Lecturer at Universiti Sains Malaysia, Malaysia
Dr. Mohd Shahrimie Mohd Asaari is a Senior Lecturer in the School of Electrical & Electronic Engineering at Universiti Sains Malaysia (USM), with over a decade of experience in research, teaching, and industrial collaboration. His multidisciplinary work bridges deep learning, hyperspectral imaging, biometrics, computer vision, and intelligent systems, resulting in a diverse portfolio of high-impact journal publications. Dr. Asaari’s work significantly contributes to solving real-world problems, ranging from plant disease detection and PCB defect analysis to public safety through surveillance and biometric systems. He has successfully led or contributed to over 10 competitive national and industrial research grants, reflecting his strong leadership in research and innovation. Additionally, his consultancy projects and training roles for government and private agencies underline his influence beyond academia. With his international academic background, including a PhD from the University of Antwerp, and ongoing collaboration with global experts, Dr. Asaari is a driving force in applied AI and smart sensing systems.
Professional Profile
Education🎓
Dr. Mohd Shahrimie Mohd Asaari holds a Ph.D. in Science (Physics) from the University of Antwerp, Belgium, where he specialized in hyperspectral imaging and plant phenotyping. His postgraduate journey continued with a Master of Science in Electrical & Electronic Engineering from Universiti Sains Malaysia (USM), enriching his foundation in advanced electronics and intelligent systems. He earned his Bachelor of Engineering (B.Eng) in Electrical & Electronic Engineering from Universiti Teknologi MARA, Malaysia, with a focus on core engineering principles and digital systems. This comprehensive academic trajectory has equipped him with deep technical expertise, analytical rigor, and research skills across electronics, signal processing, and machine learning. His cross-disciplinary academic training—spanning physics, engineering, and computational technologies—has been instrumental in shaping his approach to solving complex problems in smart agriculture, industrial automation, and computer vision. Dr. Asaari’s strong educational foundation continues to inform his leadership in interdisciplinary research and technological innovation.
Professional Experience📝
Dr. Mohd Shahrimie Mohd Asaari has been serving as a Senior Lecturer in the Electronic Program at Universiti Sains Malaysia (USM) since 2019. He has over 5 years of experience in university-level teaching, covering subjects like Digital Signal Processing, Intelligent Systems, Microcontrollers, IoT Technology, and Circuit Laboratories. Before joining academia full-time, he spent 3 years in the semiconductor industry, which provided him with valuable hands-on experience and industry-relevant knowledge. His professional engagements extend beyond the classroom, with active participation in national-level consultation projects and technology-based research collaborations. He has also been involved in government and private training programs, including biometrics and intelligent systems modules conducted for CyberSecurity Malaysia. As a project leader and team member on multiple research initiatives, Dr. Asaari consistently bridges theoretical research with practical applications, thereby strengthening industry-academia collaboration. His dual experience in industry and academia positions him as a versatile expert in electronic systems and applied artificial intelligence.
Research Interest🔎
Dr. Mohd Shahrimie Mohd Asaari’s research interests lie at the intersection of artificial intelligence, computer vision, hyperspectral imaging, intelligent sensing, and biometric systems. He is particularly passionate about developing AI-driven solutions for real-world applications, such as plant disease detection, soldering defect identification in printed circuit boards, social distancing and face mask violation detection, and finger vein recognition. His work frequently incorporates convolutional neural networks (CNNs), YOLO object detection models, and generative adversarial networks (GANs) for data augmentation and classification tasks. He is also interested in explainable AI (XAI) techniques, especially for medical applications like osteosarcoma survival prediction. A major portion of his research contributes to agriculture, security, and industrial automation. His multidisciplinary approach combines physics, electronics, and machine learning, enabling holistic solutions across diverse domains. Dr. Asaari aims to enhance system robustness and real-time performance, bridging the gap between academic theory and operational deployment in smart technologies.
Award and Honor🏆
Dr. Mohd Shahrimie Mohd Asaari has garnered recognition for his impactful research through numerous competitive grants and national-level consultancy roles. He has been a principal investigator and co-investigator on various prestigious Malaysian funding schemes, including the Fundamental Research Grant Scheme (FRGS), Research University Team Grant (RU TEAM), and industry-matching grants—collectively valued at several hundred thousand Malaysian Ringgit. Notable projects include the development of AI systems for poultry mating detection, social distancing monitoring, finger vein recognition, and sustainable agriculture. He has been entrusted with leading consultation projects by national bodies such as CyberSecurity Malaysia and the Malaysia Productivity Corporation. Additionally, Dr. Asaari holds certifications such as HRDC Certified Trainer and Intel’s CREST AI for Youth Trainer, signifying his contributions to capacity building. His research has been published in reputable journals such as IEEE Access, Neurocomputing, and the ISPRS Journal of Photogrammetry and Remote Sensing, further affirming his excellence in scholarly and applied research.
