Artificial Intelligence

Artificial Intelligence (AI) represents a next wave in the digital revolution. Already AI is changing the way we

live and work and has great potential for society’s grand challenges. At the same time, developing and integrating AI in a responsible way is not easy. Human-centeredness, value sensitivity and excellence across all AI aspects should pave the way towards augmented intelligence. Such AI is transparent, explainable, fair, socially compatible, and is developed and deployed based on careful consideration of the disruptions AI technology can cause. This track aims to provide a showcase and forum for connecting Dutch research on this theme.

The focal point of the parallel and poster sessions is the presentation of the work of young researchers. Preference will be given to abstracts by postdocs and PhD candidates.

Track chairs:
Charlotte Gerritsen (VU)
Stefan Leijnen (Hogeschool Utrecht)

Track committee:
Maurice Peemen - Thermo Fisher Scientific
Arlette van Wissen - Philips
Judith Masthoff - UU
Martijn Zoet - Zuyd University of Applied Science
Remko Helms - Open Universiteit

Track programme

  Wednesday 10 February

10.40 - 11.55

AI Foundations

Invited speaker Martijn Zoet - Artificially intelligence for everyone
 - abstract and bio below -

Saba Amiri - Compressive Differentially-Private Federated Learning Through Quantization

Matthijs Jansen - A Scalable Benchmarking Infrastructure for Distributed Deep Learning

14.00 - 14.45

Visual AI

Meike Nauta - Neural Prototype Trees for Interpretable Image Recognition

Richard Schoonhoven - Pruning and Tuning Computational Imaging Pipelines

Maruf A. Dhali - Artificial neural networks analyzing Dead Sea Scrolls

  Thursday 11 February

10.40 - 11.55

Social AI

Invited speaker Judith Masthoff - Artificial Intelligence for Emotional Wellbeing
- abstract and bio below -

Ilir Kola - Towards Social Situation Awareness in Support Agents

Laura van der Lubbe - Persuasive system with gamification to improve diet complience

14.00 - 14.45

AI & Health

Anusha Aswath - Detection of mitochondria in large electron microscopy images

Yoni Schirris - Predicting genomic defects from gigapixel tumor tissue images

Andreas Panteli - Soft margin loss for unlabelled regions

Invited Speakers

Bio Martijn Zoet
Martijn Zoet is a professor (lector) at Zuyd University of Applied
Science in Sittard and holds the chair for the Future Proof Financial.
He obtained his PhD from Utrecht University and was a researcher
at HU university of applied science Utrecht from 2010 to 2014
before joining Zuyd University of Applied Science. In addition,
Martijn is the managing partner of the EDM Competence Centre
that he founded in October 2015. EDM-CC supports corporations,
governments, and institutions to map their data, decision
management, and machine learning challenges and find solutions
to these challenges. His research focus is on business
rules management, decision management, decision mining,
process mining, data mining, machine learning and, FinTech.

Abstract: Artificially intelligence for everyone

The development of Generative Adversarial Networks, AlphaGoZero and GPT-3 are all important advances in the field of artificial intelligence. However, which percentages of organizations apply any of the previously mentioned techniques? And are the techniques used to drive business strategy? The answer to the first question is that only a very small part of organizations applies one or more of these techniques. And even a smaller part of organizations applies them to drive business strategy. Still, these breakthroughs provide a temptation to mainly focus on the development of a strategy for AI rather than a strategy with AI. While both are needed to drive the development of AI as well as the adoption by organizations. The same applies to AI research and AI Education were a temptation exists to mainly focus on the development of fundamental techniques, principles, and ethics for AI rather than techniques, principles, and ethics that work with AI. How can AI capabilities be delivered to, or even build by, first year students not enrolled in a  Data Science, Statistics or Information Technology study? The presentation will discuss the challenges and shifts of focus needed to scale and strengthen applicable AI research. In addition the presentation will also touch on the ‘risky’ subject of automatizing different research capabilities such that research on and with AI can get an additional boost. 

Bio Judith Masthoff
Professor Judith Masthoff is a chair in Interaction Technology at Utrecht University and an honorary chair in Computing Science at the University of Aberdeen. Her research focusses on personalization: how artificial intelligence systems can automatically adapt to humans. She has applied this in a broad range of areas including recommender systems, intelligent user interfaces, intelligent tutoring systems, persuasive technology, and affective computing. She is Editor in Chief of the User Modeling and User-Adapted Interaction journal and a director of User Modeling Inc., the professional association of user modeling researchers.

Abstract: Artificial Intelligence for Emotional Wellbeing

Researchers claim that we are facing a global loneliness epidemic, and that mental illness, anxiety disorders, stress and burnout are on the rise. This talk is about how adaptive AI systems can actively improve emotional wellbeing. We will discuss different ways of doing so, the work already done, the challenges faced, and our vision of a new kind of personalized systems. First, systems can provide emotional support, adapted to the recipient's characteristics such as their personality, affective state, cultural background, and stressors experienced. Second, systems can aid humans to provide emotional support, so mediating emotional support, adapting to both the support giver and recipient. Third, systems can support and motivate people to adopt behaviours that improve their wellbeing and that of others. Fourth, systems can team people up, deciding who are the best placed to provide support and motivation. Finally, systems can improve the wellbeing of groups and not just individuals, monitoring group wellbeing, encouraging and supporting effective group behaviours, and building group identity and cohesion.

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