S. M. Mahedy Hasan
Doctor of Philosophy (PhD) Student , Computer Science
Idaho State University, ID, USA
Member, Software Engineering and Cybersecurity Research Team (SECReT)
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Assistant Professor (On Study Leave), Computer Science & Engineering
Rajshahi University of Engineering & Technology (RUET) Rajshahi-6204, Bangladesh.
📧 smmahedyhasan@isu.edu || mahedy@cse.ruet.ac.bd
🙋ABOUT ME
I am S. M. Mahedy Hasan, a PhD Researcher in Computer Science at Idaho State University, USA, and an Assistant Professor (on study leave) in Computer Science and Engineering at Rajshahi University of Engineering & Technology (RUET), Bangladesh, one of the country’s leading engineering institutions. I am deeply passionate about teaching and research, with significant contributions in both academic and professional spheres within the field of computer science. I earned my B.Sc. in Computer Science and Engineering from RUET and continued my higher studies in the same discipline. Over the years, I have been actively involved in guiding undergraduate and postgraduate students, helping them develop strong skills in programming, problem-solving, and research methodologies.
📢 RECENT NEWS AND UPDATES
Mahedy and his co-authors received the 3rd Best Paper Award at ISPR-2024 conference, which was held in Turkey on May 27, 2024.
My research focuses on the application of Machine Learning (ML) and Deep Learning (DL) to solve real-world problems across biomedical science, education, cyber security and software engineering. I am particularly interested in designing intelligent systems that can process large, complex datasets to uncover hidden patterns, support human decision-making, and drive innovation in critical domains.
I work on developing deep learning models for disease detection, classification, and image segmentation using medical imaging data such as X-rays, MRIs, and CT scans. The goal is to create AI-assisted diagnostic tools that can help healthcare professionals make faster, more accurate, and cost-effective clinical decisions, ultimately improving patient care and outcomes.
My research in this area focuses on analyzing student learning behavior and performance data to predict outcomes and design personalized learning pathways. By applying ML algorithms, I aim to build intelligent tutoring systems that can provide early interventions, recommend adaptive learning strategies, and ensure that students receive the support they need to succeed in their academic journey.
Within software engineering, my work explores how ML/DL can be integrated into software development, testing, maintenance, and defect prediction. I am particularly interested in empirical studies that leverage data from real-world software projects to understand developer behavior, improve productivity, and enhance software reliability.
In the field of cybersecurity, I investigate how ML models can be applied to detect anomalies, prevent cyber-attacks, and secure critical infrastructures against evolving threats.
🔑 Key Domains
⚡ Machine Learning & Deep Learning
🩺 Medical Image Analysis
📚 Educational Data Mining
💻 Empirical Software Engineering
🔐 Cybersecurity
👁️ Computer Vision
🛠️ TRAINING AND WORKSHOPS
