SAUMENDU ROY (SAUMO)
Doctoral Researcher in Software Engineering & Explainable AI
Building Trustworthy, Human-Centered AI for Software Engineering
I explore the intersection of Software Engineering, Machine Learning, and Explainable AI to create research that is reliable, practical, and easy to understand for both academia and industry.
RESEARCH & PUBLICATIONS
A curated collection of journal publications, conference proceedings, and under-review research in software engineering, explainable AI, cloud computing, IoT, and intelligent systems.
Journal Publications
Conference Proceedings
Under Review
Travelling and Networking
Webinars and Videos
Academic Expertise & Research Impact
Academic Excellence & Research Innovation
Saumendu Roy is a Doctoral researcher in Software Engineering specializing in explainable AI and machine learning for software systems. His work focuses on improving the transparency, reliability, and practical usability of AI-driven tools, particularly in software defect prediction.
Professional Experience
Experienced in university teaching, research supervision, and publishing in leading software engineering and AI venues.
Advanced Research
Active research in explainable AI, software defect prediction, machine learning, and human-centered intelligent systems.
Teaching Excellence
Teaching core computer science courses, including Structured Programming, Data Structures, Algorithms, and Software Engineering, while mentoring students in research projects.
Innovation & Development
Guiding innovative research projects in explainable AI, software engineering, and machine learning, with a focus on real-world impact and collaboration.
Discover My Journey
I am a PhD candidate in Computer Science at the University of Saskatchewan, specializing in Explainable AI (XAI) and AI-driven software engineering. My research focuses on AI reliability, interpretability, and developer-centered AI systems, with particular emphasis on understanding and improving the stability and trustworthiness of machine learning explanations.
With first-author publications in leading software engineering venues such as ICSE, ICSME, and EASE, my work aims to bridge the gap between artificial intelligence and software engineering, ensuring that AI-assisted development is reliable, transparent, and practical for real-world software systems.
Beyond research, I have extensive teaching experience as an Instructor and Teaching Assistant, mentoring students in research, software engineering, and machine learning. I have also taken leadership roles in academic and student initiatives, contributing to collaborative research and community engagement.
I am open to research collaborations, industry partnerships, and academic opportunities related to Explainable AI, trustworthy machine learning, and AI-enabled software engineering.
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Learn more about Saumendu Roy’s academic work, research contributions, and teaching experience.