Erasmus MC

Society for Quantitative Artificial Intelligence Research


Erasmus MC SQuAIRe Aims

Create  an AI community

To foster ties that promote the free exchange of knowledge within the community among experts in AI, non-experts, clinicians, and biologists who utilize ML techniques at all levels of academic careers.

AI research

To consolidate AI and ML expertise within Erasmus MC by sharing cutting-edge technological advances.


To provide tutorials on the elucidation of ML & AI fundamentals and good practices

Vision of Erasmus MC squAIre

The AI, Data Science and Big Data age has accelerated the rate of innovation so quickly that most researchers simply can’t keep up. Meanwhile we are contending with an ever-increasing demand for AI applications in healthcare and biomedical research, while there is a shortage of experts.

As artificial intelligence (AI) applications become increasingly widespread and frontier science in machine learning (ML) rapidly evolves, our best chance to accurately and efficiently leverage these tools lies in building a strong and vibrant community that shares knowledge and resources with each other.

Preempting our organization's upcoming efforts to converge forces with TU Delft and Erasmus University Rotterdam, here we build a ground-up Erasmus MC-wide community to consolidate expertise in clinically and biologically relevant artificial intelligence (AI) and machine learning (ML)research within our institute while at the same time increasing awareness for the science and engineering behind AI and ML.

Health care is facing enormous challenges given the ageing of the population. The coming years, an increasing number of people will need care and less people will be available to provide that care. Additionally, the costs of health care will increase substantially. Big data, generated in research and in daily clinical practice, the accessibility of these data, and exploring them by AI/ML is essential to address these challenges. By doing so, we will get a better understanding of biology and disease, and we will have better prognostic and predictive models. This will enable us to provide more individualized and more efficient approaches to help individual patients and the population, which will contribute to the sustainability of health care.
Stefan Sleijfer
Dean, Erasmus MC

The impact of quantitative AI research will initially feed our wildest imaginations and then go beyond it, generating imaginations of its own that we may not even comprehend.
Chris de Zeeuw
Chair, Department of Neuroscience, Erasmus MC

Expertise and knowledge on AI and big data are rather scattered over multiple clinical and research departments. To really contributed as Erasmus MC to the development and implementation of AI-tools, more coordinated efforts are needed. Bringing people together for exchange and sharing information is a first important step
Aad van der Lugt
Chair, Department of Radiology and Nuclear Medicine, Erasmus MC

AI has started to reshape healthcare and translate in valuable applications for clinicians and basic researchers, for example discovering links between genetic information. So, AI as transforming technology comes with risks, and ethical and societal impacts we are aware of, but also must be developed specifically for basic research, where the return will rather be long-term and AI's full potential will require a long-term vision. The latter fits perfectly with future basic research of the highest caliber that is already establishing massive data sets at Erasmus MC.
Danny Huylebroeck
Chair, Department of Cell Biology, Erasmus MC

AI will be of great help with the challenges that we face in our health care system. As a clinician, I look forward to contribute to the implementation of AI into patient care.  I am convinced it will help us improve care for our patients, but different skills and education will be required. For this reason it is important that Erasmus MC, with its strong Convergence policy, is taking a leading role.
Robin Peeters
Chair, Department of Internal Medicine, Erasmus MC

Supported by


Erasmus mc, the netherlands

Wiro Niessen

October 10, 2022
17:00 - 18:00
Collegezaal 1
Borrel: 18:00 onwards
Opening (video)

"How big data and AI facilitate precision medicine"(video)


Guangyu Robert Yang

November 8, 2022
Collegezaal 1
Borrel: 18:00 onwards
"insights from AI in modeling complex biological systems" (video)

Erasmus mc, the netherlands

Devika Narain

"Dimensionality reduction algorithms"
December 6, 2022
Collegezaal 1
Borrel: 18:00 onwards

erasmus mc, the netherlands

Gennady Roshchupkin

"All you need to know about AI and Machine Learning" (video)
January 26, 2023
Collegezaal 1
Borrel: 17:30 onwards
In collaboration with
Smart Health Tech Center (SHTC)

erasmus mc, the netherlands

Ihor Smal

"Redefining Computational Biology by the means of AI"
February 28, 2023
Collegezaal 2
Borrel: 18:00 onwards

Event open for everyone

Radboud University, the netherlands

Marcel van Gerven

" AI for Neurotechnology" (video)
March 21, 2023
Collegezaal 2
Borrel: 18:00 onwards

QUANTIB BV, the netherlands

Valerio Fortunati

"Bringing AI to Clinical Devices:
Challenges and Achievements"
April 18, 2023
Collegezaal 2
Borrel: 18:00 onwards

Delft University of Technology, the netherlands

Jeroen van den Hoven

"The Quest for Responsible AI"
May 23, 2023
Borrel: 18:00 onwards

Meta AI, USA

Laurens van der Maaten

"Visualizing Data using t-SNE Embeddings"
June 27, 2023
Collegezaal 1
Borrel onwards

Our Team

Dr. Devika Narain
Associate Professor
Department of Neuroscience
Erasmus MC

Dr. Ihor Smal
Assistant Professor
Department of Molecular Genetics
Department of Cell Biology
Erasmus MC

Dr. Gennady Roshchupkin
Assistant Professor
Department of Radiology and Nuclear Medicine
Department of Epidemiology
Erasmus MC

Ready to get started?

Join us