Dr. Jebran Khan
Research Assistant Professor
Department of AI, Ajou University, South Korea.
Research Assistant Professor
Department of AI, Ajou University, South Korea.
Contact (South Korea)
Email: jebran@kduniv.ac.kr, khan.jebran2019@gmail.com
Skype: khan.jebran447
Office: (24764) 46, Bongpo4-gil, Toseong-myeon, Goseong-gun, Gangwon-do, Korea
((24764) 강원도 고성군 토성면 봉포4길 46)
Tel : 033-639-0127, FAX : 033-639-0303
Dr. Jebran Khan is an accomplished researcher and educator with over 14 years of experience in cutting-edge research and teaching at prestigious institutions, including the University of Engineering & Technology (UET) Peshawar, Korea Aerospace University, AJOU University, and Kyungdong University Global. He is an Assistant Professor in the Department of Artificial Intelligence at Kyundong University Global, South Korea.
Dr. Khan's academic journey began with a B.Sc. and M.Sc. in Computer Systems Engineering from UET Peshawar, Pakistan, followed by a Ph.D. in Electronics and Information Engineering from Korea Aerospace University. His doctoral work and subsequent research have established him as a leader in several emerging domains of Artificial Intelligence (AI) and its applications.
Dr. Khan has consistently contributed to advancing AI research as a dedicated scholar. Over the past five years, he has published extensively in high-impact journals, addressing critical AI and Machine Learning challenges. His work spans diverse areas, including Natural Language Processing, Large Language Models, Social Network Analysis, Recommender Systems, Graph Analysis Applications, Human Activity Recognition, and Contact Tracing. Dr. Khan's research also emphasizes AI's ethical and practical aspects, contributing to building trustworthy AI systems for societal impact.
Dr. Khan’s research contributions span diverse domains, including Large Language Models, Graph Analysis Applications, Human Activity Recognition, Contact Tracing, and Explainable AI. He focuses on developing innovative and trustworthy AI solutions for complex real-world problems. His collaborative research efforts include partnerships with scholars from South Korea, Pakistan, and Ireland on behavior analysis, explainable NLP, and AI ethics.
Dr. Khan is also an editor and reviewer for high-impact journals from prestigious publishers like IEEE, Springer, and MDPI. He has participated in and presented at numerous international conferences, contributing to the global AI research community.
Dr. Khan aims to bridge the gap between theoretical AI advancements and practical applications, particularly in social media ecosystems and health informatics. His vision is to develop innovative, resilient, and trustworthy AI systems that address contemporary challenges and create a sustainable societal impact.
Please don't hesitate to contact me if you are interested in collaborating on research in the relevant areas of our joint interest.
Fully funded Scholarship in Ph.D.
Among top 10 at undergraduate level.
3rd position in Pre-Engineering at the Intermediate level.
Introduction to Responsible AI Algorithm Design through LinkedIn Learning (2024)
Responsible AI: Principles and Practical Applications through LinkedIn Learning (2024)
Introduction to Large Language Models through LinkedIn Learning (2024)
Machine Learning with Python: Foundations through LinkedIn Learning (2024)
Programming for Everybody (Getting Started with Python) from the University of Michigan through Coursera (2019)
Machine Learning by Andrew Ng from Stanford University through Coursera (2018)
Graduated among the top 10 (9th position) of the 2010 batch at the Department of Computer Systems Engineering, UET Peshawar, Pakistan (2010)
3rd position in the HSSC (intermediate) exam pre-engineering group at BISE Malakand, Pakistan (2005)