T.M. McGinnity
University of Ulster, Nottingham Trent University, Intel (United States)
Papers
55
Total Citations
1,474
H-Index
18
About
T.M. McGinnity is a prominent researcher whose work spans neuromorphic computing, brain-computer interfaces, robotics, and trustworthy autonomous systems. His 2019 review of learning in biologically plausible spiking neural networks, with over 416 citations, stands as a landmark contribution to the field, providing researchers with a comprehensive framework for understanding how brain-inspired computing can advance artificial intelligence. McGinnity has made significant strides in brain-computer interface technology, developing adaptive systems that enable EEG-based control of mobile robots and assistive devices—a breakthrough with meaningful implications for individuals with motor impairments. His work on multi-robot systems in healthcare settings and robotic smart home ecologies demonstrates a commitment to translating cutting-edge research into socially beneficial applications. More recently, McGinnity has emerged as a leading voice on human-centered AI and trustworthy robots and autonomous systems, systematically defining the properties that make autonomous technologies safe, reliable, and ethically deployable. His contributions to tactile sensing and dexterous robot manipulation further illustrate the breadth of his impact. Collectively, his research, accumulating over 1,000 citations, reflects a career dedicated to building intelligent systems that are both technically sophisticated and genuinely human-centered.
Research Focus
Key Achievements
Top Papers
- 1A review of learning in biologically plausible spiking neural networks416 citations · 2019
- 2EEG-Based Mobile Robot Control Through an Adaptive Brain–Robot Interface108 citations · 2014
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- 6Material recognition using tactile sensing66 citations · 2017
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- 8Robotic Ubiquitous Cognitive Ecology for Smart Homes35 citations · 2015
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