Academic Profile : Faculty

Dr Yuvaraj Rajamanickam
Education Research Scientist, Centre for Science of Learning in Education
Research Scientist, National Institute of Education - Office for Research
External Links
Controlled Keywords
Dr. Yuvaraj Rajamanickam is a lecturer (research scientist) at the Science of learning in Education Centre (SoLEC), National Institute of Education (NIE), Singapore. He received both B.E. (Electronics and Communication Engineering) and M.E. degrees (Biomedical Engineering-Gold Medalist) from Anna University and the Ph. D degree (Biomedical Electronics) from University Malaysia Perlis (UniMAP), Malaysia, 2015. Before joining NIE, he was a Postdoctoral Research Fellow in the School of Electrical and Electronic Engineering at Nanyang Technological University (NTU), Singapore and the Neural Systems Lab, Department of Biomedical Engineering at University of Kentucky, USA. In research, his interests are machine learning algorithms, with application to biomedical signal processing (such as electroencephalogram (EEG)) that include affective computing, brain-computer interface (BCI), and cognitive neuroscience. Dr. Yuvaraj supports interdisciplinary research and has successfully collaborated on many research projects with computer science scholars, psychologists, neurologists, and education institutions. To date, he has published in several top-tier journals, conferences, and book chapters. He has continued to involve in the various reputed conference technical committees and has also held positions as publicity chair, committee member of the IEEE conferences. He also serves as a reviewer of various journals such as IEEE Transactions on Neural Systems and Rehabilitation Engineering, NeuroImage, Neuroscience Letters, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions in Affective Computing, etc.
Dr. Yuvaraj areas of expertise are machine learning/deep learning algorithms with application to biomedical signal processing. His current research works focus on affective computing in education using neurophysiological signals.
- Optimising capacity to improve ideas by investigating Brainwave Responses to ideaimprovement trigger with Electroencephalogram (EEG)
- Collaborative Teaching Between Remote Higher Education Institutions: A Blended Synchronous Learning Approach to Educational Neuroscience
- RaDiX: Building flexibility and creativity to support lifelong learning through Physical Education
- RISE-M: Regulation Competencies for At-rISk Adolescents: Social Well-bEing & Neurophysiological Markers
- Self-Regulated Learning, Emotion, and Achievement: Applying Multimodal Classroom Research in a Singapore School
- Development of Brain Networks and Social-Emotional Functions
- Emotion Recognition from EEG Signals using Machine Learning Approach
- Automated Boredom Detection using Multimodal Physiological Signals
Awards
• 2023 NIE Excellence in Service Award
• 2016 Young Scientist research award, awarded by the Science and Engineering
Research Board (SERB), Govt of India.
• 2015 Gold Medal, Malaysian Technology Expo (international), Malaysia.
• 2014 Special Award, Best Invention in Biotechnology, Japan Intellectual Property
Association, ITEX Expo, Malaysia.
• 2014 Gold Medal, ITEX Expo (international), Malaysia.
• 2016 Young Scientist research award, awarded by the Science and Engineering
Research Board (SERB), Govt of India.
• 2015 Gold Medal, Malaysian Technology Expo (international), Malaysia.
• 2014 Special Award, Best Invention in Biotechnology, Japan Intellectual Property
Association, ITEX Expo, Malaysia.
• 2014 Gold Medal, ITEX Expo (international), Malaysia.
Fellowships & Other Recognition
• 2019 Visiting Fellowship, University of Exeter, UK.
• 2019 Visiting Fellowship, Austrian Institute of Technology (AIT), Austria.
• 2019 Visiting Fellowship, Austrian Institute of Technology (AIT), Austria.
Courses Taught
AGE06B Applications of Educational Neuroscience
AGE06D Neurodiversity and Learning Experience
AGE06E Neuroscience, Computational Thinking and AI in Learning
AGE06D Neurodiversity and Learning Experience
AGE06E Neuroscience, Computational Thinking and AI in Learning