Experience

Massachusetts Institute of Technology (Feb 2024 - Present)

Evaluated monoterpene oxidation chemistry in CRACMM, emphasizing the critical role of PANs.
Developed a chemical speciation algorithm to convert high-resolution lab data into model-ready formats.
Built a relational database and automated ETL pipeline linking lab data with chemical models.
Created an open-source Python/SQLite toolkit to support chemical mechanism development.

Led source-oriented simulations of PM and ozone exposure from wildfire and animal agriculture emissions under future energy and greenhouse gas (GHG) scenarios for CARB and USDA projects.
Developed a wildfire speciation profile expanding CARB’s wood combustion inventory from 14 to 72 reactive organic gas species, improving air toxics and health risk modeling resolution.
Applied data fusion techniques combining EPA monitoring stations, PurpleAir sensors, in-situ meteorological observations, and satellite aerosol optical depth (AOD) data using a random forest approach. Reduced model bias and improved forecast accuracy for wildfire smoke exposure and key pollutants.
Calculated public health co-benefits and environmental justice (EJ) metrics from GHG mitigation strategies in support of environmental justice goals under CEQA.

Designed and analyzed environmental chamber experiments to investigate secondary organic aerosol (SOA) and ozone formation from wildfire VOCs.
Built detailed oxidation mechanisms for wildfire-relevant VOCs (furans, phenols and monoterpenes) using the SAPRC mechanism generator (MechGen), and implemented them into air quality models to improve simulation accuracy for EPA- and NSF-funded projects.

Led discussion sections and provided MATLAB support for the course “Engineering Modeling and Analysis”, and graded assignments and exams (~100 students).

Collaborated with GIS and computer science teams to develop a risk assessment framework for water system vulnerability by analyzing pipe failure data in relation to extreme weather patterns.

Delivered short- and long-term county-level weather forecasts, combining surface observations with radar, satellite imagery, and model guidance.
Communicated real-time warnings and briefings to local media and emergency response teams during typhoons and weather events, helping the public prepare and respond.

Classified Pacific tropical cyclones based on formation patterns using large-scale circulation and gridded datasets.
Leveraged gridded meteorological datasets and satellite products to trace the evolution of initial disturbances into tropical cyclones.
Used WRF, satellite, and in situ data to study terrain impacts on mesoscale precipitation and wind systems.
Applied data assimilation techniques to enhance model inputs and produce more accurate predictions.

Delivered lectures twice a week and hands-on WRF model labs for the course “Numerical Weather Forecast” (~20 students).