Prof. Dr. Ir. Fons J. Verbeek
Imaging & Bioinformatics, LIACS, Leiden University
- f.j.verbeek@liacs.leidenuniv.nl
Prof. Dr. Fons Verbeek
Prof. dr. Fons Verbeek has a background in Computer Science and Biology; he has a PhD in Applied Physics. His research topic is Image Analysis with a focus on microscopy imaging. His research stretches from feature extraction and segmentation to classification strategies in the domain of the life-sciences.
Visualization of research data is much addressed in his research projects. In the master program he teaches a course on Image Processing and Analysis. In additon, in his research he is using modelling techniques applied to biomedical data to gain further understanding on cohesion in biomolecular processes.
Imaging & Visualization typically require Human interaction. Therefore, in research project the subject of Human Computer Interaction is often addressed. In the Media Technology programme and the CS bachelor he is involved in teaching the Human Computer Interaction course and engaged in supervising students in their research.
For more information check the research group website of Imaging & BioInformatics for projects at the Leiden Institute of Advanced Computer Science he works on.
See for more information my Personal website
Research
Computers are becoming ever more powerful and are taking on more complex tasks. The Leiden Institute of Advanced Computer Science (LIACS) contributes to revolutionary scientific research and applies the latest inventions in the field, offering answers to today’s questions of society.
Improve computer systems
With our research, we make computer systems faster and more efficient. Due to our improved algorithms and software, computers can compute faster and recognise patterns in large digital files at an earlier stage.
Applied and fundamental
We are keen to work on socially and industrially relevant questions. Behind the solutions for socially relevant questions, there are often deep theoretical discoveries, with a strong basis in statistics. In other words, we solve both fundamental and applied problems. This means that our research contributes to developments in every aspect of the field. It broadens our own conceptual world and that of other researchers.
Our research fields
With one another and together with others, we focus on eight research fields.
Artificial intelligence and machine learning
- [A]Social Creatures Lab
- Automated Design and Analysis of Algorithms (ADA group)
- Multicriteria Optimization and Decision Analysis (MODA group)
- Natural computing (NACO group)
- Reinforcement Learning lab
Data Science
- Computational Network Science Lab (CNS Lab)
- Data Mining and Sports
- Explainatory Data Analysis
- Health Data Science
- Text Mining and Retrieval
Media & interaction
Programming education
Science based business (SBB)
Systems and security
- Cyber Security Lab
- High performance computing
- Large-scale Computing Infrastructure
- Leiden Embedded & Real-time Computing (LERC)
Theory
- Algorithms
- Bio-inspired computing
- Concurrent Systems
- Quantum Lab
- Systems Modelling Lab (SML)
- System Verification Lab (SVL)
Vision and imaging
Vision and imaging
On the basis of the characteristic aspects of a picture, certain computers can tell us what the picture is showing. They can learn this in the same way that young children are able to learn to recognize images. Further improving these techniques opens the way to a whole range of new applications. Biology and (bio) medical sciences offer numerous applications for computer science. We are pleased to work alongside biologists and medical scientists in identifying smart solutions for medical applications. Now and in the future, computers will be decisive in fighting a whole raft of diseases.
Bio-informatics
The bio-informatics lab aims at strengthening biological, medical, behavioral research with innovative computational, mathematical and artificial intelligence technologies. The research of the bioinformatics group focuses on research methods and workflows for analyzing, modelling and semantically integrating biomedical data. They are involved in multiple initiatives to develop multiple initiatives to develop methods and infrastructure for FAIR (Findable, Accessible, Interoperable and Reusable) data, in order to increase the value of research results and to address the growing analysis bottleneck. Another research area of the group is in biopolymer sequence analysis, which focuses on bioinformatics identification of functional structures in non-coding RNAs and viral RNA genomes. This work is done in close collaboration with wet bench research laboratories.
Deep learning and computer vision
The goal of the LIACS Media Lab (LML) at Leiden University is to conduct state-of-the-art research in the areas of deep learning, artificial intelligence and computer vision. Their research spans the dominant kinds of media information which are images, video, audio and text, or "multimedia". One of the most ubiquitous society problems is how to browse and search the vast mountain of multimedia information from diverse sources such as smartphones, digital libraries, cultural heritage collections and the Internet. Even though acquiring the multimedia information is straightforward, there currently are no effective solutions for finding multimedia information using everyday common queries. The group has an emphasis on using deep learning and computer vision methods to classify images into human-understandable text and involves using the content such as pixels in images and advanced artificial intelligence and deep neural network algorithms to determine who or what is in the image.
Imaging
The imaging group focuses on bio-imaging, image analysis and visualization. With their experience in high-throughput imaging, 3D reconstruction, cell tracking and pattern recognition, the group intends to find the relation between the information analyzed from image and other bio-molecular information resources. Furthermore, they develop new algorithms and techniques for producing images using the very latest equipment. These help create clearer three-dimensional pictures of organs and – on a scale of thousands of times smaller – body cells. These applications facilitate functional study, disease modeling and drug screening in the bio-medical field.