Hello there!

I am a Doctoral Candidate in Computer and Information Science at the University of Delaware, where I also earned my M.S. My research advances trustworthy AI for healthcare by developing both predictive and generative models that improve clinical decision support and patient outcomes. I design graph-based learning frameworks for structured EHR modeling, as well as hallucination-aware, agentic large language model systems for reliable clinical text summarization. By integrating deep learning, knowledge graphs, and language models, I build clinically aligned AI systems that enhance decision-making efficiency, support proactive risk management, and enable safer deployment of generative models in real-world healthcare settings.

I earned my Bachelor’s degree in Computer Science and Engineering from Chittagong University of Engineering & Technology (CUET). Alongside my academic training, I gained hands-on industry experience as a Data Science Intern and Software QA Engineer, where I worked on real-world AI systems and large-scale data analysis projects. These experiences strengthened my ability to translate research ideas into practical, deployable solutions.

I am committed to advancing machine learning for healthcare, with a focus on generative AI, graph learning, and large language models. My goal is to develop reliable, clinically aligned AI systems that address real-world challenges and contribute to measurable improvements in patient care.