Martin is currently a (part-time) Professor of Computational Neuroscience and Cognitive Robotics in the Department of Computing and Technology at Nottingham Trent University. He leads the Computational Neuroscience and Cognitive Robotics research group at NTU.
Martin joined NTU as Dean of the School of Science and Technology in March 2014. In August 2016, he became Pro Vice-Chancellor for Student Affairs and Head of the College of Science and Technology. Formerly, he was Director of the Intelligent Systems Research Centre, Acting Associate Dean of the Faculty of Computing and Engineering and Head of the School of Computing and Intelligent Systems at Ulster University.
He was also a Director of the Ulster University’s technology transfer company, Innovation Ulster, and a spin out company Flex Language Services. He was awarded both a Senior Distinguished Research Fellowship and a Distinguished Learning Support Fellowship from Ulster University in recognition of his contribution to research and teaching. Martin is a Fellow of the IET, SMIEEE and a Chartered Engineer.
He retired from his post as PvC and Head of College in January 2018.
Martin is an active researcher. His current research interests are focused on computational intelligence, and in particular on computational systems, which explore and model biological signal processing, specifically in relation to cognitive robotics and computational neuroscience. His work addresses the creation of computational models of neural processing of visual, auditory or tactile stimuli, and the creation of artificial intelligent systems to emulate such sensory processes, with implementations in both software and reprogrammable hardware. His work on cognitive robotics addresses the issues of autonomous learning and skill building in mobile robotics.
He is the author or co-author of over 300 research papers and has attracted approximately £25 million to support his research, from a wide variety of funding sources. He also has a strong interest in innovations in teaching and learning and has attracted substantial funding to support implementation of technology assisted learning in higher education.
Opportunities to carry out postgraduate research towards an MPhil/PhD exist and further information may be obtained from the NTU Doctoral School.
Professor McGinnity is a former grant holder on a number of national, international and EU projects. He is a regular reviewer for national and international research funding organisations and contributes strongly to the research community.
Martin has collaborated on research projects with colleagues from a wide range of countries and organisations:
- University of Zurich
- ITT Genoa
- Verilog (France)
- Etnoteam (Italy)
- Tasking Software (Netherlands)
- Joanneum Research (Austria)
- Sintef (Norway)
- IMMS (Germany)
- National University of Ireland (Maynooth)
- Philips Semiconductors (Germany)
- Philips Consumer Electronics (Netherlands)
- Aisling Microsystems (Ireland)
- IXL Laboratory (France)
- CNRS (France)
- University of Heidelberg (Germany)
- Trinity College (Ireland)
- University of Cambridge (UK)
- Cavendish Laboratory (UK)
- Max Planck Institute (Germany)
- University of Duisburg (Germany)
- Technical University Braunschweig (Germany)
- Tyndall Institute (NMRC) Cork (Ireland)
- UCD (Ireland)
- IIT Kanpur (India)
- IIT Rajasthan (India)
- Duke University (USA)
- Florida Atlantic University (USA)
Sponsors and collaborators
Martin’s research funding has included support from the European Union (13 grants) and local industry, as well as:
- UK Engineering and Physical Sciences Research Council
- N.I. Industrial Research and Development Unit
- UK Dept. Trade and Industry
- Leverhulme Trust
- NI Dept. Education and Learning
- major industry (Citi, Fidessa, First Derivatives, Singularity, NYSE Technologies)
- Udaras na Gaeltachta
- N.I. Foresight Programme
- Science Research Infrastructure Fund 2
- Science Research Infrastructure Fund 3
- HEA North South Collaborative Research Programme
- N.I. Dept. Enterprise
- Trade and Investment
- EU Interreg
- Derry City Council
- Enterprise Ireland
- Intertrade Ireland
- ILEX Urban Regeneration (Derry)
- Kerr D., Coleman S.A, McGinnity T.M., (2018) Biologically Inspired Intensity and Depth Image Edge Extraction, IEEE Transactions on Neural Networks and Learning Systems 2018
- Kerr, Emmett, McGinnity, T.M. and Coleman, SA (2017) Material Recognition using Tactile Sensing. Expert Systems with Applications
- Gerlein, Eduardo, McGinnity, TM, Belatreche, Ammar and Coleman, Sonya (2017) Network on Chip Architecture for Multi-agent Systems in FPGA. Accepted for ACM Transactions on Reconfigurable Technology and Systems
- Herman, P.H., Prasad, Girijesh and McGinnity, TM (2017) Designing an Interval Type-2 Fuzzy Logic System for Handling Uncertainty Effects in Brain-Computer Interface Classification of Motor Imagery Induced EEG Patterns. IEEE Transactions on Fuzzy Systems 25 (1). pp. 29-42
- Jing, Min, Bryan, Scotney, Coleman, SA and McGinnity, T. Martin (2017) Novel "Squiral" (Square Spiral) Architecture for Fast Image Processing. Journal of Visual Communication and Image Representation, 49. pp. 371-381
- Joshi, Alok, Youssofzadeh, Vahab, Vemana, Vinith, McGinnity, TM, Prasad, Girijesh and Wong-Lin, KongFatt (2017) An Integrated Modelling Framework for Neural Circuits with Multiple Neuromodulators. Journal of The Royal Society, Interface, 14 (126)
- Shynkevich, Yauheniya, McGinnity, T.Martin, Coleman, Sonya, Belatreche, Ammar and Li, Yuhua (2017) Forecasting Price Movements using Technical Indicators: Investigating the Impact of Varying Input Window Length. Neurocomputing, 264 . pp. 71-88
- Vance, Philip, Das, Gautham, Kerr, Dermot, Coleman, Sonya, McGinnity, T.Martin, Gollisch, Tim and Liu, Jian (2017) Bio-Inspired Approach to Modelling Retinal Ganglion Cells using System Identification Techniques. IEEE Transactions on Neural Networks and Learning Systems
- Yang, Shufan, Wong-Lin, KongFatt, Andrew, James, Mak, Terrence and McGinnity, TM (2017) A neuro-inspired visual tracking method based on programmable system-on-chip platform. Neural Computing and Applications
- Wang, J., Belatreche, A., Maguire, L.P., McGinnity, T.M., (2015) SpikeTemp: An enhanced rank-order based learning approach for Spiking Neural Networks with Adaptive Structure, IEEE Transactions on Neural Networks and Learning Systems