Stefanos Kollias became a Professor of Machine Learning in the School of Computer Science at the University of Lincoln in 2016. He previously worked as a Professor in the School of Electrical and Computer Engineering at the National Technical University of Athens, and Director of the Intelligent Systems, Content & Interaction Laboratory, since 1997. He is also an IEEE Fellow (2015) and has been a member of the Executive Committee of the European Neural Network Society (2007-16).
Prof Kollias’ research interests include machine learning, intelligent systems & neural networks, multimedia analysis, affective computing, semantic metadata interoperability, digital libraries, IoT.
He has published 108 papers in international journals and 300 papers in proceedings of international conferences. There are 7500 citations to his work, with h-index 41 in Google Scholar. He has supervised more than 40 Ph.D. students. He and his group have participated in more than 100 European R&D projects, getting funding of more than €20M.
Vassilis Cutsuridis is a Lecturer at the School of Computer Science in University of Lincoln. After a detour through the software industry, he returned to academia in 2006, first as a Research Fellow at the University of Stirling, UK, then as a Visiting Scholar at the Center for Memory and the Brain, Boston University (USA), a Lecturer at King’s College London (UK) and a Research Scientist at FORTH (Greece).
His research interests lie at the interface between computer science and neuroscience broadly interested to reverse engineer how the brain and mind work in health and disease in order to understand the circuits and patterns of neural activity that give rise to mental experience and behavior in order to extract the brain algorithms and blue print designs to design and develop more efficient intelligent methods and systems for complex data analysis in Medical imaging, Robotics, Drug Discovery, Neuroscience.
He has published 40 journals papers and 30 refereed papers in conference proceedings and books. He has edited 5 books including the Hippocampal Microcircuits: A Computational Modeler’s Resource Book and the Perception-Action Cycle: Models, Architectures and Hardware. He acts as an Associate Editor in several international journals including Cognitive Computation and Frontiers in Cognitive Science.
Mingjun Zhong is a Lecturer in Computer Science (Machine Learning) in College of Science. Before coming to Lincoln, he was a Research Associate at the School of Informatics in the University of Edinburgh, working with Dr. Charles Sutton and Dr. Nigel Goddard on the EPSRC project “IDEAL: Intelligent Domestic Energy Advice Loop”. He was an Associate Professor in the Dalian University of Technology, China. Prior to this, he was a Research Assistant at the School of Computing in the University of Glasgow under the supervision of Professor Mark Girolami. Prior to this, he was a Postdoctoral Fellow at INRIA Rennes, France, working with Dr. Anatole LECUYER. He obtained his PhD in Applied Mathematics from the Department of Applied Mathematics in the Dalian University of Technology, China.
His research interests include machine learning, computational statistics, Bayesian inference, computational sustainability, nonintrusive appliance load monitoring (energy disaggregation), biomedical engineering, bioinformatics. He is interested in devising probabilistic and statistical methods for understanding the patterns and phenomena observed in real-world data. He likes to collaborate with scientists from various areas to understand their data.
Bowei Chen is a Lecturer in Data Science in the School of Computer Science at the University of Lincoln (UK), and a member of the Machine Learning Group. Prior to joining Lincoln, he received his PhD in Computer Science from the University College London, where he was with the Media Futures Group and the Centre for Doctoral Training in Financial Computing and Analytics. Dr. Chen’s research interests are broadly in the overlap among machine learning, data mining and business analytics. He is interested in developing intelligent algorithms and data solutions to three main themes: computational advertising (with the focus on programmatic guarantee and advertisement options), mathematical finance (with the focus on derivatives pricing and algorithmic trading) and management of information systems (with the focus on e-commerce business models design). He is a member of the editorial board of Electronic Commerce Research and Applications.
Georgios Leontidis is a Lecturer in Computer Science at the University of Lincoln. He is a member of the newly founded Machine Learning Research Group, carrying out research on the areas of data science, big data analytics, statistical modelling and machine learning. He received his PhD in computer science and medical informatics from the University of Lincoln for his novel research on early screening and diagnosis of diabetic retinopathy. Before joining the University of Lincoln, Georgios worked as a data scientist and project manager in IBA Dosimetry in Germany, creating solutions for predicting the outcome of the radiation treatment in cancer patients. Before that, he was a Marie Curie research fellow at the University of Lincoln. His research outcomes have been published in various international journals, conferences and book chapters, and has also been invited to give interviews in a radio station, a newspaper and various scientific magazines. Georgios has also appeared in the annual magazine of the University of Lincoln and he was an invited keynote speaker at the 16th annual conference of the British Association of Retinal Screening in 2016.
Miao Yu is a Lecturer at the School of Computer Science in University of Lincoln. He worked as a research associate for the research project “Signal Processing Solutions in a Networked Battlespace” (funded by the EPSRC) in the Aeronautical and Automotive Engineering Department, Loughborough University from 2013 to 2017. Prior to it, he obtained his PhD in the School of Electrical and Electronic Engineering, Loughborough University with the PhD thesis title— “Computer vision based techniques for fall detection with application towards assisted living”. Dr. Miao’s research interests lie in developing algorithms in statistical signal processing, image/video processing, machine learning and data/knowledge modelling, with applications in objects detection and tracking, behaviour recognitions and abnormal detection for healthcare.