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Professor Bogdan Matuszewski

Professor of Computer Vision, Head of Computer Vision and Machine Learning (CVML) Research Group and Deputy Director of Research Centre in Engineering
School of Engineering

Bogdan heads Computer Vision and Machine Learning (CVML) Research Group and is deputy director of Research Centre in Engineering. He has an extensive network of collaborators in academia, industry and healthcare sectors. He participated in 24 projects, leading 11 of them, and secured in excess of £2.5M in direct research funding. His main research area is in computer vison and machine learning. He produced more than 150 publications and won several awards for his research.

Professor Matuszewski is research active within the areas of digital engineering, computing and healthcare technology. He heads the Computer Vision and Machine Learning (CVML) Research Group, the Robotics and Computer Vision Laboratory and chairs the University 3D Imaging Working Group. He is deputy director of the UCLan Research Centre in Engineering. He is a member of the UCLan THRIVE Research Centre, leading the Building Blocks of Wellbeing (psychology, bioscience, bioimaging) Group. He is also active in the Applied Digital Signal and Image Processing (ADSIP) Research Centre and the Advanced Digital Manufacturing Technology (ADMT) Research Centre. He has been instrumental in developing an MSc course in Applied Data Science, where he teaches Artificial Intelligence and Machine Learning module.
He has active collaborative links with industry and a number of hospitals and universities across Europe. On his current project, funded by the Science and Technology Facilities Council (STFC) Cancer Diagnosis Network+, he is developing an automated system for decision support in colonoscopy. As project principal investigator he collaborates with both national and international partners including, East Lancashire NHS Hospitals Trust (ELHT), STFC DiRAC Supercomputer Facility, ENSEA’s ETIS Cergy-Pontoise and Sorbonne Universities.

Professor Matuszewski is a member of the Institute of Electrical and Electronics Engineers (IEEE), the British Machine Vision Association (BMVA), and the Medical Image Computing and Computer Assisted Intervention Society (MICCAI). He has published over 150 research papers in different areas of computer vision and medical image processing and supervised 16 PhDs to successful completion. He has been a work package leader for the FP7 funded “SEMEiotic Oriented Technology for Individual’s CardiOmetabolic risk self-assessmeNt and Self-monitoring (SEMEOTICONS)” project. He was principal investigator for the EPSRC funded ECSON (EP/F013698/1), MEGURATH (EP/D077540/1) and TeRaFS (EP/H024913/1) projects. He has participated in 24 EU, Research Council, and industry funded research projects, including PIMHAI, INDeT, INDUCE, SPACERANE, JERI and DIAPS. He has led 11 of these projects. He has been a member of organising and reviewing committees for a number of conferences including: ICIP, SMC, FG, VISSAP, EST, MedViz, and GAMI. He organized/chaired 15 conference sessions including 6 at IEEE conferences: SPSympo’2019, ViMaBi’2019, IPTA’2019, IUCC’2015, ICIP’2014, SMC’2013, CYBCONF’2013, SMC’2012, ICIP’2011.
His PhD was in the area of inverse problems, since then his research interests have included: industrial and medical computer vision; use of Bayesian methodology for modelling, tracking and pattern recognition; and deformable models and their applications to data registration and segmentation. His most recent research projects include, deep learning, diffeomorphic image registration, level set segmentation incorporating prior shape and topology information, non-rigid structure from motion, and 3D dimensional data acquisition and analysis with emphasis on face analysis.