intelligent interactive natural language systems you can trust and control
    dr. V. Niculae (M), Universiteit van Amsterdam
    Artificial intelligence agents are seemingly approaching human performance in natural language tasks like automatic translation and dialogue. However, deployed in the wild, such systems are out of control, learning to produce harmful language even unprompted. Using recent machine learning breakthroughs, the researcher rethinks language generation for trustworthiness and controllability.
  • Efficient AI with material-based neural networks
    dr. H.C. Ruiz Euler (M), Universiteit Twente
    The unprecedented success of artificial intelligence (AI) comes at the price of unsustainable computational costs. This project will research the potential of a novel technology for highly efficient AI hardware: “material-based neural networks”. This technology will enable the next generation of efficient AI systems for edge computing and autonomous systems.
  • Helping computers say what they mean to say
    dr. J.D. Groschwitz (M), Universiteit van Amsterdam
    When a computer talks to us, for example when answering a question, it must translate that answer from its inner computer representation to fluent human language. This project combines linguistics and state-of-the-art machine learning to create a language generation system in which the output text expresses exactly what the computer meant to say.
  • The life and death of white dwarf binary stars
    dr. J.C.J. van Roestel (M), Universiteit van Amsterdam
    Double white dwarf stars are a rare but important type of binary star. They are potential supernova progenitors, some merge to form massive rotating white dwarfs, and they also emit gravitational wave radiation. I will combine data from the Dutch BlackGEM telescope with multiple other telescope surveys and use novel machine learning methods to uncover the population of short-period eclipsing white dwarf binary stars across the entire sky. By comparing the observed population and characteristics with binary population synthesis models, I will determine how these double white dwarfs end their life.
  • Personalizing radiotherapy with Artificial Intelligence: reducing the toxicity burden for cancer survivors
    Lisanne van Dijk PhD, University Medical Center Groningen (UMCG)
    Many head and neck cancer patients suffer from persistent severe toxicities following radiotherapy. As survival rates increase, toxicity reduction has become more pivotal. This project uses Artificial Intelligence techniques to predict toxicity trajectories, which can facilitate personalized decision-support to guide physicians in finding optimal strategies to reduce these severe toxicities.
  • Towards realistic models for spatiotemporal data
    dr. K. Kirchner (V), Technische Universiteit Delft
    Many environmental factors, such as temperature or air pollution, are recorded at several locations and dates. Because of limited computing power, a realistic analysis of the resulting large datasets is often unachievable. This project develops computational approaches which enable efficient accurate data analysis and reliable forecasts for phenomena with uncertainty.
  • Explainable Artificial Intelligence to unravel genetic architecture of complex traits
    Gennady Roshchupkin PhD, Erasmus MC Medical Center
    While we have learned that most diseases have a genetic component, we are still far away from understanding the underlying processes. Using Artificial Intelligence, I will investigate the complex relationship between DNA mutations and human health. This will be the basis for development of novel diagnostic, prognostic and therapeutic tools.
  • Neural networks for efficient storage and communication of information
    dr. J. Townsend (M), Universiteit van Amsterdam
    The brain is an extremely efficient system for storing and communicating information. This research will study the use of artificial neural networks, inspired by the mechanisms in the brain, for data compression, enabling faster internet communication and more efficient storage of computer files.

Find the complete list of Veni grants 2021 here.

Episode 16 with Dominique Roest of the Police AI Lab

In episode 16 of Snoek op Zolder Dominique Roest, Kwartiermaker Team Rendement Operationele Informatie at the Dutch Police and member of ICAI’s Advisory Board, tells about the huge increase in data in the police world, the ethical aspects that play an important role with that, why AI is such an important asset for detective work, the TROI-team as a startup within the police, how much fun it is to work for the police, the values of good laws and regulations and the future of AI for investigative work.

Episode 15 met Gijs Dubbelman

In Snoek op Zolder #15 is Gijs Dubbelman van het EAISI Mobility Lab van TU Eindhoven University en NXP Semiconductors te gast. De aflevering gaat over de toekomst van neurale netwerken in zelfrijdende auto’s, het nut en de uitdagingen van zelflerende systemen, segmentatie van videobeelden om daaruit veel meer informatie te halen, neurale netwerken die meerdere taken aankunnen, transparantie van dat soort netwerken, trainingsdata voor intelligente auto’s, Europa versus China en de VS, het Max Verstappen effect en data analyse in de F1, duurzaamheid en AI en de toekomst van de automotive industrie.

ICAI Launch Pad open call for 2nd batch of motivated PhD students looking to receive free career coaching

PhD Students following an AI-related study who are planning to enter the job market can register for an intensive free career program as of now. During this intense program the students will receive 1:1 coaching sessions from an AI-domain specialist with over 10 years’ experience within the field.

