Professor Silvester Czanner
Head of School
Biography
Prof. Silvester Czanner got his PhD in Mathematics from Comenius University in 1998. He habilitated and got his Docent (Reader) in Applied Informatics from Slovak University of Technology in 2024. He has travelled worldwide, teaching on three continents and working in academia and industry. He was part of world-leading research teams at some of the best HE institutions in the world (Harvard/MIT, Carnegie Mellon University). He has successful work experience in higher education: developing and delivering teaching, mentoring the young generation, and setting up and leading national and international teaching and learning programmes. During the last few years, he has focused more on higher management and administrative work in academia but still supervising research students and teaching regularly. He got his first external funding in 2000 while working at the University of Aizu in Japan. His experience securing funding from EU funders started in 2007 when he was awarded the prestigious Research Councils UK Academic Fellowship. Since 2007, as PI or Co-Investigator, has been awarded research grants from the IAS European Frontiers grant, Robert’s Fund, Reinvention Centre Collaboration fund, EPSRC, TLE Fund and H2020. He also received a travel grant from the Royal Academy of Engineering and training funds from the ERASMUS scheme for international faculty exchange. He successfully evaluated research grants and served on prioritisations panels for funding agencies, dealing with complex decision-making as an external reviewer/evaluator and panel member for international project reviews. Since 2013, he has been regularly appointed as an independent expert for the European Commission and project proposals evaluator for the Irish and Polish Governments. Silvester is the Head of the School of Computer and Engineering Sciences at the University of Chester. He provides leadership and line management to academic staff within a subject area (Computer Science, Engineering, Mathematics) with respect to all academic activities, including teaching, enterprise, and research. He is also holding several advisory appointments. He is the Chair of the University Internal Quality System Assessment Board at Pan-European University, Slovakia. He co-led the university accreditation process (Institutional Evaluation Programme (IEP)), which was conducted by the European University Association (EUA). He is also a member of the International Scientific-Technical Cooperation Council (ISTCC), the Slovak Research and Development Agency, the Ministry of Education, Slovakia and a member of the Slovak Accreditation Agency for Higher Education, an advisory body of the Government of the Slovak Republic. Silvester is a senior member of ACM, a senior fellow of HEA, a fellow of RSA and a former director and executive member of Eurographics UK.
Research and Knowledge Exchange
Prof. Silvester Czanner is a researcher and academic known for his contributions to computer science, applied mathematics, and biomedical engineering. His work primarily focuses on developing computational methods and algorithms that advance medical imaging and computer graphics. Silvester’s research bridges the gap between computational techniques and practical medical applications. His interdisciplinary approach contributes to medical diagnostics, treatment planning, and healthcare technology advancements. By integrating methods from computer graphics, machine learning, and computational geometry, his work aims to improve patient outcomes and support medical professionals with innovative tools. Medical Image Analysis Algorithm Development: Creating advanced algorithms for the processing and analysing medical images obtained from modalities such as MRI, CT scans, and ultrasound. Image Segmentation: Developing techniques to accurately segment and identify anatomical structures within medical images. Image Registration: Working on methods to align images from different modalities or time points to track changes or combine information. Computer Graphics and Visualization Realistic Rendering: Research methods to enhance the realism of computer-generated images, particularly for medical visualisation. Data Visualization: Developing tools and techniques to visualise complex biomedical data comprehensibly. Virtual Reality (VR) and Augmented Reality (AR): Exploring the use of VR and AR in medical training and simulation. Machine Learning and Artificial Intelligence in Medicine Predictive Modelling: Using machine learning algorithms to predict disease progression or treatment outcomes based on imaging data. Deep Learning: Implementing deep neural networks for tasks like image classification, segmentation, and anomaly detection. Data Mining: Extracting meaningful patterns from large biomedical datasets to support clinical decision-making. Interdisciplinary Applications Image-Guided Surgery: Developing technologies that provide surgeons with real-time imaging and navigation tools during procedures. Therapeutic Planning: Enhancing treatment planning for radiation or chemotherapy through precise modelling and visualization. Educational Tools: Creating interactive models and simulations for educational purposes in medical and biological sciences.