I'm Akshay — I build end-to-end systems across computer vision, full-stack engineering, and applied ML. From hackathon floors to research labs.
Real-time ADAS system scoring riding behavior 0–100 with live video analysis. Computer vision pipeline with 60fps WebSocket streaming, Kalman filter on Lucas-Kanade optical flow, calibration-free speed estimation, and 6 behavioral metrics including helmet detection via Otsu blob analysis.
View on GitHub Read the deep-diveProduction-grade Cal.com clone. Normalized 6-table PostgreSQL schema, real-time double-booking prevention, automated email reminders via Cron, 11 REST endpoints. Deployed on Vercel.
View on GitHubHybrid quantum-classical deep learning model combining CNNs with variational quantum circuits using 4-qubit angle encoding. 6–8% accuracy improvement → 90% classification accuracy.
View on GitHubResearch under Dr. Mahesh Parihar, IIT Bombay. Classification models on the Pima Indians Diabetes Dataset achieving 96% accuracy with full ROC-AUC benchmarking.
View on GitHubStudent researcher under Dr. Yogeshwar Singh, DIAT Pune. ML models for Remaining Useful Life (RUL) estimation on the C-MAPSS dataset with a full preprocessing dashboard.
View on GitHubI'm a CS + AI/DS undergrad at IIIT Kottayam (Class of 2027) who builds end-to-end AI systems — from computer vision pipelines and real-time backends to full-stack dashboards.
My work spans automotive, healthcare, aerospace, and education. I care about shipping solutions that are technically rigorous and practically useful — not just demos.
I actively compete in hackathons and programming contests, and I've conducted research under faculty at IIT Bombay and DIAT Pune.
When I'm not shipping code I'm under the barbell — won the IIIT-K Powerlifting meet in 2026.
Got a project, opportunity, or just want to talk tech?
akshaysriram.b@gmail.com