Md. Haidar Sharif is an educator and researcher specializing in artificial intelligence, computer vision, and deep learning, with a strong focus on video analytics, crowd behavior understanding, and intelligent surveillance systems. He is currently affiliated with the University of the Cumberlands, where he teaches computer science courses and contributes to student development in data science and AI-related fields.
His research spans machine learning-based event detection, anomaly detection in crowd scenes, and computational methods for tracking and analyzing dynamic visual data. He has published extensively in peer-reviewed journals and conferences, including work on deep crowd anomaly detection, laser-based privacy-preserving surveillance systems, and eigenvalue-based event detection in video streams.
Dr. Sharif has held academic and research positions across multiple international institutions in Europe, the Middle East, and the United States. His work integrates theoretical modeling with applied artificial intelligence, particularly in real-time systems and high-performance computing environments.
Beyond academia, he is engaged in developing advanced learning materials that bridge foundational AI concepts with real-world applications. He is committed to helping students build practical skills in machine learning, programming, and data-driven problem solving.
Outside of his academic work, he enjoys exploring emerging technologies and spending time with his family in Maryland.