Mr at University of Manitoba, Canada
Ali Mohammad Alqudah, M.Sc., is a dedicated Graduate Research Assistant at the Biomedical Instrumentation and Signal Analysis Lab, Biomedical Engineering Program, University of Manitoba (UoM), Canada. With a strong foundation in computer and biomedical systems engineering, he has contributed significantly to research in machine learning and biomedical applications. Ali is affiliated with multiple professional organizations, including IEEE and ACM, and has been consistently recognized for his academic excellence, notably featuring on Stanford’s top 2% scientist list from 2021 to 2024. His editorial roles in prestigious journals further highlight his expertise and influence in his field. Ali’s research and professional activities reflect his commitment to advancing the integration of AI and biomedical engineering.
Profile
Scopus
Scholar
Education 🎓
Ali Mohammad Alqudah is currently pursuing his Ph.D. in Biomedical Engineering at the University of Manitoba, where he specializes in deep learning applications for medical conditions such as obstructive sleep apnea (OSA). His research under Prof. Zahra Moussavi focuses on innovative diagnostic methods using tracheal breathing sounds during wakefulness. Alqudah’s educational journey began with a B.S.E. in Biomedical Systems Engineering from Yarmouk University, Jordan (2015), followed by an M.Sc. in Computer Engineering (Industrial Automation) in 2018, where he graduated first in his class with a GPA of 91.4%. His academic training includes advanced coursework in biomedical signal processing and medical imaging, shaping his expertise in computational biomedical applications.
Experience 💼
Ali Mohammad Alqudah’s professional trajectory includes extensive research and teaching experiences. He is currently a Graduate Research Assistant at the University of Manitoba, contributing to cutting-edge studies in biomedical signal processing and AI applications in healthcare. His work has involved deep learning models for OSA detection and other diagnostic innovations. Alqudah’s prior roles include academic assistantships and involvement in laboratory teaching at Yarmouk University. His contributions are marked by the practical integration of machine learning and engineering skills, advancing research that bridges technology and medicine. Ali has also served in editorial capacities for prominent journals, showcasing his thought leadership and commitment to scholarly dissemination.
Awards and Honors 🏆
Ali Mohammad Alqudah’s exceptional contributions have earned him spots on Stanford’s prestigious list of the top 2% of scientists worldwide for four consecutive years (2021-2024). His outstanding academic performance during his M.Sc. at Yarmouk University led to him graduating first in his class. Ali’s scholarly output has been widely recognized, with publications in high-impact journals and conference proceedings. His membership in professional organizations such as IEEE and ACM further testifies to his active engagement in the scientific community. These honors reflect his deep commitment to advancing research in biomedical engineering, signal processing, and artificial intelligence.
Research Focus 🔍
Ali Mohammad Alqudah’s research centers on the intersection of artificial intelligence and biomedical engineering. His primary areas of interest include machine learning and deep learning for medical diagnostics, biomedical signal and image processing, and computer applications in healthcare. His current Ph.D. work explores the application of deep learning for detecting obstructive sleep apnea using non-invasive tracheal breathing sound analysis. Alqudah’s studies incorporate advanced techniques in pattern recognition and AI to improve patient screening and diagnostic accuracy. His commitment to leveraging AI for enhanced medical outcomes positions him as a key contributor to innovations in healthcare technology.
Conclusion 📝
Ali Mohammad Alqudah’s distinguished academic and research career, combined with his technical proficiency and global recognition, make him a strong candidate for the Young Scientist Award. His ongoing work in deep learning for medical diagnostics has the potential to revolutionize early disease detection methods, providing tangible advancements in healthcare technology. With minor enhancements in collaborative and mentorship activities, Alqudah could further solidify his position as a future leader in biomedical engineering research.
Publications 📚
- Title: Sliding window based deep ensemble system for breast cancer classification
Year: 2021
Authors: A Alqudah, AM Alqudah
Journal: Journal of Medical Engineering & Technology 45 (4), 313-323
- Title: Reduced number of parameters for predicting post-stroke activities of daily living using machine learning algorithms on initiating rehabilitation
Year: 2021
Authors: AM Alqudah, M Al-Hashem, A Alqudah
Journal: Informatica 45 (4)
- Title: Advanced time-frequency methods for ECG waves recognition
Year: 2023
Authors: A Zyout, H Alquran, WA Mustafa, AM Alqudah
Journal: Diagnostics 13 (2), 308
- Title: Pulmonary Diseases Decision Support System Using Deep Learning Approach
Year: 2022
Authors: Y Al-Issa, AM Alqudah, H Alquran, A Al Issa
Journal: Computers, Materials & Continua 73 (1), 311-326
- Title: An embedded system based on raspberry pi for effective electrocardiogram monitoring
Year: 2023
Authors: YM Obeidat, AM Alqudah
Journal: Applied Sciences 13 (14), 8273
- Title: Enhancing Prediction of Prosthetic Fingers Movement Based on sEMG Using Mixtures of Features and Random Forest
Year: 2019
Authors: WN Al-Sharu, AM Alqudah
Journal: International Journal of Recent Technology and Engineering (IJRTE) 8 (4)
- Title: International Journal of Advanced Trends in Computer Science and Engineering
Year: 2019
Authors: AM Alqudah, H Alquraan, IA Qasmieh, A Alqudah, W Al-Sharu
Journal: International Journal 8 (6)
- Title: EOG-based mouse control for people with quadriplegia
Year: 2016
Author: AM Alqudah
Journal: XIV Mediterranean Conference on Medical and Biological Engineering and …
- Title: A New Weighted Deep Learning Feature Using Particle Swarm and Ant Lion Optimization for Cervical Cancer Diagnosis on Pap Smear Images
Year: 2023
Authors: M Alsalatie, H Alquran, WA Mustafa, A Zyout, AM Alqudah, R Kaifi, …
Journal: Diagnostics 13 (17), 2762
- Title: The Internet of Things in Healthcare: A survey for Architecture, Current and Future Applications, Mobile Application, and Security
Year: 2019
Author: AM Alqudah
Journal: JOIV: International Journal on Informatics Visualization 3 (2), 113-122
- Title: Detection of valvular heart diseases using fourier transform and simple cnn model
Year: 2022
Authors: WN Al-Sharu, AM Alqudah, S Qazan, A Alqudah
Journal: IAENG International Journal of Computer Science 49 (4), 985-993
- Title: Automated diagnosis of heart-lung diseases in chest X-ray images
Year: 2022
Authors: M Alslatie, H Alquran, WA Mustafa, I Abu-Qasmieh, AM Alqudah, …
Journal: 2022 5th International Conference on Engineering Technology and its …