SHANMUKHA RAO SAMANTHULA

Spearheading Data-Driven Solutions in Material Science

At Multiscale, I majorly contribute to the development of innovative solutions in the dynamic field of Material Science, focusing on intelligent document processing and robust data infrastructure. My role encompasses:

- Workflow Development: Engineered components for efficient workflow management using individual widgets, Celery, and RabbitMQ, and developed a scheduling module leveraging Airflow and Docker for streamlined operations.
- Visualization: Designed and developed sophisticated visualization components using Plotly and other supporting modules to provide actionable insights and enhance data interpretation.
- Monitoring & Alerting: Implemented and optimized monitoring and alerting systems with Grafana, Prometheus, and ELK stack, ensuring comprehensive system oversight and timely notifications.
- Centralized Logging: Designed and built a centralized logging module, configuring Grafana and Kibana for effective log visualization and analysis.
- Data Infrastructure: Established a robust backend infrastructure in Python, utilizing Flask API and FastAPI for efficient data handling and integration.
- Database Architecture: Architected a MongoDB database tailored to Material Science needs, optimizing data organization and retrieval processes.
- Microservices Orchestration: Orchestrated Docker-based microservices with Python, Apache Airflow, RabbitMQ, and FastAPI to enhance scalability and system performance.
- Data Extraction: Implemented data extraction from BigQuery through strategic SQL queries, supporting machine learning models, data visualizations (using Plotly and Matplotlib), and other analytical efforts.
I am dedicated to advancing data-driven solutions and optimizing processes in Material Science, leveraging cutting-edge technologies to drive innovation and efficiency.Spearheading Data-Driven Solutions in Material Science At Multiscale, I majorly contribute to the development of innovative solutions in the dynamic field of Material Science, focusing on intelligent document processing and robust data infrastructure. My role encompasses: - Workflow Development: Engineered components for efficient workflow management using individual widgets, Celery, and RabbitMQ, and developed a scheduling module leveraging Airflow and Docker for streamlined operations. - Visualization: Designed and developed sophisticated visualization components using Plotly and other supporting modules to provide actionable insights and enhance data interpretation. - Monitoring & Alerting: Implemented and optimized monitoring and alerting systems with Grafana, Prometheus, and ELK stack, ensuring comprehensive system oversight and timely notifications. - Centralized Logging: Designed and built a centralized logging module, configuring Grafana and Kibana for effective log visualization and analysis. - Data Infrastructure: Established a robust backend infrastructure in Python, utilizing Flask API and FastAPI for efficient data handling and integration. - Database Architecture: Architected a MongoDB database tailored to Material Science needs, optimizing data organization and retrieval processes. - Microservices Orchestration: Orchestrated Docker-based microservices with Python, Apache Airflow, RabbitMQ, and FastAPI to enhance scalability and system performance. - Data Extraction: Implemented data extraction from BigQuery through strategic SQL queries, supporting machine learning models, data visualizations (using Plotly and Matplotlib), and other analytical efforts. I am dedicated to advancing data-driven solutions and optimizing processes in Material Science, leveraging cutting-edge technologies to drive innovation and efficiency.