Dr. Syed Muhammad Usman
Category: Faculty
Published on: November 1, 2024
PERSONAL INFORMATION
Name Dr. Syed Muhammad Usman
Email drsyedmusman@gmail.com
Phone 03320615294
Research Area Biomedical Signal Processing, Medical Imaging, Precision Agriculture
Number of Publications Journals=18

Conferences=06

 

AFFILIATIONS
Designation Senior Assistant Professor
Department Computer Science
University Bahria School of Engineering and Applied Sciences, Bahria University, Islamabad
QUALIFICATION
DEGREE PASSING YEAR MAJORS UNIVERSITY
PhD 2021 Computer Engineering Bahria University, Islamabad
MS 2017 Computer Engineering National University of Science and Technology (NUST), Islamabad
BS 2011 Computer Engineering The Islamia University of Bahwalpur
EXPERIENCE
DESIGNATION FROM TO ORGANIZATION
Sr. Assistant Professor 2024 Present Bahria University, Islamabad
Assistant Professor,  2022 2024 Air University, Islamabad
Program Manager (Data Science)  2022 2024 Air University, Islamabad
Program Manager (Software Engineering)  2019 2022 SZABIST University, Islamabad
Lecturer 2017 2022 SZABIST University, Islamabad
Design Engineer 2013 2017 Centangle (Pvt.) Ltd.
JOURNAL PUBLICATIONS (Cumulative Impact Factor: 52.6)
1. Usman, S.M., Khalid, S. and Bashir, S., 2021. A Deep Learning based Ensemble Learning Method for Epileptic Seizure Prediction. Computers in Biology and Medicine, p.104710. (Impact Factor: 7.0)
2. Usman, S.M., Khalid, S. and Bashir, Z., 2021. Epileptic seizure prediction using scalp electroencephalogram signals. Biocybernetics and Biomedical Engineering, 41(1), pp.211-220. (Impact Factor: 5.3)
3. Syed Abdullah Shah, Imran Taj, Syed Muhammad Usman, Syed Nehal Hassan Shah, Ali Shariq Imran and Shehzad Khalid “A Hybrid Approach of Vision Transformers and CNNs for Detection of Ulcerative Colitis”, Scientific Reports, Accepted for publication, 2024. (Impact Factor: 3.8)
4. Muhammad Zubair, Muhammad Owais, Tahir Mahmood, Saeed Iqbal, Syed Muhammad Usman, Irfan Hussain “Enhanced gastric cancer classification and quantification interpretable framework using digital histopathology images”, Scientific Reports, Sci Rep 14, 22533 (2024). https://doi.org/10.1038/s41598-024-73823-9 (Impact Factor: 3.8)
5. Amna Waheed, Imran Taj, Shehzad Khalid, Syed Muhammad Usman, Ali Shariq Imran, Muhammad Usman Akram “Advancing Emotional Health Assessments: A Hybrid Deep Learning Approach Using Physiological Signals for Robust Emotion Recognition”, IEEE Access, Accepted for publication, 2024. (Impact Factor: 3.4)
6. Frnaz Akbar, Syed Muhammad Usman “Automated Lesion Detection in Cotton leaf visuals using deep learning ”, PeerJ Computer Science, Accepted for Publication, 2024. (Impact Factor: 3.5)
7. Usman, S.M., Khalid, S., Jabbar, S. and Bashir, S., 2021. Detection of preictal state in epileptic seizures using ensemble classifier. Epilepsy Research, p.106818.(Impact Factor: 2.0)
8. Usman, S.M., Khalid, S. and Aslam, M.H., 2020. Epileptic seizures prediction using deep learning techniques. IEEE Access, 8, pp.39998-40007. (Impact Factor: 3.4)
9. Usman, S.M., Khalid, S., Akhtar, R., Bortolotto, Z., Bashir, Z. and Qiu, H., 2019. Using scalp EEG and intracranial EEG signals for predicting epileptic seizures: Review of available methodologies. Seizure, 71, pp.258-269. (Impact Factor: 2.7)
10. Y. Maqsood, S.M. Usman, M. Alhussein, K. Aurangzeb, S. Khalid, and M. Zubair “Model Agnostic Meta-Learning (MAML)-Based Ensemble Model for Accurate Detection of Wheat Diseases Using Vision Transformer and Graph Neural Networks,” Comput. Mater. Contin., vol. 79, no. 2, pp. 2795-2811. 2024. (Impact Factor: 2.0)
