Education:
Dr. Khondaker Mamun’s educational background is extensive and distinguished. He completed his Postdoctoral research at the Institute of Biomaterials and Biomedical Engineering (IBBME) at the University of Toronto, Ontario, Canada, in collaboration with the Holland Bloorview Kids Rehabilitation Hospital. He earned his PhD in Computer Science and Medical Engineering from the University of Southampton, UK, in 2012. His dissertation, “Pattern Identification of Movement Related States in Biosignals,” was supervised by Prof. Shouyan Wang, Director of the Biomedical Electronics Department at the Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, China. His PhD examiners were Prof. John Stein from the University of Oxford and Dr. David Simpson from the University of Southampton. Dr. Mamun also holds an MSc in Computer Science and Engineering from the Bangladesh University of Engineering and Technology (BUET), where he completed a dissertation on “Memory Efficient Data Structure for Static Huffman Tree” under Prof. Md. Mostofa Akbar in 2007. He began his academic journey with a BSc in Computer Science and Engineering from Ahsanullah University of Science and Technology (AUST) in Dhaka, Bangladesh, graduating first in his class in 2002. His undergraduate dissertation, “Architecture of Enterprise Resource Planning (ERP) for a Group of Companies,” was supervised by Dr. Tamjidul Hoque from the University of New Orleans, USA.
Professional Experience:
Dr. Khondaker Mamun has garnered extensive professional experience across academia and research institutions. He is currently serving as a Professor in the Department of Computer Science and Engineering at United International University, Dhaka, Bangladesh. Previously, he held a postdoctoral position at the Institute of Biomaterials and Biomedical Engineering (IBBME) at the University of Toronto, Canada, collaborating closely with the Holland Bloorview Kids Rehabilitation Hospital. During his tenure at the University of Toronto, Dr. Mamun worked on advanced biomedical engineering projects, focusing on assistive technology and biosignal processing. Before his postdoctoral work, Dr. Mamun completed his PhD at the University of Southampton, UK, where he specialized in the pattern identification of movement-related states in biosignals. His academic journey also includes significant teaching and research roles at various institutions. Throughout his career, Dr. Mamun has been involved in numerous research projects, contributing to the fields of biomedical signal processing, machine learning, and assistive technology. His work has led to several publications in high-impact journals and conferences, reflecting his commitment to advancing scientific knowledge and practical applications in healthcare technology.
Research Interests:
Dr. Khondaker Mamun’s research interests are diverse and multidisciplinary, focusing on the intersection of technology and healthcare. His primary areas of interest include biomedical signal processing, where he works on developing advanced algorithms for analyzing biosignals to improve patient care and diagnostic accuracy. He is also deeply engaged in assistive technology, aiming to create innovative solutions that enhance the quality of life for individuals with disabilities. Additionally, Dr. Mamun explores machine learning and artificial intelligence applications in healthcare, particularly in the development of intelligent systems for real-time health monitoring and decision support. His research contributions extend to neuroengineering, where he investigates the neural mechanisms underlying movement and the development of neuroprosthetics. Through his work, Dr. Mamun seeks to bridge the gap between cutting-edge technology and practical healthcare solutions, driving advancements in medical technology and improving patient outcomes.
Skills:
Dr. Khondaker Mamun possesses a diverse set of skills that showcase his extensive experience and multidisciplinary expertise. He is proficient in biomedical signal processing, enabling him to analyze and interpret complex biomedical signals for improved diagnostic and therapeutic outcomes. His skills in machine learning and artificial intelligence are applied to healthcare applications, including real-time health monitoring and predictive analytics. Dr. Mamun excels in assistive technology development, designing innovative devices and systems to enhance the quality of life for individuals with disabilities. His expertise in neuroengineering involves exploring neural mechanisms and developing neuroprosthetics and brain-computer interface technologies. Additionally, he has strong capabilities in data analysis and statistical modeling, essential for processing and interpreting large datasets in medical research. Dr. Mamun is also proficient in software development, utilizing various programming languages and tools in biomedical research and healthcare technology. His project management skills ensure effective oversight of interdisciplinary research projects from conception to execution. He is excellent at collaboration and teamwork, working with healthcare professionals, engineers, and researchers to achieve common goals. Dr. Mamun is experienced in academic writing and publishing, authoring research papers and articles for prestigious journals and conferences. Furthermore, he is committed to teaching and mentoring, fostering the next generation of innovators in biomedical engineering and healthcare technology.
Conclution:
Dr. Khondaker Mamun’s exceptional academic background, extensive research experience, significant contributions to digital health and biomedical engineering, and active engagement in both academic and professional communities make him an outstanding candidate for the Best Researcher Award. His work in establishing AIMS Lab and CMED Health highlights his commitment to innovation and practical applications of research, further cementing his suitability for this prestigious recognition.
Publication Tob Noted:
Progress in Brain Computer Interface: Challenges and Opportunities
- Authors: S. Saha, K.A. Mamun, K. Ahmed, R. Mostafa, G.R. Naik, S. Darvishi, …
- Journal: Frontiers in Systems Neuroscience
- Year: 2021
- Volume: 15
- Article ID: 578875
- Citations: 284
Technological Advancements and Opportunities in Neuromarketing: A Systematic Review
- Authors: F.S. Rawnaque, K.M. Rahman, S.F. Anwar, R. Vaidyanathan, T. Chau, …
- Journal: Brain Informatics
- Year: 2020
- Volume: 7
- Pages: 1-19
- Citations: 138
Cloud-Based Framework for Parkinson’s Disease Diagnosis and Monitoring System for Remote Healthcare Applications
- Authors: K.A. Al Mamun, M. Alhussein, K. Sailunaz, M.S. Islam
- Journal: Future Generation Computer Systems
- Year: 2017
- Volume: 66
- Pages: 36-47
- Citations: 81
A Critical Review on World University Ranking in Terms of Top Four Ranking Systems
- Authors: F. Anowar, M.A. Helal, S. Afroj, S. Sultana, F. Sarker, K.A. Mamun
- Book: New Trends in Networking, Computing, E-learning, Systems Sciences, and …
- Year: 2015
- Citations: 61
Telemonitoring Parkinson’s Disease Using Machine Learning by Combining Tremor and Voice Analysis
- Authors: M.S.R. Sajal, M.T. Ehsan, R. Vaidyanathan, S. Wang, T. Aziz, K.A.A. Mamun
- Journal: Brain Informatics
- Year: 2020
- Volume: 7
- Issue: 1
- Article ID: 12
- Citations: 56
Exploration of EEG-based Depression Biomarkers Identification Techniques and Their Applications: A Systematic Review
- Authors: A. Dev, N. Roy, M.K. Islam, C. Biswas, H.U. Ahmed, M.A. Amin, F. Sarker, …
- Journal: IEEE Access
- Year: 2022
- Volume: 10
- Pages: 16756-16781
- Citations: 44