Towards data-driven vulnerability prediction for requirements. - Sayem Mohammad Imtiaz; Tanmay Bhowmik (ESEC/SIGSOFT FSE, 2018)

SecureChange: An Automated Framework to Guide Programmers in Fixing Vulnerability. - Sayem Mohammad Imtiaz; Kazi Zakia Sultana; Tanmay Bhowmik (SEKE, 2020)

Mining Learner-friendly Security Patterns from Huge Published Histories of Software Applications for an Intelligent Tutoring System in Secure Coding. - Sayem Mohammad Imtiaz; Kazi Zakia Sultana; Aparna S. Varde (IEEE BigData, 2021)

Predicting Vulnerability for Requirements. - Sayem Mohammad Imtiaz; Md Rayhan Amin; Anh Quoc Do; Stefano Iannucci; Tanmay Bhowmik (IRI, 2021)

Decomposing a Recurrent Neural Network into Modules for Enabling Reusability and Replacement. - Sayem Mohammad Imtiaz; Fraol Batole; Astha Singh; Rangeet Pan; Breno Dantas Cruz; Hridesh Rajan (ICSE, 2023)

Design by Contract for Deep Learning APIs. - Shibbir Ahmed; Sayem Mohammad Imtiaz; Syeda Khairunnesa Samantha; Breno Dantas Cruz; Hridesh Rajan (ESEC/SIGSOFT FSE, 2023)

What kinds of contracts do ML APIs need? - Syeda Khairunnesa Samantha; Shibbir Ahmed; Sayem Mohammad Imtiaz; Hridesh Rajan; Gary T. Leavens (Empir. Softw. Eng., 2023)

Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot. - David O'Brien; Sumon Biswas; Sayem Mohammad Imtiaz; Rabe Abdalkareem; Emad Shihab; Hridesh Rajan (ICSE, 2024)

IRepair: An Intent-Aware Approach to Repair Data-Driven Errors in Large Language Models. - Sayem Mohammad Imtiaz; Astha Singh; Fraol Batole; Hridesh Rajan (Proc. ACM Softw. Eng., 2025)