Munsung’s main interests are in incorporating multiple data sources obtained by remote sensing techniques such as weather radars and satellites to accurately measure, model, and forecast precipitation. He focuses on big data analysis, cloud computing, time series and geostatistical analysis, machine learning, and data fusion with optimization.
He has been involved in multiple water resources projects: development of a radar rainfall processing and nowcasting systems based on radar network observations (S-, C-, and X-bands); development of a statistical downscaling algorithm of precipitation from Global Circulation Models; assessment of a rainwater harvesting system for stormwater management. He received his PhD degree from the Hydraulics and Water Resources program at the University of Iowa, USA. As a research assistant at the Iowa Flood Center and IIHR —Hydroscience & Engineering, he focused on understanding the spatiotemporal structures of errors in radar rainfall estimates and developing radar rainfall retrieval algorithms for real-time flood forecasting.