Among other things students will learn about:

  • The differences between the academic field and commercial industry,
  • How to find relevant jobs in the market,
  • How to reach out to potential employers
  • How to build-up your LinkedIn profile,
  • How to best build your resume to stand out, and
  • How to prepare for a job interview all get addressed.

Students can register till the 15th of February ’22 when the 1st rounds of qualification will start.
Register here or send an email to kai@future-impact.io.

Episode 14 with Marlou Snelders and Saskia Lensink

In this new episode of Snoek op zolder host Hennie Huijgens speaks with Marlou Snelders and Saskia Lensink about research into language and speech technology at the NAIN. They discuss who pays for such a research lab and how you organize such a complex collaboration. They talk about the growth fund of the Dutch AI Coalition and about why and how you should involve citizens in the development of AI. There is also some gossip about Bert, Robbert, Bertje, Roberta and Camembert. (This podcast is in Dutch.)

Marlou Snelders is innovation liaison at HSD Security Delta and coordinator of the Security, Peace and Justice working group of the Dutch AI Coalition and Saskia Lensink is specialist in the field of language and speech technology at TNO and one of the leaders of the NAIN.

Limburg welcomes first ICAI Lab for the development of AI for patient care

Knowledge institutions from Limburg will join forces with local parties in healthcare and IT. The first ICAI Lab in the region – the ICAI Brightlands Smart Health Lab – is committed to making breakthroughs in patient care by developing and deploying artificial intelligence.

ICAI Brightlands Smart Health Lab

With the arrival of the ICAI Brightlands Smart Health Lab, Limburg joins the national network of ICAI Labs. In this new lab, researchers from Maastricht University and Zuyd University of Applied Sciences will collaborate with healthcare providers, the Netherlands Comprehensive Cancer Organisation, medical IT service provider ilionx, and several Brightlands campuses and organisations.

The activities of the new lab span the entire process from the development to the deployment of artificial intelligence in healthcare. Among other topics, the lab focuses on preparing medical data so that it can be used anonymously for ‘training’ artificial intelligence. Other key activities of the ICAI Brightlands Smart Health Lab include the development of artificial intelligence and putting the technology into practice. The lab specifically focuses on artificial intelligence that can predict how a patient’s disease will develop. In this way, the technology can help map out treatment plans for diseases like cancer.

Ecosystem

Professor Andre Dekker, one of the lab’s academic directors alongside Dr. Rianne Fijten and Dr. Alberto Traverso, considers the collaboration between all parties as crucial for the success of their joint vision for the future. Dekker: “Bringing together knowledge and data from very diverse parties in the Brightlands ecosystem is precisely what allows us to conduct relevant research, develop real solutions and put these into practice.”

Responsibly connecting data

Dekker and his team bring their expertise in responsible sharing of privacy-sensitive medical data. The ICAI Brightlands Smart Health Lab thereby builds on their work on the Personal Health Train: a network that allows healthcare providers to learn from each other’s data, but in which data never leaves the host institution’s management and through which the privacy of patients is preserved.

Dr. Rianne Fijten: “Data is often an abstract concept for researchers, but it comes from real people. That is why careful handling of privacy-sensitive medical data is very important to us.”

Partners in the ICAI Brightlands Smart Health Lab

The ICAI Brightlands Smart Health Lab is a collaboration between Maastricht University, Zuyd University of Applied Sciences, Maastro Clinic, Maastricht UMC+, ilionx, Netherlands Comprehensive Cancer Organisation (IKNL), Brightlands Institute for Smart Society, Brightlands Smart Services Campus, Brightlands Maastricht Health Campus and AI Hub Brightlands.

Episode #13 with Laura Hollink

In aflevering #13 van Snoek op Zolder vertelt Laura Hollink van het Centrum voor Wiskunde en Informatica (CWI) en het Cultural AI Lab, over de ICAI samenwerking van CWI, TNO, de UvA en de VU, het KNAW Humanities Cluster, de Koninklijke Bibliotheek, het Nederlands Instituut voor Beeld en Geluid én het Rijksmuseum, over hoe BERTje het mkb kan helpen om ook met AI te starten, over white boxing the black box, over hoe AI interessant wordt gemaakt voor gebruik door geesteswetenschappers en over een eerlijk en onbevooroordeeld aanbevelingssysteem voor boeken die je kunt lenen.

Over Snoek op Zolder

Snoek op Zolder is de tweewekelijkse wetenschapspodcast van ICAI en de Nederlandse AI Coalitie (NL AIC). Hennie Huijgens duikt met een onderzoeker van een publieke of private organisatie in de wereld van kunstmatige intelligentie. Zijn belangrijkste vraag is ‘wat is de stand van zaken in AI onderzoek, en wat betekent dat voor mij en voor de samenleving?’

