Dr. Ihor Smal
Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University
Kruytgebouw, room Z509
Padualaan 8, 3584 CH Utrecht
Ihor Smal studied physics and electrical engineering at Ivan Franko National University of Lviv, Ukraine (M.Sc. degree (cum laude) 1999), where he later worked as a research scientist (1999-2002), carrying out research in the field of nonlinear dynamical systems and chaos. From 2003 to 2005, he was a research assistant (postmaster program “Mathematics for Industry”) at the department of Mathematics and Computer Science of Eindhoven University of Technology, the Netherlands. In 2005 he graduated on the project “Design and implementation of a six camera scanning unit” and was awarded a Professional Doctorate in Engineering degree (PDEng). From 2005 to 2009 he was a PhD student at Biomedical Imaging Group Rotterdam (BIGR, Erasmus University/MC), the Netherlands, conducting research on motion registration and analysis in cellular and molecular bioimaging, defending the thesis entitled “Particle Filtering Methods for Subcellular Motion Analysis” (2009).
From February 2009 to 2018 he was a postdoctoral fellow at the Departments of Medical Informatics and Radiology of the Erasmus MC in Rotterdam, the Netherlands, conducting research on several topics defined by the personal grants (VENI, Erasmus MC Fellowship and NWO BBoL grant). From 2019 to 2020 he was an assistant professor at the department of Geoscience and Remote Sensing, TU Delft working on statistical and machine learning methods for optical and laser remote sensing. In 2020 he returned to the field of bioimaging as an assistant professor at the Erasmus MC, Biomedical Sciences Theme, working in collaboration with several research groups at the departments of Cell Biology and Molecular Genetics, developing methods for motion analysis and image understanding using modern statistical and AI methods. Since 2023, he is an assistant professor at Utrecht University, division of Cell Biology, Neurobiology and Biophysics, heading the lab on statistical image analysis, smart microscopy and explainable AI methods.
Our research focuses on combining statistical signal and image processing with advanced data modeling, with a particular focus on motion analysis in biological systems. The goal is to bridge the gap that exists between developing pure methodological advances in computer vision and machine learning and solving challenging real-world applications with high societal impact, which can benefit from using modern AI techniques. We strive to move from pure image processing and analysis to completely automated image/data understanding, based on machine learning and artificial intelligence. This will provide exciting new opportunities for the study and understanding of living systems.
We are part of the NWO IMAGINE! (“Innovative Microscopy and Guidance of cells In their Native Environment”) programme (Tech. Work Package 2) aiming at the development of high-precision control strategies that will enable automated real-time manipulation of key aspects of the biological systems. Our main focus is on development of novel solutions for real-time image processing and image analysis using explainable AI approaches that will be used for automated real-time optimization of imaging experiments, to control cellular architecture, migration and fate with light and provide feedback to the imaging systems to achieve automated guidance of biological processes.
You can find more information about our current activities and possible research projects on our webpage: www.smal.ws
For the most up-to-date list of publication click here