Researcher at King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
Dr. Sunusi Bala Abdullahi is a dedicated researcher and academic in the field of computer vision and artificial intelligence. With a strong foundation in electrical and computer engineering, he has contributed extensively to machine learning-based systems, computer vision technologies, and statistical modeling. His research delves into human-computer interaction (HCI), social signal processing, and digital image processing, impacting how technology interfaces with human behaviors and applications like sign language recognition. Dr. Abdullahi’s commitment to innovation is evident in his scholarly works, collaborations with international research teams, and mentorship of future researchers. His journey is marked by a blend of technical expertise, leadership, and cross-disciplinary collaboration.
Profile
Google Scholar
Education
Dr. Abdullahi’s academic foundation is robust, beginning with his Bachelor of Science degree in Electrical Engineering from Bayero University, Kano, Nigeria, followed by a Master of Science from the same institution in 2018. His most significant academic milestone came with the completion of his Doctor of Philosophy in Electrical and Computer Engineering from King Mongkut’s University of Technology Thonburi, Bangkok, in 2023. His Ph.D. focused on the intersection of machine learning and computer vision, developing cutting-edge solutions for real-world applications like dynamic gesture recognition and multimodal biometric systems.
Experience
Dr. Abdullahi’s academic career spans multiple roles, showcasing his ability to bridge research and teaching. He started as a research assistant and visiting researcher at the University of A Coruna in Spain in 2022. His experience as a teaching assistant at King Mongkut’s University of Technology Thonburi (2023) and subsequent roles as a postdoctoral fellow have allowed him to mentor students, co-supervise Ph.D. candidates, and conduct groundbreaking research in AI, computer vision, and image processing. His international collaborations with institutions in countries like Thailand, Nigeria, Spain, Saudi Arabia, and South Africa further illustrate his global academic network and diverse expertise.
Research Interests
Dr. Abdullahi’s primary research focus lies in the areas of computer vision, digital image processing, artificial intelligence, and their applications in human-computer interaction. His work explores the integration of machine learning models to improve multimodal data interaction, enhance human motion analysis, and advance social signal processing. A significant portion of his research is dedicated to improving sign language recognition technologies, contributing novel algorithms and methods to enhance accuracy in human motion detection and gesture recognition systems.
Awards
Throughout his career, Dr. Abdullahi has been recognized for his contributions to research. In 2023, he received the Young Researcher Encouragement Award at the 5th ASEAN-UEC Workshop on Informatics and Engineering in Bangkok. He also earned the same award in 2020 at the 2nd ASEAN-UEC Workshop on Energy and AI in Indonesia. His academic journey began with the Dean’s Honor Roll Award in 2006 for Best Outstanding Student Performance from the Federal College of Education in Nigeria. In addition to these accolades, Dr. Abdullahi secured multiple research grants, including the prestigious Petchra Pra Jom Klao Ph.D. Scholarship Award.
Publications
Dr. Abdullahi has authored numerous research articles in high-impact journals. His most recent publications include:
Abdullahi, S.B., Chamnongthai, K., Cancela, B., & Bolon-Canedo, V. (2024). Spatial-temporal feature-based end-to-end fourier network for 3D sign language recognition. Expert Systems with Applications, 248, 123258. Cited: 10
Abdullahi, S.B., Chamnongthai, K., Lubna, G., & Haruna, C. (2024). Fsign-net: Depth sensor aggregated frame-based fourier network for sign word recognition. IEEE Sensors Journal, 248, 123258. Cited: 14
Alamri, F. S., Abdullahi, S.B., Khan, R. A., & Saba, T. (2024). Enhanced weak spatial modeling through cnn-based deep sign language skeletal feature transformation. IEEE Access, 12, 43675–43689. Cited: 12
Bature, Z. A., Abdullahi, S.B., Chiracharit, W., & Chamnongthai, K. (2024). Translated pattern-based eye-writing recognition using dilated causal convolution network. IEEE Access, 12, 59079–59092. Cited: 4
Conclusion
Dr. Sunusi Bala Abdullahi is a strong contender for the Best Researcher Award. His comprehensive contributions to computer vision, AI, and machine learning, combined with his leadership in research supervision, international collaborations, and a prolific publication record, make him a standout candidate. His ability to innovate, collaborate globally, and mentor rising researchers establishes him as a deserving recipient of this award. With continued growth in interdisciplinary research and global academic leadership, Dr. Abdullahi’s influence will likely expand even further in the coming years.