Dr. Inam Ullah
Department of Computer Engineering
Gachon University, South Korea
Assistant Professor
Email: inam.fragrance@gmail.com; inam@gachon.ac.kr
Qualifications
2021 Ph.D., Hohai University (HHU), China
2018 M.Sc., Hohai University (HHU), China
2016 B.Sc., University of Science & Technology Bannu (USTB), Pakistan
Publications (Selected)
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Memon, S. A., Ullah, I., Abro, G. E. M., Ullah, I., & Noor, A. (2025). Advanced data association technique using integrated track splitting filter for multi-target tracking in clutter and occlusion. Expert Systems with Applications, 277, 127193.
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Rahman, A. U., Ali, S., Saqia, B., Halim, Z., Al-Khasawneh, M. A., AlHammadi, D. A., ... & Alharbi, M. (2025). Alzheimer's disease prediction using 3D-CNNs: Intelligent processing of neuroimaging data. SLAS technology, 32, 100265.
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Monirul, I. M., Qiu, L., Ruby, R., Ullah, I., & Sharafian, A. (2025). Accurate SOC estimation in power lithium-ion batteries using adaptive extended Kalman filter with a high-order electrical equivalent circuit model. Measurement, 249, 117081.
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Butt, A. U. R., Saba, T., Khan, I., Mahmood, T., Khan, A. R., Singh, S. K., ... & Ullah, I. (2025). Proactive and data-centric Internet of Things-based fog computing architecture for effective policing in smart cities. Computers and Electrical Engineering, 123, 110030.
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Arshad, T., Zhang, J., & Ullah, I. (2024). A hybrid convolution transformer for hyperspectral image classification. European Journal of Remote Sensing, 57(1), 2330979.
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Bilal, H., Tian, Y., Ali, A., Muhammad, Y., Yahya, A., Izneid, B. A., & Ullah, I. (2024). An Intelligent Approach for Early and Accurate Predication of Cardiac Disease Using Hybrid Artificial Intelligence Techniques. Bioengineering, 11(12), 1290.
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Ullah, I., Ali, F., Khan, H., Khan, F., & Bai, X. (2024). Ubiquitous computation in internet of vehicles for human-centric transport systems. Computers in Human Behavior, 161, 108394.
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Ahmed, M. J., Afridi, U., Shah, H. A., Khan, H., Bhatt, M. W., Alwabli, A., & Ullah, I. (2024). CardioGuard: AI-driven ECG authentication hybrid neural network for predictive health monitoring in telehealth systems. SLAS technology, 29(5), 100193.
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Ullah, I., Adhikari, D., Khan, H., Anwar, M. S., Ahmad, S., & Bai, X. (2024). Mobile robot localization: Current challenges and future prospective. Computer Science Review, 53, 100651.
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Rasheed, Z., Ma, Y. K., Ullah, I., Tao, Y., Khan, I., Khan, H., & Shafiq, M. (2024). Edge computing in the digital era: The nexus of 5G, IoT and a seamless digital future. In Future communication systems using artificial intelligence, internet of things and data science (pp. 213-234). CRC Press.
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Ahmad, I., Yao, C., Li, L., Chen, Y., Liu, Z., Ullah, I., ... & Chen, S. (2024). An efficient feature selection and explainable classification method for EEG-based epileptic seizure detection. Journal of Information Security and Applications, 80, 103654.
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Ullah, I., Noor, A., Nazir, S., Ali, F., Ghadi, Y. Y., & Aslam, N. (2024). Protecting IoT devices from security attacks using effective decision-making strategy of appropriate features. The Journal of Supercomputing, 80(5), 5870-5899.
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Rasheed, Z., Ma, Y. K., Ullah, I., Ghadi, Y. Y., Khan, M. Z., Khan, M. A., ... & Shehata, A. M. (2023). Brain tumor classification from MRI using image enhancement and convolutional neural network techniques. Brain Sciences, 13(9), 1320.
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Arshad, T., Zhang, J., Ullah, I., Ghadi, Y. Y., Alfarraj, O., & Gafar, A. (2023). Multiscale feature-learning with a unified model for hyperspectral image classification. Sensors, 23(17), 7628.
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Khan, H. U., Hussain, A., Nazir, S., Ali, F., Khan, M. Z., & Ullah, I. (2023). A service-efficient proxy mobile IPv6 extension for IoT domain. Information, 14(8), 459.
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Khan, H. U., Sohail, M., Ali, F., Nazir, S., Ghadi, Y. Y., & Ullah, I. (2023). Prioritizing the multi-criterial features based on comparative approaches for enhancing security of IoT devices. Physical Communication, 59, 102084.
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Hussain, A., Hussain, T., Ullah, I., Muminov, B., Khan, M. Z., Alfarraj, O., & Gafar, A. (2023). CR-NBEER: cooperative-relay neighboring-based energy efficient routing protocol for marine underwater sensor networks. Journal of Marine Science and Engineering, 11(7), 1474.
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Shah, A., Ali, B., Wahab, F., Ullah, I., Amesho, K. T., & Shafiq, M. (2023). Entropy-based grid approach for handling outliers: a case study to environmental monitoring data. Environmental science and pollution research, 30(60), 125138-125157.
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Mazhar, T., Irfan, H. M., Khan, S., Haq, I., Ullah, I., Iqbal, M., & Hamam, H. (2023). Analysis of cyber security attacks and its solutions for the smart grid using machine learning and blockchain methods. Future Internet, 15(2), 83.
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Mazhar, T., Irfan, H. M., Haq, I., Ullah, I., Ashraf, M., Shloul, T. A., ... & Elkamchouchi, D. H. (2023). Analysis of challenges and solutions of IoT in smart grids using AI and machine learning techniques: A review. Electronics, 12(1), 242.
Profile Details
WoS Researcher ID: Z-3617-2019
https://orcid.org/0000-0002-5879-569X
https://www.linkedin.com/in/dr-inam-ullah-767695143/
https://scholar.google.com/citations?user=HgzcLyUAAAAJ&hl=en
https://www.researchgate.net/profile/Inam-Ullah-20
https://sciprofiles.com/profile/InamUllah