ICAI Interview: Improving patients’ vision and hearing with the help of AI

Umut Güçlü and Yağmur Güçlütürk run the Donders AI for Neurotech Lab together. With the help of machine learning techniques the lab tries to develop solutions that restore sensory and cognitive functions. These can be, for example, tools that improve hearing and vision, but they can also be solutions to help paralyzed people communicate or to suppress epilepsy. Güçlü and Güçlütürk: ‘We use an immensely high level of interdisciplinary exchange – with engineers, experimentalists, surgeons and ethicists – to achieve our goals.’

Umut Güçlü
Yağmur Güçlütürk

Donders AI for Neurotech Lab is a collaboration between the Donders Institute for Brain, Cognition and Behaviour, Radboud University, Phosphoenix, Advanced Bionics, Oneplanet Research Center and Abbott.

Dr. Umut Güçlü is lab manager of ICAI’s Donders AI for Neurotech Lab and is assistant professor of AI at Donders Institute for Brain, Cognition and Behaviour.

Dr. Yağmur Güçlütürk is lab manager of Donders AI for Neurotech Lab and is assistant professor of AI at Donders Institute for Brain, Cognition and Behaviour

First of all, what are your roles as lab managers?

‘Together, we are responsible for the day-to-day running of the lab. That is, we coordinate communication and research activities as well as supervising the Master students and the PhD candidates in the lab.’

The Donders AI for Neurotech Lab is working on an interesting combination: AI combined with neural implants. What kind of things is the lab working on now?

‘We develop machine learning methods for brain reading and brain writing technologies that restore cognitive and sensory function. We try to answer questions like: How can we use machine learning methods to optimally stimulate the brain via cortical implants? How can we improve the speech understanding of the users of cochlear implants? (Cochlear implants are small electronic devices that electrically convert sound into electric pulses to restore or improve someone’s hearing, red.) Another project revolves around the development of techniques for decoding and regulation of cognitive states like emotions, attention and stress.’

What are the opportunities and what are the challenges?

‘Tens of millions of people suffer from blindness and hundreds of millions of people suffer from deafness across the world. These losses can be devastating and greatly reduce one’s autonomy and quality of life. On top of that, large economic losses to society are accrued due to reduced workforce participation and burden of care. Thus far, however, previous implants have provided limited recovery of function. Hence, several crucial technological advances are required before effective, safe, permanent solutions are available to patients. Alleviating these challenges is our biggest opportunity.’

In what way can AI be used in neurotechnology?

‘AI has made huge leaps forward, allowing breakthroughs in object recognition, language processing, and even autonomous driving. With AI, a computer learns on its own from data, and develops an “answer” that can be used autonomously by a mechanical or electrical device. Here we use AI to improve the performance of brain-reading and brain-writing, enabling the automatic sensing of a signal in the outside world, or from a brain recording, that can then be directly fed to a neurostimulator for disorders of vision, movement, hearing, communication, and for the prevention of debilitating seizures. Our team is making use of the latest AI techniques in neural networks and probabilistic inference developed towards optimal signal detection, useful for the neurostimulation applications requiring rapid, and adaptive, brain-reading and brain-writing applications.’

And in what way is your lab’s approach different from other research?

‘I would say: the immensely high level of interdisciplinary exchange required to achieve our objectives. Given the scale and sophistication of our undertaking, we work together with different companies, knowledge institutes, patient organizations and an advisory board. For example, we closely collaborate with engineers who develop hardware, with experimentalists who use animal models, surgeons and physicians who perform clinical trials as well as with ethicists who keep societal implications in check.’

What kind of implants in this area are already being used by patients?

‘There are already hundreds of thousands of cochlear implant users in the world. While there is still room for breakthroughs, it is a mature technology in common use. In contrast, the technology readiness level of visual cortical implants is relatively low, having only been demonstrated as a proof-of-principle in recent studies with great leaps in the horizon. For example, one of our close collaborators Eduardo Fernández from the University Miguel Hernández in Spain recently demonstrated how an array of penetrating electrodes can produce a simple form of vision by conducting a series of experiments with a 58-year-old blind volunteer who has been blind for the last 16 years. The blind volunteer was implanted with 100 microelectrodes in the visual cortex of the brain and wore camera eyeglasses. A software was used to transform what the camera captures to how the electrodes stimulate the neurons in the brain. As a result, images comprising white points of light known as “phosphenes” were created directly in the mind of the volunteer who was able to identify lines, shapes and simple letters evoked by different patterns of stimulation.’

Interested to find out more about the research of this lab? On December 16, Donders AI for Neurotech Lab will talk about their state-of-the-art work during the lunch Meetup of ‘ICAI: The Labs’ on AI for Cognition in the Netherlands. Find out more and join!