Stiliyan N. Kalitzin
Stiliyan N. Kalitzin (Bulgarian: Стилиян Калицин) is a theoretical physicist whose work spans computational neuroscience, image analysis, and epileptic seizure detection. Since 2000, he has been Head of the Medical Technology Department at the Dutch Epilepsy Clinics Foundation (Stichting Epilepsie Instellingen Nederland, SEIN). He is also affiliated as external faculty with the Image Sciences Institute at the University Medical Centre Utrecht and supervises PhD students in medical physics, biomedical engineering, and clinical engineering.
Kalitzin began his research career while still a student of theoretical atomic physics at Sofia University, publishing his first research article, which examined the extension of Einstein space classifications to N=1 supergravity. He later continued work on supersymmetry unified models at University of Utrecht and conducted research on biological neural network models of human vision at Amsterdam University Medical Center. His work on invertible orientation representations for two-dimensional image analysis was subsequently adopted in image processing and computer vision and influenced the development of three-dimensional orientation score methods.
At SEIN and affiliated centers, Kalitzin’s work focuses on computational approaches to normal and epileptic brain activity, including image and signal processing and closed-loop seizure control. His contributions include automated video-based detection of nocturnal convulsive seizures and the development of adaptive remote sensing paradigms for real-time alerting of convulsive epileptic seizures. In collaboration with Sergey Karpuzov and Georgi Petkov, his more recent work has focused on optical flow–based video analysis for real-time awareness of hazardous events, with applications in the automated detection of epileptic seizures, falls, and respiratory disturbances.
Kalitzin is the author of more than 100 publications in international journals, book chapters, and conference proceedings. He received a 1997 SNN/STW research grant for work on neural-network-based scale-space grouping in image analysis and, in 2010, a TOP grant from the ZonMw for the development of a multimodal seizure-detection instrument.