Data Science student. Mini project at RAET'26. Two internships. Building one honest project at a time — from Kerala, India.
Two internships. Both real. Both learned from.
14-day hybrid internship. Covered Git/GitHub workflows, Firebase hosting, KiCad, PlatformIO, TinyML with Edge Impulse, and ESP32 deployment. Building a professional GitHub repo with daily documentation. Fulfils university 2-week internship requirement. The TinyML component connects directly to my Silent Scream Detector hackathon concept.
My first real internship. Walked in with nothing but curiosity. Worked through Python fundamentals, data analysis tasks, and small projects. Realised I actually enjoy solving problems with code. Didn't post about it then — kept the certificate in a folder and moved on. That mindset shift started everything that came after.
A mini project that made it to a national conference.
A dual-backbone deep learning model combining ResNet50 and DenseNet121 as parallel feature extractors — one captures global brain structure, the other picks up fine-grained texture. Features fused with simple concatenation and a lightweight classifier.
No attention mechanisms. No 3D models. Transfer learning with ImageNet weights. A practical, honest approach that actually worked — and made it to a national conference.
Built a live Streamlit app — MRI validation, preprocessing, and inference in one interface. Co-authored with Adith C, Harinand P, and Sruthin M. Guided by Ms. Neethu T Reji.
View on GitHub →Real work. Honest descriptions. No inflated claims.
MORE PROJECTS INCOMING — JULY 2026 ONWARDS · RETAIL ANALYTICS · COHORT SQL · EFAMS · R SHINY · BHIS · CLINICAL NLP
Honest about what I know. Honest about what I'm learning.