Research
Dr. Akter's research sits at the intersection of software security and Large Language Models (LLMs), with a particular emphasis on automating the detection and mitigation of software vulnerabilities. She applies LLMs and deep learning techniques to identify vulnerabilities in source code, software supply chains, and adversarial settings.
Research Interests
Software Security
Natural Language Processing (NLP)
Grants & Funded Projects
✓ Funded — 2025
“Efficient Neuro-Symbolic LLM-Driven Framework for Real-Time Detection and Mitigation of Software Vulnerabilities in Autonomous Spacecraft Systems”
NASA Michigan Space Grant Consortium (MSGC) Seed Grant · PI: Mst Shapna Akter
$5,000 + $5,000 Oakland University match · May 1, 2025 – December 30, 2025