International Conference on Gerontechnology 2024

Collaborating for the Future of Gerontechnology

Speakers

inner-banner-4
Roy
Prof. VELLAISAMY Arul Lenus Roy
Chair Professor of Intelligent Systems
School of Science and Technology
Hong Kong Metropolitan University
Hong Kong
Profile

Prof. Roy Vellaisamy is a Chair Professor of Intelligent Systems and leader of Molecular Electronics (MOLEC) group at the Hong Kong Metropolitan University (HKMU). Prior to HKMU, he was a Professor of Intelligent Systems at the University of Glasgow (UK) where he is currently a Professor affiliate. In Hong Kong, he held faculty positions at City University of Hong Kong for 11 years (2008 to 2019; Assistant & Associate Professor) and The University of Hong Kong (2004 to 2008; Research Assistant Professor). In 2019, he received gold medals for his “Sensor Platform” at the 47th International Exhibition of Inventions (Geneva); iCAN 2022 (Toronto, Canada); He was also a recipient of TRIL-Research Fellow awarded by The International Centre for Theoretical Physics (ICTP, UNESCO institution), Trieste (Italy), Excellent Product Award (2011, 12, 13 & 18) at China Hi-Tech Fair awarded by the PRC's Ministry of Commerce and secured “1000 talent plan” of Zhejiang province (2017). Together with his graduate students, Roy as a founding member, established several spin-off companies in HK and UK for the development of point of care diagnostic tools. Roy works closely with industries in UK and Greater Bay Region for the development of intelligent sensors and quantum technologies.

Abstract

Neuromorphic Systems for Gerontechnology

 

Neuromorphic artificial intelligence systems are the future of ultrahigh performance computing  clusters to overcome complex scientific and economical challenges. To elucidate  biomimicking mammalian brain synapses, we introduce a new class of Topological  Neuristors (TN) with ultralow energy consumption (pJ) and higher switching speed (µs).  Bioinspired neural network characteristics of TNs are the effects of surface state properties of topological insulator (TI) materials. With augmented device  and TI material design, we demonstrate top notch neuromorphic behaviour with effective  learning-relearning-forgetting stages. In addition, we demonstrate excellent efficacy in treating cognitive neural dysfunctions through modulated neuromorphic stimuli. As a proof of concept, we demonstrate real-time neuromodulation of electroencephalogram (EEG) deduced distorted event-related potentials (ERP) by modulation of our synaptic device array.