Md Hasibul Hasan

PhD Candidate, Environmental Engineering

University of Central Florida

Biography

Md Hasibul Hasan is a PhD candidate in Environmental Engineering at UCF air quality research Lab. His research interests include low cost sensor technology, air quality modeling, machine learning, motor vehicle emissions estimation, exposure estimation and GHG emission uncertainity estimation in aerial remote sensing. He is currently working on multiple projects funded by National Science Foundation (NSF), Florida Department of Transportation (FDOT), Metroplan Orlando (MPO), California Air Resource Board (CARB) and SailBri Cooper (SCI). He was a recipient of prestigious ORCGS Doctoral Fellowship from UCF. He received SAS data mining graduate certificate from University of Central Florida in 2023. He is a licenced Engineer in training (EIT) from Maryland Department of Labor.

Interests

Air Quality Modeling
Low Cost Sensors
Transportation Based Emission
GHG Uncertaininty in Remote Sensing
Pollutant Exposure Estimate

Education

MS in Environmental Engineering , 2023

University of Central Florida
BS in Civil Engineering, 2019

Bangladesh University of Engineering and Technology

Experience

Graduate Research Assistant , UCF Air Quality Research Lab , University of Central Florida (April 2021 - August 2021, April 2022 - April 2023, August 2023 - August 2024)
Graduate Teaching Assistant , Engineering Mechanics (Statics) , University of Central Florida , (April 2023 - August 2023, August 2024 - Present)

Publications

Hasan, M. H., Zhang, P., Chen, J., Shi, G., Abichou, T., & Yu, H. (2025). Exploring uncertainties in the integrated mass enhancement method for remote sensing retrievals of methane emissions. Waste Management, 200, 114759.
Yu, H., Hasan, M. H., Ji, Y., & Ivey, C. E. (2025). A brief review of methods for determining time-activity patterns in California. Journal of the Air & Waste Management Association.
Hasan, M. H., Yu, H., Ivey, C., Pillarisetti, A., Yuan, Z., Do, K., & Li, Y. (2023). Unexpected Performance Improvements of Nitrogen Dioxide and Ozone Sensors by Including Carbon Monoxide Sensor Signal. ACS omega, 8(6), 5917-5924.
Xiang, K., Yu, H., Du, H., Hasan, M. H., Wei, S., & Xiang, X. (2023). Exploring influential factors of CO2 emissions in China’s cities using machine learning techniques. Environmental Science and Pollution Research, 1-16.
Hasan, M. H. (2023). Performance Comparison of Low-Cost Sensors Across Six Cities of Continental United States.
Al Islam, M., & Hasan, H. (2020). Generation of IDF equation from catchment delineation using GIS. Civil Engineering Journal, 6(3), 540-547.