Current Engagement

As a Ph.D. student at Iowa State University, I am currently conducting research in AI Engineering under the guidance of Dr. Hridesh Rajan in the Software Design lab. My research focuses on enhancing the evolvability and modularity of deep learning models, with a specific emphasis on leveraging modularity to improve the maintainability, comprehensibility, and reusability of large-scale models such as language models (LLMs). In my most recent study, presented at the International Conference on Software Engineering in 2023, I investigated the decomposition of sequential models, demonstrating the reusability facilitated by modularity.

Short Biography

I am currently pursuing my Ph.D. in the Department of Computer Science at Iowa State University, where I am a fourth-year student. I am currently a member of the Laboratory for Software Design, where I work under the guidance and supervision of Dr. Hridesh Rajan.

Prior to joining Iowa State, I obtained my master’s degree in computer science from Mississippi State University, which provided me with valuable research opportunities. During my time there, I actively contributed to the field of software engineering, focusing specifically on promoting secure software development. My research efforts resulted in several publications that have advanced the understanding and practices in this area. Furthermore, I had the opportunity to engage in interdisciplinary collaboration between transportation engineering and computer science, working alongside Dr. Pengfei Li. Together, we proposed a novel analysis tool for examining traffic signal coordination, bridging the gap between these two domains.

My journey in computer science began with a bachelor’s degree from Chittagong University of Engineering & Technology, where I worked under the guidance of Dr. Koushik Deb. My undergraduate thesis concentrated on the development of a robust automated video surveillance system. The objective was to create a system capable of adapting to various real-world scenarios, significantly reducing object tracking time.