Headline

B.Tech CSE (AI) Graduate | AI/ML Engineer — Deep Learning & Medical Imaging | PyTorch, U-Net, XGBoost | Co-Author, Scientific Reports (Nature) — In Review

About

As a B.Tech (AI) graduate from Amrita Vishwa Vidyapeetham, I've spent the last two years going deep on applied machine learning: not just training models, but shipping them as usable, interpretable systems. I build deep learning systems that hold up under peer review — and security systems that assume attackers already have a quantum computer. What I bring: 🔹 Deep learning & medical imaging: co-authored "A Unified Deep Learning Framework for Multi-Organ Tumor Detection and Segmentation" (currently under peer review, Scientific Reports / Nature Portfolio) — a hybrid 2D/3D U-Net system spanning brain, liver, and lung imaging (BraTS, LiTS, LUNA16), with Grad-CAM explainability and Monte Carlo dropout uncertainty estimation, achieving Dice scores up to 0.87 🔹 ML + security systems: built a hybrid fraud detection and Post-Quantum Cryptography framework for Metaverse financial transactions — Random Forest/XGBoost risk classification feeding a selective Falcon-512/Dilithium2 signing pipeline, benchmarked for latency and throughput, with a live Streamlit dashboard 🔹 Published research: peer-reviewed paper on social media sentiment analysis (ICOFE-2024), benchmarking 6 models from Logistic Regression to BERT I'm now looking for an AI/ML Engineer, Data Engineer, Solution Engineer, or Implementation Engineer role where I can own the technical build AND the conversation with the people who'll use it. Open to opportunities — let's talk.

Location

Greater Bengaluru Area

AI stack

claude code

codex

langchain

langgraph

githubcopilot

huggingface

Education

Bachelor of Technology - BTech, Artificial Intelligence, Amrita Vishwa Vidyapeetham