Md Haidar Sharif

Haidar Sharif

Professor

Computer and Data Science
hsharif@captechu.edu

Md Haidar Sharif is a Full-time Faculty Member in the Department of Computer Science and Cybersecurity at Capitol Technology University. His teaching and research interests include artificial intelligence (AI), machine learning (ML), deep learning (DL), computer vision (CV), and high-performance computing (HPC).

Dr. Sharif earned his PhD in Computer Science from Université de Lille 1, France, in 2010. He received his MSc in Computer Science from Universität Duisburg-Essen, Germany, in 2006, and his BSc in Electronics and Computer Science from Jahangirnagar University, Bangladesh, in 2001. His international academic background includes extensive experience in research, teaching, and interdisciplinary collaboration. His research focuses on AI, ML, DL, CV, and HPC. His work has been published in peer-reviewed journals, including IEEE Access, Sensors, Electronics, Pattern Recognition, and Artificial Intelligence Review. He is also the author of Sundry Applications and Computations of sin() and cos(), a textbook examining computational applications of trigonometric functions in computer architecture and numerical computation. He conducted postdoctoral research in AI, with a focus on DL.

Dr. Sharif has extensive teaching experience in computer science, AI, ML, DL, and data-related disciplines. His teaching philosophy emphasizes connecting theoretical foundations with practical applications. He uses programming, real-world datasets, ML tools, and hands-on projects to help students develop computational knowledge, analytical thinking, and practical problem-solving skills.

At Capitol Technology University, Dr. Sharif contributes to teaching and curriculum development, including AI education. He is committed to preparing students to understand, implement, evaluate, and responsibly apply modern AI technologies. His professional goals include advancing AI education and research and developing intelligent, data-driven solutions to real-world challenges.

Areas of Expertise

  • Computer and Data Science
  • Machine Learning
  • Artificial Intelligence
  • High-Performance Computing

Education

  • PhD, Computer Science, Université de Lille 1, France, 2010
  • MSc, Computer Science, Universität Duisburg-Essen, Germany, 2006
  • BSc, Electronics and Computer Science, Jahangirnagar University, Bangladesh, 2001

Selected Publications

  • Sharif, M. H., Jiao, L., & Omlin, C. W. (2025). Deep crowd anomaly detection: State-of-the-art, challenges, and future research directions. Artificial Intelligence Review.
  • Sharif, M. H., Jiao, L., & Omlin, C. W. (2023). CNN-ViT supported weakly-supervised video segment-level anomaly detection. Sensors, 23(18), 7734.
  • Shehu, H. A., Sharif, M. H., Uddin Sharif, M. H., Datta, R., Tokat, S., Uyaver, S., Kusetogulları, H., & Ramadan, R. A. (2021). Deep sentiment analysis: A case study on stemmed Turkish Twitter data. IEEE Access, 9, 56836–56854.
  • Classification of breast cancer histopathological images using DenseNet and transfer learning. Computational Intelligence and Neuroscience, 2022, Article 8904768.
  • Sharif, M. H., et al. Low-cost pupil center localization algorithm based on maximized integral voting of circular hollow kernels. The Computer Journal, 62(7), 1001–1015, 2019.
  • Sharif, M. H., Despot, I., & Uyaver, S. (2018). A proof of concept for home automation system with implementation of the Internet of Things standards. Periodicals of Engineering and Natural Sciences, 6(1), 95–106.
  • Sharif, M. H., Uyaver, S., & Zerdo, Z. (2018). Classification and detection of various geographical features from satellite imagery. Periodicals of Engineering and Natural Sciences, 6(1), 84–94.
  • Sharif, M. H., et al. An entropy approach for abnormal activities detection in video streams. Pattern Recognition, 45(7), 2543–2561, 2012.
  • Sharif, M. H., et al. High-performance mathematical functions for single-core architectures. Journal of Circuits, Systems, and Computers, 23(4), 1450051, 2014.
  • Sharif, M. H. Sundry Applications and Computations of sin() and cos() — textbook on computational applications of trigonometric functions, including applications related to computer architecture and numerical computation.

Organizations & Affiliations

  • Capitol Technology University — Full-time Faculty
  • University of Maryland Global Campus (UMGC) — Adjunct Faculty
  • Institute of Electrical and Electronics Engineers (IEEE) — Member

‪Portfolio/Personal Website