Research Overview
Our lab is dedicated to advancing data-driven methodologies and statistical tools for improving air quality assessment and management. We specialize in the development of calibration models for low-cost sensors, empowering accurate and cost-effective air quality measurements. Leveraging data from low-cost sensors and satellites, we infer aerosol sources, enhancing our understanding of pollution origins and patterns. Additionally, we are focused on creating innovative algorithms to automate the source apportionment process, streamlining the identification of pollution contributors. Furthermore, our research involves long-term analysis of air quality using satellite data, enabling a comprehensive understanding of pollution trends and variations over time. We also employ data science techniques to forecast air pollution, aiding proactive measures and public health protection.
Areas of focus includes:
- Low-cost Sensors
- Satellite and Reanalysis Data
- Real time Source Apportionment
- Pollution Forecasting
Collaborators:
- Pratim Biswas, University of Miami
- Y. S. Mayya, Indian Institute of Technology Bombay
- Chandra Venkatraman, Indian Institute of Technology Bombay
