Abid Mehmood

Dr. Abid Mehmood serves as an Associate Professor at The Beacom College of Computer & Cyber Sciences, Dakota State University, leveraging over 20 years of combined academic and industry expertise to advance artificial intelligence applications in critical domains including healthcare, precision agriculture, and surveillance systems.

His educational foundation includes:

• Ph.D. in Computer Science from Universiti Teknologi Malaysia (2014)
• M.Sc. in Computer Science from Quaid-i-Azam University (2001)
• B.Sc. in Computer Science from University of Peshawar (1998)

Dr. Mehmood's research centers on applied machine learning and deep learning, with pioneering work in computer vision for medical diagnostics (skin lesion classification, glaucoma detection), precision agriculture solutions (automated fruit disease identification, crop yield estimation), and surveillance technologies (real-time anomaly detection in video streams). His predictive analytics expertise extends to healthcare sentiment analysis, financial forecasting, and driver behavior monitoring, consistently translating theoretical AI advances into practical implementations across diverse sectors.

Analysis of his 15 most recent publications (2021-2024) reveals a pronounced interdisciplinary focus, with 60% dedicated to healthcare applications (medical imaging diagnostics), 27% to agricultural technology, and 13% to surveillance/security systems. This trajectory demonstrates strategic alignment with societal needs while maintaining technical rigor in computer vision and deep learning architectures.

No scientific awards were documented in the provided materials.

Dr. Mehmood has secured substantial research funding through 14 competitively awarded grants (2021-2024) totaling SAR 400,000+ from Saudi Arabian institutions, including King Faisal University and the Ministry of Education. His grant portfolio demonstrates exceptional breadth:

• Healthcare Innovation: Driver depression monitoring systems, skin lesion classification frameworks, glaucoma diagnostics, and obesity/fatty liver correlation studies
• Agricultural Technology: Automated fruit disease identification and crop yield estimation using AI-driven remote sensing
• Security Systems: Lightweight anomaly detection frameworks for video surveillance
• Cross-Domain Applications: Stock price prediction models, vaccine sentiment analysis, and aspect-oriented programming solutions