Research Skill🔬
Dr. Mohd Shahrimie Mohd Asaari possesses a robust set of research skills that span deep learning, hyperspectral image analysis, signal processing, biometric recognition, and embedded system design. He is proficient in developing and deploying convolutional neural networks (CNNs), YOLO-based object detection algorithms, and GANs for tasks such as image segmentation, classification, and data augmentation. His skills also extend to hardware-level experimentation, particularly in implementing AI models on FPGAs and real-time systems for defect and biometric recognition. Dr. Asaari demonstrates expertise in feature fusion, dimensionality reduction, and spectral correction, especially for plant stress assessment and agricultural applications. In addition, he has experience with explainable AI frameworks and intelligent sensing technologies. He actively uses programming languages and tools such as Python, MATLAB, and embedded C/C++ for algorithm development and system integration. His ability to transition research from conceptual design to real-world applications reflects his strong applied research capabilities.
Conclusion💡
Dr. Mohd Shahrimie Mohd Asaari stands out as a highly competitive candidate for the Best Researcher Award. His broad interdisciplinary research, consistent funding success, and contributions to both academia and industry mark him as a researcher of significant impact and promise. To further strengthen his future candidacy, greater emphasis on technology commercialization, research leadership at national level, and mentorship outcomes is recommended.
Publications Top Noted✍
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Title: Fusion of band limited phase only correlation and width centroid contour distance for finger based biometrics
Authors: MSM Asaari, SA Suandi, BA Rosdi
Year: 2014
Cited by: 374
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Title: Close range hyperspectral imaging of plants: A review
Authors: P Mishra, MSM Asaari, A Herrero-Langreo, S Lohumi, B Diezma, et al.
Year: 2017
Cited by: 357
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Title: Close-range hyperspectral image analysis for early detection of stress responses in individual plants
Authors: MSM Asaari, P Mishra, S Mertens, S Dhondt, D Inzé, et al.
Year: 2018
Cited by: 162
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Title: Analysis of hyperspectral images for detection of drought stress and recovery in maize
Authors: MSM Asaari, S Mertens, S Dhondt, D Inzé, N Wuyts, P Scheunders
Year: 2019
Cited by: 100
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Title: Fusing spectral and textural information in NIR hyperspectral imaging to improve green tea classification
Authors: P Mishra, A Nordon, MSM Asaari, G Lian, S Redfern
Year: 2019
Cited by: 65
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Title: Hand gesture tracking system using Adaptive Kalman Filter
Authors: MSM Asaari, SA Suandi
Year: 2010
Cited by: 47
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Title: Precise detection for dense PCB components based on modified YOLOv8
Authors: Q Ling, NAM Isa, MSM Asaari
Year: 2023
Cited by: 45
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Title: Non-destructive analysis of plant physiological traits using hyperspectral imaging: A drought case study
Authors: MSM Asaari, S Mertens, L Verbraeken, S Dhondt, D Inzé, et al.
Year: 2022
Cited by: 43
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Title: Adaptive Kalman Filter Incorporated Eigenhand (AKFIE) for real-time hand tracking
Authors: MS Mohd Asaari, BA Rosdi, SA Suandi
Year: 2015
Cited by: 30
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Title: Intelligent biometric group hand tracking (IBGHT) database
Authors: MSM Asaari, BA Rosdi, SA Suandi
Year: 2014
Cited by: 20
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Title: SDD-Net: Soldering defect detection network for printed circuit boards
Authors: Q Ling, NAM Isa, MSM Asaari
Year: 2024
Cited by: 17
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Title: Embedded operating system and industrial applications: A review
Authors: YH Hee, MK Ishak, MSM Asaari, MTA Seman
Year: 2021
Cited by: 15
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Title: GANs for image augmentation in farming: A review
Authors: Z ur Rahman, MSM Asaari, H Ibrahim, ISZ Abidin, MK Ishak
Year: 2024
Cited by: 12
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Title: Explainable AI for cancer diagnosis: A systematic review
Authors: YA Mohamed, BE Khoo, MSM Asaari, ME Aziz, FR Ghazali
Year: 2024
Cited by: 12
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Title: Vision-based hand detection and tracking using fusion of KCF and SSD
Authors: MN Haji Mohd, MS Mohd Asaari, O Lay Ping, BA Rosdi
Year: 2023
Cited by: 11