About Me

Biography

I’m a Ph.D. Candidate in Computer Science at the University of Southern California, advised by Professor Nenad Medvidović. My research focuses on using AI and deep learning to improve software security—specifically, developing techniques that can automatically detect and mitigate vulnerabilities during software development. The goal of my work is to make software systems more resilient and to help developers build secure applications from the start.

Before joining USC, I was a Lecturer at the University of Liberal Arts Bangladesh (ULAB), where I taught software engineering, algorithms, and data structures. Earlier, I worked as a Software Engineer at Samsung Research & Development Institute Bangladesh (SRBD), where I developed frontend solutions for Samsung’s network device management systems. During my internship at SRBD, I also built a prototype Generative Adversarial Network (GAN) for Neural Style Transfer on images.

My experience spans software engineering, applied AI, and research-driven innovation, with a focus on bridging the gap between cutting-edge research and practical, real-world applications.

Research Interests

My research spans several interconnected areas:

• Software Security
• Vulnerability Detection and Analysis
• Software Engineering
• AI

I am particularly interested in leveraging AI techniques to develop secure software systems.

Education

• Ph.D. in Computer Science, University of Southern California, 2026 (Expected)
  Dissertation: "Improving Deep Learning based Vulnerability Detection"
  Advisor: Professor Nenad Medvidović
• M.S. in Computer Science, University of Southern California, 2025
  
• B.S. in Software Engineering, University of Dhaka, 2019
  

Academic Community Service

Program Committee Member:

• FSE–Artifacts Track (2025)
• SVM Workshop (2026)

Reviewer:

• EASE 2025
• AAAI 2026

External Interests

Outside of research, I enjoy cooking, hiking, reading, and listening to music. I also follow soccer and my favorite team is Liverpool FC.