Assist Prof Dr. Inam Ullah, Shenzhen University, China
Dr. Inam Ullah, currently at Gachon University, South Korea, holds a Ph.D. in Information & Communication Engineering from Hohai University, China, specializing in adaptive techniques for mobile robot localization. His extensive academic and professional background includes roles as a Postdoctoral Research Fellow at Chungbuk National University, South Korea, and a Project Consultant/Advisor for AI and data science at the University of Dir, Pakistan. Dr. Ullah’s research spans IoT, robotics, autonomous vehicles, and AI, boasting a cumulative Impact Factor of 268.20 and over 23,000 Google Scholar citations. He has significantly contributed to top-tier journals as a guest editor and has received numerous awards, including the Jiangsu Province Distinguished International Students Award and the Distinguished Alumni Award from the University of Science & Technology Bannu.
🌍 Professional Profile:
Suitability Summary for Best Researcher Award
Dr. Inam Ullah demonstrates exceptional qualifications and achievements that make him a strong contender for the Best Researcher Award. His professional and academic journey is marked by significant contributions to the fields of AI, IoT, and data science, backed by a robust publication record and impactful research.
Academic and Professional Background
Dr. Inam Ullah has an impressive academic background, with a Ph.D. in Information & Communication Engineering from Hohai University, China, where he specialized in adaptive techniques for mobile robot localization. His education also includes an MS from the same institution, focusing on underwater localization algorithms, and a bachelor’s degree in Electrical Engineering from the University of Science & Technology Bannu, Pakistan.
Professional Experience
Dr. Ullah currently serves as an Assistant Professor in the Department of Computer Engineering at Gachon University, South Korea. He has also held significant roles as a Postdoctoral Research Fellow at Chungbuk National University, South Korea, and as a Project Consultant/Advisor for AI, Data Science, and Commercialization at the University of Dir, Pakistan. His teaching and research roles have spanned various institutions, including a notable tenure at Hohai University, China.
Research Contributions
Dr. Ullah’s research interests encompass a wide array of advanced topics including IoT, robotics, autonomous vehicles, wireless sensor networks, network security, computer vision, AI, and machine learning. His work has resulted in a cumulative Impact Factor (IF) of 268.20, with 23012 Google Scholar citations, an h-index of 28, and an i10-index of 51. These metrics underscore his research’s widespread recognition and influence.
Publications and Editorial Roles
Dr. Ullah has been an active contributor to top-tier journals and conferences. He has served as a guest editor for several high-impact journals, such as “Computers in Human Behavior,” “Sensors,” “Journal of Marine Science and Engineering,” and “Electronics.” His editorial contributions have furthered the discourse in critical areas like AI, big data analytics, and underwater sensor networks.
Awards and Honors
Dr. Ullah’s excellence in research and academics has been recognized through various awards and honors. Notable among these are the Jiangsu Province Distinguished International Students Award, the Top-100 Outstanding Students Award at Hohai University, and the Distinguished Alumni Award from the University of Science & Technology Bannu.
Publication Top Notes:
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Title: A Localization Based on Unscented Kalman Filter and Particle Filter Localization Algorithms
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Citations: 147
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Year: 2019
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Title: Motor Imagery EEG Signals Decoding by Multivariate Empirical Wavelet Transform-Based Framework for Robust Brain–Computer Interfaces
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Citations: 145
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Year: 2019
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Title: Localization and Detection of Targets in Underwater Wireless Sensor Using Distance and Angle-Based Algorithms
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Citations: 132
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Year: 2019
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Title: Student-Performulator: Student Academic Performance Using Hybrid Deep Neural Network
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Title: A Multi-Layer Cluster-Based Energy Efficient Routing Scheme for UWSNs