Ali Rohan received the B.S. degree in electrical engineering from The University of Faisalabad, Pakistan, in 2012, and the M.S. and PhD degrees in electrical, electronics, and control engineering from Kunsan National University, South Korea, in 2018 and 2020, respectively. From 2012 to 2013, he worked as a Development Engineer at the Niagara Group of Industries, Pakistan. From 2013 to 2015, he worked as a Project Engineer for Circle Club, Pakistan. From 2015 to 2016, he worked as a Project Manager for Steam Masters, Pakistan, and also as a Lecturer at the Department of Electrical and Telecommunication Engineering, Government College University Faisalabad, Pakistan. From 2016 to 2020, he worked as a Research Associate with the Factory Automation and Intelligent Control Lab., Kunsan National University. From 2020 to 2021, he worked as an Assistant Professor with the Department of Mechanical, Robotics, and Energy Engineering, Dongguk University, South Korea. He is currently working as Research Fellow with the Faculty of Medicine and Health Sciences, University of Nottingham, United Kingdom.
Data Science, Machine Learning, Artificial Intelligence, Computer Vision, Automation and Control, Robotics
My current research work is mainly focused on developing AI and computer vision-based solutions for animal behaviour monitoring. I am also interested in developing assistive AI technologies for the… read more
ASGHAR, FURQAN, ROHAN, ALI, TALHA, MUHAMMAD, HAN, YUN-JONG and KIM, SUNG-HO, 2020. JKIIS Journal of Korean Institute of Intelligent Systems. 30(1), 8-19
RABAH, MOHAMMED, ROHAN, ALI, HAGHBAYAN, MOHAMMAD-HASHEM, PLOSILA, JUHA and KIM, SUNG-HO, 2020. Heterogeneous parallelization for object detection and tracking in UAVs IEEE Access. 8, 42784-42793
ASGHAR, FURQAN, ROHAN, ALI, TALHA, MUHAMMAD, HAN, YUN-JONG and KIM, SUNG-HO, 2020. Fuzzy Logic based Efficient Load Management and Optimal Operation of a PV-DG Hybrid System with Battery Backup 한국지능시스템학회 논문지. 30(1), 28-39
ROHAN, ALI, RABAH, MOHAMMED, HOSNY, TAREK and KIM, SUNG-HO, 2020. Human pose estimation-based real-time gait analysis using convolutional neural network IEEE Access. 8, 191542-191550