Data enthusiast, AI/ML practitioner, and cloud computing explorer with experience in real-time edge AI deployment, full-stack development, and data analytics. Skilled in Python, SQL, C, and JavaScript, with practical expertise in TensorFlow Lite, Scikit-learn, React, Django, and AWS/Azure. Focused on building impactful solutions, delivering robust applications, and leveraging data to drive informed decisions. Published researcher with real-world project experience, continuously upskilling across emerging technologies.
- Published ML Research: Developed an end to end currency recognition system for the visually impaired using MobileNetV2/TFLite, achieving 98.35% accuracy and sub-second inference on Raspberry Pi.
- End-to-End Pipeline Engineering: Built comprehensive Jupyter-based machine learning workflows (e.g., CardioRisk ML) featuring GPU-accelerated XGBoost, stratified cross-validation, and automated model evaluation for consistent, reproducible results.
- Scalable Data Systems: Engineered scalable PySpark ETL pipelines and distributed processing workflows on HDFS/Parquet, optimizing partitioning to reduce network I/O for large-scale environmental datasets.
- Enterprise-Grade Full-Stack: Developed modular SaaS backends using Node.js/TypeScript and Django/React, integrating PostgreSQL.
- Edge AI Deployment: Optimized TensorFlow Edge AI models on Raspberry Pi for real-time inference, ensuring operational robustness in hardware-constrained production environments.
- Continuous Technical Upskilling: Completed 55+ certifications, including Lean Six Sigma Yellow Belt, Agile Scrum, and AWS Cloud Foundations, showcasing a commitment to process efficiency and reliability.
- Community & Leadership: Google Maps Level 10 Local Guide with 92M+ views and captained multiple collegiate sports teams, demonstrating leadership and performance under pressure.