Saikat Mondal

Research

My research strengthens the global programming knowledge that powers both millions of developers and modern AI systems such as ChatGPT. I focus on improving the reliability, reproducibility, and trustworthiness of community-driven platforms such as Stack Overflow through large-scale empirical studies and the development of intelligent, practical tools.

I build systems that detect and repair security vulnerabilities, predict and prevent low-quality edits, generate helpful code explanations, and resolve moderation inconsistencies with high accuracy. My work directly improves the quality of the answers developers depend on, reducing costly debugging and elevating the data used to train AI coding models.

I also analyze community behaviors to promote equity, accessibility, and high-quality knowledge sharing. I design research and tools that make global programming knowledge safer and more dependable, creating a stronger foundation for both human learning and AI-assisted software development.

Building on this foundation, my current research focuses on the transformative role of Large Language Models (LLMs) in software engineering. While models such as ChatGPT, Gemini, MetaAI, and DeepSeek automate many development tasks, my goal is to move beyond automation and build true human–AI collaboration. I aim to combine the strengths of AI and human expertise to offer trustworthy, explainable, and context-aware assistance.

I envision LLMs as intelligent companions that provide validated insights, deepen understanding, and support collaborative problem-solving. A central part of this vision is fostering a learning ecosystem that encourages diverse solution paths and strengthens developer confidence. My goal is to create AI systems that developers trust, learn from, and rely on to build robust, inclusive, and sustainable software.

Leadership & Community Service

I have served academic, professional, and community organizations in a broad range of leadership and service roles, developing strong strengths in organizational leadership, coordination, and community building. My experience includes elected and executive positions within graduate and alumni councils, long-term leadership in departmental and laboratory initiatives, and mentoring roles that support students from diverse backgrounds. Notably, I have served as President, Vice President, and Representative of the Computer Science Graduate Council, Lead Organizer of academic and research events, a mentor in national diversity-focused education programs, and a founder, advisor, and coordinator of educational and technology outreach initiatives. Across these roles, I am committed to advancing inclusive leadership, student empowerment, and sustainable community impact.

Teaching

My teaching bridges industry and academia to deliver practical, authentic learning experiences. My mission is to empower students with relevant skills while cultivating a supportive, inclusive learning environment where all students—regardless of background—feel valued, capable, and positioned to succeed.

I began my formal teaching career in 2012 as a full-time lecturer (later promoted as Assistant Professor) in the Department of Computer Science and Engineering at Khulna University, Bangladesh. Prior to academia, I worked as a software engineer in the Advanced R&D Division at Samsung R&D Institute Bangladesh, and this experience continues to enrich my pedagogy with real-world insights.

Over seven years, I supervised 100+ software development projects and taught upper-division courses including Artificial Intelligence and Software Engineering (along with core CS courses). I emphasize interactive learning through hands-on labs, project-based work, structured Q&A, peer learning, and open-book assessments that reward critical thinking.

At the University of Saskatchewan, I served as Instructor & Lead Coordinator for CMPT 470/816: Advanced Software Engineering (Winter 2025), designing an inclusive, employment-focused curriculum covering modern topics such as AI in Software Engineering, Trustworthy & Responsible AI, Low-code/No-code Development, Cloud-native Systems, DevOps, Software Process Automation, and Data-Driven Decision Making.

I am committed to effective and continuously improving teaching and have completed formal training in pedagogy and assessment, including programs in Teaching Methodology and Research Methodology * as well as advanced university-level workshops on Teaching, Learning & Assessment †. These experiences have strengthened my foundation for engaging, inclusive, and evidence-based teaching.

Review

I serve as a reviewer and program committee member for top-tier conferences and journals in Software Engineering. My conference service includes roles as Program Committee Member for the International Conference on Software Analysis, Evolution and Reengineering (SANER 2026 — ERA Track) , Junior Program Committee Member for the International Conference on Mining Software Repositories (MSR 2026) , MSR 2025 , and MSR 2024 , as well as Shadow Program Committee Member for the International Conference on Software Engineering (ICSE 2025) . I also served as a Program Committee Member for the Software Analytics Research (SOAR) Symposium 2025 .

In addition, I regularly review for leading journals, including IEEE Transactions on Software Engineering (TSE), Empirical Software Engineering (EMSE), ACM Transactions on Software Engineering and Methodology (TOSEM), Information and Software Technology (IST) (1 review), Journal of Systems and Software (JSS), and Journal of Software: Evolution and Process (JSME).