Assistant Professor
Department of Information Sciences & Technologies

Email: [email protected]
Phone: (616) 331-3884
Office: MAK D-2-216

Education
Ph.D., Computer Engineering, Polytechnique Montréal, 2014

Asynchronous courses: CIS 678 - 02

Dr. Kamrul Hasan is an Assistant Professor in the College of Computing, where he brings extensive expertise in machine learning, data science, and applied artificial intelligence. His research focuses on a broad range of areas, including semi-supervised active learning, generative AI, natural language processing, computer vision, and the application of machine learning in precision agriculture, health informatics and cybersecurity. In addition to his research, Dr. Hasan is passionate about preparing students for real-world challenges by integrating hands-on learning, industry-relevant projects, and emerging technologies into the classroom. 

His extensive industry experience, combined with an interdisciplinary research approach, equips students to apply AI and data science solutions across diverse domains such as healthcare, agriculture, and cybersecurity. Dr. Hasan actively collaborates with both academic and industry partners to advance innovative research and practical applications that address pressing global challenges. His recent publication, "Status of Malaria in the African Continent – Data Mining Insights from Heterogeneous, but Interrelated Data Sources" (CSIT, 2024), reflects his ongoing commitment to solving global challenges through intelligent data analysis and integration. 

Beyond his academic and research activities, Dr. Hasan enjoys traveling, gardening, and playing badminton and cricket. His diverse interests and collaborative approach enrich both his teaching and research.

• Status of Malaria in the African Continent - Data Mining Insights from Heterogeneous, but Interrelated Data Sources, Ken Muchira, Hemalatha Sabbineni, John Moses Bollarapu, and Kamrul Hasan, Computer Science & Information Technology (CSIT), 2024. (https://aircconline.com/csit/papers/vol14/csit141401.pdf)
• Integrated Predictive Maintenance Tool for Business Aircrafts Through Continuous Monitoring in Practice (abstract), Rai, A., Macdonald, E., Hasan, K., Liu, Q., Hresko, J., Mendoza, J., Rabusseau, G., Yacout, S., & Adulyasak, Annual Symposium, Airline Group of the International Federation of Operational Research Societies, AGIFORS, 2023.

• Precision Farming: Dancun Juma, Thrinadh Tellagorla, and Puneeth Kumar Amudala
• Deep Learning: TimeGPT (Dinesh Kumar Raju Kattunga), Transformers (Arnold Muiruri)
• Cybersecurity: AI-Driven Red Teaming on Non-Deterministic Systems (Joyce Malicha), Zero Day Attack (Hilda Ogamba, Victor Bungei, and Melanie Gateru)
• Data Mining: Dental Implant Failure (Sai Sarika Vemana), Environmental Sustainability (Cliff Mutegi)

Updated Research Opportunities:

• Precision Farming: In this project, we are building certain supporting tools for farmers aiming to reduce their cost, improve throughput, and leave less (negative) environmental impacts.
• Distributed Semi Supervised Learning: Are you curious about the latest machine learning tools, techniques, and beyond? In this research, we are developing models that can learn both from labeled and unlabeled data and work in a distributed fashion pursuing a coordinated and common objective.
• Knowledge Discovery and Data Mining (also directed towards potential collaborators): If you are an expert in a certain field and require data science assistance, please give us a shout. During my tenure as a Data Scientist for multiple North American companies, I have contributed in building AI products for various domains: Natural Language Processing, Computer Vision, Supply Chain, Aviation, Cybersecurity, and Healthcare.