11. Aslam, M.H.; Usman, S.M.; Khalid, S.; Anwar, A.; Alroobaea, R.; Hussain, S.; Almotiri, J.; Ullah, S.S.; Yasin, A. Classification of EEG Signals for Prediction of Epileptic Seizures. Applied Sciences 2022, 12, 7251. (Impact Factor: 2.5)
12. Syed Muhammad Usman, Shahzad Latif, Arshad Beg, “Principle components analysis for seizures prediction using wavelet transform”, International journal of ADVANCED AND APPLIED SCIENCES, Volume 6, Issue 3 (March 2019), Pages: 50-55 (Impact Factor: 0.4)
13. Shah, S.M.A., Usman, S.M., Khalid, S., Rehman, I.U., Anwar, A., Hussain, S., Ullah, S.S., Elmannai, H., Algarni, A.D. and Manzoor, W., 2022. An Ensemble Model for Consumer Emotion Prediction Using EEG Signals for Neuromarketing Applications. Sensors, 22(24), p.9744.(Impact Factor: 3.4)
14. Awan, A.W., Usman, S.M., Khalid, S., Anwar, A., Alroobaea, R., Hussain, S., Almotiri, J., Ullah, S.S. and Akram, M.U., 2022. An Ensemble Learning Method for Emotion Charting Using Multimodal Physiological Signals. Sensors, 22(23), p.9480.(Impact Factor: 3.4)
15. Khan, A.R., Yasin, A., Usman, S.M., Hussain, S., Khalid, S. and Ullah, S.S., 2022. Exploring Lightweight Deep Learning Solution for Malware Detection in IoT Constraint Environment. Electronics, 11(24), p.4147. (Impact Factor: 2.6)
16. Riaz, S., Latif, S., Usman, S.M., Ullah, S.S., Algarni, A.D., Yasin, A., Anwar, A., Elmannai, H. and Hussain, S., 2022. Malware Detection in Internet of Things (IoT) Devices Using Deep Learning. Sensors, 22(23), p.9305. (Impact Factor: 3.4)
17. Muhammad Naveed, Fahim Arif, Syed Muhammad Usman, Aamir Anwar, Myriam Hadjouni, Hela Elmannai, Saddam Hussain, Syed Sajid Ullah, Fazlullah Umar, “A Deep Learning-Based Framework for Feature Extraction and Classification of Intrusion Detection in Networks”, Wireless Communications and Mobile Computing, vol. 2022, Article ID 2215852, 11 pages, 2022. ISI Indexed
18. Usman, S.M., Usman, M. and Fong, S., 2017. Epileptic seizures prediction using machine learning methods. Computational and mathematical methods in medicine, 2017.
INTERNATIONAL CONFERENCE PUBLICATIONS
1. Usman, S.M., Syed Nehal Hassan Shah, Nevena Dicheva, Ikram Ur Rehman, Samia Zaib, 2024, February. Integrating Advanced Healthcare AI into Higher Education of Smart Cities: Skin Cancer Classification with Custom Vision Transformers. Accepted for Publication In The 2nd International Conference on Sustainability: Developments and Innovations.
2. Muhammad Arsalan, Syed Muhammad Usman “Object Detection for Autonomous Vehicles in Urban Areas Using Deep Learning” Accepted for presentation in Future technologies Conference. 2024.
3. Usman, S.M., Shah, S.M.A., Edo, O.C. and Emakhu, J., 2023, March. A Deep Learning Model for Classification of EEG Signals for Neuromarketing. In 2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) (pp. 1-6). IEEE.
4. Tahir, H.U.A., Waqar, A., Khalid, S. and Usman, S.M., 2022, May. Wildfire detection in aerial images using deep learning. In 2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-7). IEEE
5. Usman, S.M. and Hassan, A., 2018. Efficient Prediction and Classification of Epileptic Seizures Using EEG Data Based on Univariate Linear Features. Journal of Computers, 13(6), pp.616-622.
6. Memon, K., Kumar, D. and Usman, S., 2011. Next generation a secure e-voting system based on biometric fingerprint method. In International Conference on Information and Intelligent Computing (IPCSIT) (pp. 26-32).