People - SAMP Group Members

Patrick E. McSharry received the BA in Theoretical Physics in 1993 and the MSc in Electronic and Electrical Engineering in 1995 from Trinity College Dublin. He was awarded a Marie Curie Research Fellowship in 1995 and received the DPhil in Mathematics from the University of Oxford in 1999. He is currently a Royal Academy of Engineering/EPSRC Research Fellow at the University of Oxford and his research interests include signal processing, systems biology, complex adaptive systems, operations research and forecasting.

Lucas J. Carbonaro graduated in Mathematics and received an ESRC award to pursue an MSc in Statistics at the London School of Economics. He was trained and employed, by the European Central Bank in Frankfurt am Main, both as a Consultant and Economist in the Division of Capital Markets. In Oxford he was Tutor at Queen's College and is currently involved as a research student at the Department of Statistics in the Computationally Intensive Statistics Research Group working both on volatility models and neural networks.

James Taylor's research interests relate to time series analysis and forecasting. More specifically, he is interested in prediction intervals, exponential smoothing, volatility forecasting, quantile regression, electricity demand forecasting and weather ensemble predictions. He has an undergraduate degree in Maths from Cambridge, an MSc in Operational Research from Lancaster University, and a PhD in Decision Science from London Business School. He taught at London Business School for three years before joining SBS in 1999. At Oxford, he teaches the core MBA course in Decision Science.

Oliver Gibson received the MEng in Engineering with Computing Science from Lincoln College, Oxford, and the MSc in Pattern Analysis and Neural Networks from Aston University, Birmingham. He is currently reading for a DPhil in the Signal Processing and Artificial Neural Networks Research Group at Oxford. His research is focused on the development of telemedicine systems for chronic diseases, such as diabetes, and algorithms for processing the data gathered by such systems to enhance patient care.

Gari Clifford received an MSc in Mathematics and Theoretical Physics from Southampton University, UK and a PhD in Neural Networks and Biomedical Engineering from Oxford. He has worked in industry on several FDA-approved medical devices. He is currently a Research Scientist in the Harvard-MIT Division of Health Sciences where he is the manager of an NIH-funded research program, and a major contributor to the Physionet Research Resource. He has taught at Oxford, MIT and Harvard and is currently an Instructor in Biomedical Engineering at MIT. His research interests include multidimensional biomedical signal processing, artifact and noise analysis, linear and nonlinear time series analysis, and mathematical modeling of the ECG and the cardiovascular system.

Edmund Crampin is Senior Lecturer at the Auckland Bioengineering Institute where he leads a research group in systems biology. Current research interests include mathematical modelling of metabolic, signalling and genetic networks, with a particular focus on computational modelling of cardiac myocytes. Edmund completed a DPhil in Applied Mathematics at Oxford. He was a Junior Research Fellow of Brasenose College, Oxford and was awarded a Research Fellowship from the Wellcome Trust to study mathematical models of heart disease. Edmund joined the University of Auckland as a Research Fellow in the Auckland Bioengineering Institute, and was subsequently appointed to a lectureship in the Department of Engineering Science.

Santiago Schnell is Assistant Professor at the Indiana University School of Informatics and Adjunct Assistant Professor of Biology and Physics, and Associate Director of the Biology Institute in the same university. He leads the systems biology research group in Informatics at Indiana University. He received his License in Biology and DPhil from Universidad Simón Bolívar and University of Oxford, respectively. He was a Junior Research Fellow of Christ Church, Oxford, and awarded a Research Fellowship from the Wellcome Trust at Oxford. He was a Research Fellow of the Venezuelan Academy of Medicine, a Senior Scholar in Science of Pembroke College and Lecturer in Applied Mathematics for Pembroke and Brasenose College. He is a founding member of the Bioethical Committee of the Venezuelan National Council of Science. He has an active research program in theoretical and mathematical biology.

David A. Clifton received a MEng in Engineering Mathematics and Computer Science from the University of Bristol, and is a DPhil candidate in Engineering Science at the University of Oxford. He is Senior Engineer at Oxford BioSignals, a spin-out company from Oxford's Signal Processing & Neural Networks Research Group, in which he is lead researcher responsible for the company's industrial research projects (including a large UK Government-funded DTI programme for intelligent signal analysis systems). His research interests and past experience are in the field of statistical pattern recognition for novelty detection in complex systems, previously applied to the monitoring of foetal heart-rates, patient vital-signs, industrial processes, automotive engines, and leading military/civil jet engines.

Peter R. Bannister received an MEng in Engineering and Computing Science from St. Anne's College, Oxford and a DPhil in Information Engineering from Green College, Oxford. As a graduate student, he was part of the team that developed the FSL suite of tools for functional brain image analysis. Since 2003 he has worked with Professor Lionel Tarassenko at Oxford as a member of the Signal Processing and Artificial Neural Networks Research Group where he carries out research into machine condition monitoring. He teaches Engineering Science at both undergraduate and postgraduate levels within the University, and works with Oxford BioSignals Ltd as a consultant. His research interests include pattern recognition techniques, machine learning, medical signal processing and computer vision.

Ada Lau's research interest is in volatility forecasting, wind power forecasting and stochastic optimization of wind power reserve. She received awards from the China Oxford Scholarship Fund and is currently reading for DPhil in Mathematics at the University of Oxford. She also received scholarships from the Oxford-Man Institute of Quantitative Finance and is a research member at the institute.

Zhang Jie received the Masters Degree from the school of information science and engineering of Shandong University in 2004, and the PhD from the electronic and information engineering department of Hong Kong Polytechnic University in 2007, where he is currently working. His research interests include nonlinear time series analysis, biomedical and neural signal processing, bioinformatics, complex systems and complex networks.

Michael Small received his Bachelor and Doctoral degrees from the University of Western Australia in Pure and Applied Mathematics (respectively) in 1994 and 1998. He has held research positions in Finance, Physics and Physiology while working for banks, hospitals and universities. He completed Postdoctoral Fellowships in Theoretical Physics at Heriot-Watt University (Edinburgh) and in Electronic and Information Engineering at Hong Kong Polytechnic University. He is currently an Associate Professor in the department of Electronic and Information Engineering at Hong Kong Polytechnic where he teaches Biomedical Engineering and Signal Processing. His research interests include nonlinear time series, complex systems and chaotic dynamics. His work focuses on the application of these methods to various biomedical systems include neurophysiology, cardiovascular dynamics and epidemiology.

Athanasios Tsanas received the BSc in Medical Instruments Technology in 2005, the BEng in Electrical Engineering and Electronics in 2007 and the MSc in Communications and Signal Processing in 2008 from the Technological Educational Institute of Athens, the University of Liverpool and the Newcastle University, respectively. He is currently reading for the DPhil in Biomedical Engineering, focusing on the modelling of speech and the extraction of useful clinical information for the detection of neurological disorders. His research interests include modelling complex physiological systems, in particular the cardiovascular system with a view to mechanical circulatory support devices.

Paul Moore holds a BSc in Electrical and Electronic Engineering from Bath University, an MSc in Computer Science from Brunel University and an MPhil in Computer Speech, Text and Internet Technology from Cambridge University. He held student internships with Plessey Research and IBM. After his bachelors degree, he worked on geometric modelling and human-computer interfaces for CAD systems with the Brunel CAE research group. He has since worked in the software industry, coding device drivers and writing software for communications, environmental and medical applications. He is currently reading for a DPhil in nonlinear speech signal processing, and his research interests include speech recognition, speech signal processing and machine learning for grapheme to phoneme conversion.