Dr. Amin joined the School of Computer Science, University of Nottingham, Malaysia as an Assistant Professor in February 2020. Previously, he has worked as a postdoctoral researcher from October 2017 to February 2020, and a Research Scientist from August 2015 to October 2017 at Centre for Intelligent Signal and Imaging Research (CISIR), Universiti Teknologi PETRONAS (UTP), Malaysia. He has received a B.Sc. (Hons) degree in Information Technology and a M.S. degree in Computer Science (with specialization in Artificial Intelligence) from Pakistan in 2006 and 2009, respectively. He has obtained his Ph.D. in Electrical and Electronic Engineering with a specialty in EEG Signal Processing and Applied Machine Learning from UTP in July 2017. He has published over 50 articles in flagship local and international conference proceedings and peer-reviewed impact factor journals of Elsevier, IEEE, Springer, and Frontiers with a total cumulative impact factor of above 50. His research interests include EEG/ERP signals, cognitive computing, neuroinformatics, and machine learning in healthcare. He is a senior member of IEEE, Fellow of Advanced HE (FHEA), UK, Malaysian Society of Neurosciences, and Malaysian Engineering Society.
He has expertise in human brain mapping, such as EEG and ERP acquisition, experiment designing, Feature extraction & feature selection, statistical analysis, and modeling data with machine learning techniques.
He has contributed to various research projects related to learning memory, emotion, intelligence assessment, working memory and attention, depression and epilepsy detection at the time when he was a research scientist and postdoctoral researcher. He has experience of experiment designing using E-prime software, Acquisition of EEG and ERP signals with high-density EEG system, such as EGI 128 channel system, analysis of EEG feature extraction, source analysis and resting-state connectivity by programming in MATLAB, and statistical analysis in SPSS.
He is well trained in acquisition of brain signals data; having expertise in analyzing the biomedical signals, with techniques such as Wavelet Transform, Fourier Transform, and non-linear methods for extraction of features from signals; data reduction techniques such as PCA and statistics to optimize the extracted features data, and machine learning algorithms to model the experimental data.
Teaching Courses in 2020-2021; 2021-2022; 2022-2023:
System and Architecture [Assembly Language Programming] (autumn)
Fundamentals of Artificial Intelligence (spring)
Mathematics for Computer Science II (spring)
He is conducting multidisciplinary research, especially for mental healthcare, using neuroimaging techniques, cognitive computing, signal processing, and applied machine learning. Potential students… read more
He is conducting multidisciplinary research, especially for mental healthcare, using neuroimaging techniques, cognitive computing, signal processing, and applied machine learning. Potential students interested in UG internship, UG Final Year Project, MSc dissertation, and especially MPhil/PhD studies, and Postdoc studies in the following research areas (but not limited) can contact me directly via (firstname.lastname@example.org) for supervision, idea discussion and grants application.
- AI Applications in Mental Healthcare
- EEG/ERP/MEG Signals Processing
- Applied Machine Learning
- Biomedical Data Science
- Cognitive and Affective Computing
Previously, he has investigated semantic long-term memory using EEG/ERP signals, and developed methods for EEG feature extractions. In addition, he has worked on research projects related to cognitive functions and disorders.
In Future, with the continuation of the current research, I am interested to work on Internet Gaming Addiction with EEG Technology and explore the neuronal mechanism of Gaming Addiction on cognitive abilities and academic performance. In addition, I am looking to work on designing Serious Gaming for mental healthcare, learning disabilities, and cognitive performance improvement.
Furthermore, I am also interested to work on projects Machine Learning Applications in Business Analytics, Machine, Financial Risk Assessment, Human Behavior and Decision Making, and Economic Forecasting and Decision Making for policymakers.
Interested researchers are welcome for research collaboration in the above areas (not limited) for joint grants application, joint students' supervision, joint research publications, and organizing academic and editorial events, like seminar, special issue in journal, and conferences.
Potential students are also welcome (including UG internship, UG Final Year Project, MSc dissertation, MPhil/PhD project, and Postdoc project) to contact me directly (email@example.com) for idea discussion, supervision, and grants application.