1301 W. Green St.
Urbana, IL 61801
- Cloud detection from passive satellite
- Big Data
- Machine Learning
- High performance computing
My current research consists of developing a pixel by pixel cloud detection algorithm for the NASA MAIA mission set to launch in 2022. MAIA, a.k.a. the Multi-Angle Imager for Aerosols, is the successor to the MISR mission, another multi angle instrument launched about 20 years ago. This new mission is unique in that it will collocate its aerosol measurements with medical records on the ground to find a relationship between air pollution and human health. Since aerosol measurements are only collected over cloud free environments, it's imperative to have an operational cloud mask to find pixels that are good candidates for an aerosol retrieval. This is because clouds have complicated interactions with aerosols and their properties of interest are very hard to decouple from each other in passive satellite imagery.
I'm also really interested in high performance computing and machine learning algorithms, and have been developing a convolutional neural network cloud particle classifier in my spare time. We recently worked with another group on campus to develop a dynamic U-net for cloud detection over water with almost 100% agreement with the NASA Terra MODIS cloud mask algorithm. Feel free to check out my GitHub to see if anything sparks your interest.
- M.S. Candidate Atmospheric Science; University of Illinois at Urbana-Champaign
- B.S. Atmospheric Science; University of Illinois at Urbana-Champaign
Awards and Honors
Ogura Outstanding Teaching Award 2019
Ogura Outstanding Undergraduate Research Award 2018
Graduated with High Distinction 2018
University Achievement Scholarship 2015
ATMS 304: Radiative Transfer- Remote Sensing
ATMS 421: Earth Systems Modeling
ATMS 305: Computing and Data Analysis