1. Developed a generative AI platform for ad-hoc data analysis using natural language queries.2. Conducted POC studies on multiple LLMs, selecting OpenAI, achieving a 60% improvement in query understanding.3. Engineered features using AutoML and Scikit-learn, delivering 88% accurate forecasts for IoT and business data.4. Architected a full-stack solution with Python/Flask backend and Azure cloud infrastructure to ensure scalability.5. Architected Azure Data Factory pipelines for seamless migration of IoT and business data to Azure cloud services.6. Deployed Azure IoT Edge solutions, successfully fetching 70,000 telemetric tags from Azure IoT Hub. Transformed the data using O(n) logic and ingested it into Event Grid, Stream Analytics, and Data Lake in real-time, resulting in a 20% increase in data ingestion efficiency.7. Developed Python applications for secure access management of Azure Data Lake Gen2, ensuring data quality.8. Configured Azure IoT Hub for telemetry data integration from Kepware OPC Server, creating real-time monitoring solutions.9. Integrated InfluxDB with Grafana to develop interactive dashboards for visualizing key performance indicators.

FAST - National University of Computer & Emerging Sciences