AI/ML Engineer specializing in GenAI, LLMs, RAG, AI agents, and production-ready intelligent applications.

Sai Bhavya Yangoti  • Peerlist

- Designed a two-stage malware analysis pipeline using fine-tuned local LLMs to perform malware detection and family-wise classification from sandbox execution logs. - Achieved 97.85% detection accuracy and 97.13% classification accuracy through LLM-based behavioral pattern analysis. - Authored and submitted a research paper titled “MALLM: Malware Analysis with Large Language Models” to SN Computer Science (Springer) — currently under peer review.

MALLM: Malware Analysis using Large Language 

- Built an end-to-end crack detection system using SegFormer for pixel-level segmentation, achieving 97.39% pixel accuracy and 73.23% Dice score. - Implemented crack width estimation, severity classification and built a FastAPI backend and Dockerized the application for scalable deployment. - Developed an interactive Gradio demo and deployed it on Hugging Face Spaces for real-time model visualization and testing.