School of Computer Science

Image of Hafeez Ullah Amin

Hafeez Ullah Amin

Assistant Professor,



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 focus on EEG Signal Processing 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 member of IEEE, IEEE EMBS, IEEE society of Signal Processing, and Malaysian engineering and neuroscience societies.

Expertise Summary

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 Summary

Teaching Courses in 2020-2021; 2021-2022:

System and Architecture [Assembly Language Programming] (autumn)

Fundamentals of Artificial Intelligence (spring)

Mathematics for Computer Science II (spring)

Research Summary

He is conducting multidisciplinary research, especially for mental healthcare, using neuroimaging techniques, cognitive computing, signal processing, and applied machine learning. Potential… read more

Selected Publications

Current Research

He is conducting multidisciplinary research, especially for mental healthcare, using neuroimaging techniques, cognitive computing, signal processing, and applied machine learning. Potential candidates interested in Master/Ph.D. studies in the following research areas can contact me directly for supervision (


  1. AI Applications in Mental Healthcare
  2. EEG/ERP/MEG Signals Processing
  3. Biomedical Data Science
  4. Cognitive and Affective Computing
  5. Applied Machine Learning

Past Research

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.

School of Computer Science

University of Nottingham
Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB

For all enquires please visit: