I am a Ph.D. candidate in Computer Science at William & Mary, where my research centers on leveraging Artificial Intelligence (AI) to support and enhance Software Engineering (SE) practices. My current work explores how deep learning models—especially large language models—can be optimized and adapted for code-related tasks such as code summarization, generation, and quality assessment. I am particularly interested in improving the efficiency, robustness, and interpretability of these models in real-world development workflows.

I am currently working under the supervision of Dr. Antonio Mastropaolo as a member of the AURA Lab, where I contribute to research on AI4SE with a focus on optimizing the performance and adaptability of code-focused AI models.

Before starting my Ph.D., I earned a Bachelor of Science in Computer Science and Engineering from Daffodil International University, graduating in the top tier of my class. My early research explored supervised and deep learning techniques across a variety of real-world problems, contributing to several peer-reviewed publications.

Alongside my academic journey, I also served as a full-time Lecturer at Daffodil International University, where I mentored undergraduate students and contributed to a collaborative teaching and research environment. I am passionate about impactful, collaborative research and regularly engage in conferences, seminars, and innovation events to exchange ideas with the broader scientific community.