Coder CS'25 @ SRM | ML & Full Stack & Data Engineering | Federated Learning Research | Open to internships
B.Tech Computer Science student at SRM Institute of Science and Technology building production-ready ML systems, full-stack applications, and data engineering pipelines. Active in Federated Learning Research, Machine Learning, Production ML, and Model Observability, with a focus on privacy-preserving AI, automation, and scalable analytics.
- 📡 Federated Learning Research -- Privacy-Preserving Distributed ML
- 📊 Production ML Systems -- Drift Detection & Model Monitoring
- 🌐 Open Source Contributions -- Building AI tools and libraries
- ⚙️ Scalable Data Pipelines -- ETL, streaming, and containerized analytics
- 💻 adaptive-fl-paper - Federated learning framework with ADWIN-based drift detection and dynamic client weighting for resilient model aggregation.
- 💻 fedmed-adaptive-dp - Medical tabular federated learning with sensitivity-aware adaptive differential privacy.
- 💻 federated-cv-qc - Privacy-preserving industrial defect detection using federated learning and YOLOv8.
- 💻 ModelPulse - Lightweight ML observability tool that detects production data drift and model degradation.
- 💻 news-etl-pipeline - Production ETL pipeline with sentiment analysis, MySQL storage, Docker, and Streamlit visualization.
- 💻 qaoa-vqe-maxcut-benchmark - Benchmarking QAOA versus VQE for Max-Cut using Qiskit and PennyLane.
- 🌟 Federated Learning Researcher -- Building privacy-preserving and adaptive federated ML systems for real-world data.
- 🌟 ML Systems Builder -- Creating model observability, drift detection, and production-ready AI tools.
- 🌟 Data Engineering Practitioner -- Designing containerized ETL and streaming pipelines with MySQL, Docker, and monitoring.
- 🌟 Full Stack Automation Developer -- Delivering end-to-end web and automation solutions for AI and analytics.
