Research Group
Michal Sandanus is a Research Engineer specializing in artificial intelligence and machine learning, with a focus on computer vision, time series analysis, and multimodal data processing. His work centers on developing AI-driven solutions for real-world scientific, environmental, and industrial challenges. As a member of the Green and Secure Environment team, he contributes to research projects in areas such as renewable energy forecasting, environmental monitoring, groundwater pollution modeling, and landslide detection, collaborating closely with domain experts to translate research outcomes into practical applications.
Prior to joining KInIT, Michal gained extensive experience in the healthcare and diagnostics sector, where he developed deep learning methods for medical image analysis, including image segmentation and classification. His research interests span medical imaging, signal processing, and applied machine learning, with a strong emphasis on creating robust models that can be deployed in real-world settings. He also works on machine learning approaches for spectroscopy data analysis, supporting substance identification and classification in analytical chemistry applications.
Michal holds a Master’s degree in Machine Learning from the Faculty of Information Technology at Brno University of Technology, where he graduated in 2023. His master’s thesis, focused on automatic meibomian gland and eyelid segmentation from static images and video sequences, received the Dean’s Prize and resulted in technology that continues to support clinical practice in ophthalmology. He earned his Bachelor’s degree from the Faculty of Informatics and Information Technologies at the Slovak University of Technology, where his thesis explored machine learning methods for classifying volumetric medical imaging and spectroscopy data to differentiate high-grade brain tumors.
