Sadif Ahmed is currently serving as a Lecturer in the Department of Computer Science and Engineering at BRAC University. He earned his Bachelor of Science (BSc. Engg.) degree in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET) in 2025 He has served as a Research Assistant at BUET, where he worked on Software Engineering Automation and Web UI automation, contributing to projects that enhance the reliability and security of software systems through intelligent tooling.

During his undergraduate studies, Sadif also conducted impactful research on secret breach detection in source code and issue reports using Large Language Models. He has developed a wide range of practical tools and platforms in areas like blockchain, home automation, and anime data indexing.

His research interests span Software Engineering and Security, Large Language Models, and Developer Privacy. He is particularly passionate about using Machine Learning and Natural Language Processing techniques to advance software quality, reliability, and confidentiality.

Sadif is grateful for the academic mentors and collaborative opportunities that have supported his journey. Driven by a strong enthusiasm for both research and development, he aims to contribute meaningfully to the academic and software engineering communities. Outside of academics, he enjoys sports, gaming and watching anime and tv shows.

1. Google Scholar Link
   ·Secret Breach Prevention in Software Issue Reports

• Authors: Zahin Wahab, Sadif Ahmed, Md Nafiu Rahman, Rifat Shahriyar, Gias Uddin
• Venue: arXiv preprint (Computer Science – Software Engineering, Security), October 31, 2024
• Summary: Proposes a hybrid approach combining regex and language models (BERT/RoBERTa) for detecting sensitive data leaks (e.g., API keys, credentials) in issue tracker descriptions. Includes a curated benchmark dataset (25,000 issue reports) and a browser extension (SBMBot) for real-time prevention.
  Read Here

· Secret Breach Detection in Source Code with Large Language Models

• Authors: Md Nafiu Rahman, Sadif Ahmed, Zahin Wahab, SM Sohan, Rifat Shahriyar
• Venue: Accepted at Technical Track of ESEM'25 (ACM / IEEE International Symposium on Empirical Software Engineering and Measurement 2025)
• Summary: Presents a hybrid method utilizing regex-based extraction followed by LLM-based classification to identify leaked secrets in source code. Demonstrates high performance using fine-tuned open-source LLMs like LLaMA‑3.1 and Mistral‑7B (F1 up to ~0.9852)
  Read Here

1. Research Assistant
2. Department of Computer Science & Engineering
3. Bangladesh University of Engineering and Technology (BUET)
4. (February 2024 – June 2024)
   Lecturer
5. Department of Computer Science and Engineering
6. School of Data and Sciences,
7. BRAC University (2024 - Present)

Summer 2025
                  Computer Architecture CSE 340
                  Software Engineering CSE 470
                  System Analysis and Design CSE 471  

1. Software Engineering & Security

• Secret breach detection and prevention in:
  • Issue tracker reports
  • Source code repositories
• Automation of secure development workflows using machine learning and rule-based methods.
• Developer-centric security tools (e.g., browser extensions for leak prevention).

Large Language Models (LLMs)

• Application of transformer-based models (BERT, RoBERTa, LLaMA, Mistral) in software engineering tasks.
• Fine-tuning LLMs for:
  • Code classification and analysis
  • Context-aware security detection
• Research on hybrid techniques (regex + LLM) for high-accuracy predictions.

Web UI Automation

• Research assistantship involving automation of UI workflows and testing, using tools and scripts to simulate or validate user interactions.

Machine Learning & NLP Applications

• Use of deep learning in natural language and code analysis.
• Interest in developer privacy, computational linguistics, and intelligent tooling for programmers.