Mr. Md. Khabir Uddin Ahamed – Lecturer, Jamalpur Science and Technology University, Bangladesh.
Md. Khabir Uddin Ahamed is a dynamic Bangladeshi academic and researcher in Computer Science & Engineering. Known for his contribution to data-driven technologies, he has authored several impactful publications in domains like machine learning, computer vision, and AI. With strong analytical and problem-solving skills, he’s actively engaged in academic instruction and cutting-edge research. He is currently a Lecturer at Jamalpur Science and Technology University. Khabir combines technical prowess with a passion for innovation, contributing to both academic and social sectors through technological projects and scientific publications.
Publication Profile
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Education Background
Md. Khabir Uddin Ahamed holds a B.Sc. and M.Sc. in Computer Science & Engineering from Jagannath University, where he secured the 2nd merit position in both undergraduate and postgraduate programs. His academic foundation is further solidified by earlier education from Govt. Science College and BCSIR High School under the Dhaka Board. His strong educational background has shaped his ability to undertake impactful research, particularly in artificial intelligence and data science, and contributed to his success as a university lecturer and researcher.
Professional Experience
Khabir began his teaching career as a Lecturer in the Department of Computer Science & Engineering at Bangladesh University (2022–2023). Since December 2023, he has been serving as a Lecturer at Jamalpur Science and Technology University. In his academic roles, he has taught core courses, guided student research, and contributed to institutional development. He has also participated in multiple training programs under the University Grants Commission of Bangladesh, focusing on modern teaching methods, digital compliance, and administrative tools for higher education.
Awards and Honors
While there are no direct individual award mentions, Khabir’s academic distinction—earning the 2nd merit rank in both B.Sc. and M.Sc.—reflects his scholastic excellence. Furthermore, his publications have earned significant citations, indicating international recognition of his research contributions. His training certifications from the University Grants Commission and Bangladesh Accreditation Council add further credibility to his professional qualifications, reflecting national-level validation and involvement in academic quality assurance systems.
Research Focus
Md. Khabir Uddin Ahamed’s research spans several high-impact areas within computer science, including machine learning, deep learning, data science, computer vision, and blockchain technology. His recent work has explored disease detection using deep learning, behavioral analysis on social media, and intelligent transportation systems. He is passionate about leveraging AI for societal benefit and continues to explore innovative applications of technology to solve real-world problems in agriculture, health, and cybersecurity through interdisciplinary collaboration.
Conclusion
Md. Khabir Uddin Ahamed is a promising academic and researcher with a solid foundation in Computer Science & Engineering, a growing portfolio of peer-reviewed publications, and a passion for teaching and innovation. His involvement in modern AI applications and educational development initiatives makes him a valuable asset to both the academic and research communities. As his research contributions continue to gain citations and recognition, he is poised to become a leading figure in applied AI and intelligent systems research.
Top Publications
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A deep learning approach using effective preprocessing techniques to detect COVID-19 from chest CT-scan and X-ray images
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DeepCrop: Deep learning-based crop disease prediction with web application
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An ensemble machine learning based bank loan approval predictions system with a smart application
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DTLCx: an improved ResNet architecture to classify normal and conventional pneumonia cases from COVID-19 instances with Grad-CAM-based superimposed visualization
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Diagnostics, 2023
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Cited by: 22 articles
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Identification of abusive behavior towards religious beliefs and practices on social media platforms
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An Integrated Deep Learning Model for Skin Cancer Detection Using Hybrid Feature Fusion Technique
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Cascaded intrusion detection system using machine learning