Where mosquitoes can live is affected by variations in the climate. In this work, I use machine learning methods to predict which land areas are suitable for mosquitoes on annual time scales.

Extreme events such as drought and heatwaves cause devastating impacts on the environment, human society, and the economy. In my work, I investigate extreme events, such as concurrent low precipitation and high temperature events that occur at the same time and location (concurrent compound events), analyze what drives their occurrence, and how they are projected to change in the future. 

Previous Research

I previously worked on a project to build a model for the temperature dependent optical absorption of Thulium-doped YAG. When designing high-powered solid-state laser systems it is incredibly useful to have a model that can visualize and calculate the temperature variation of optical absorption features. Therefore, in this work we measured the optical absorption of different transition manifolds for a 1% Thulium-doped YAG crystal at a range of cryogenic temperatures. We then built a model for this absorption spectra that should have general applicability to other rare earth-doped crystals. 

Moreover, it can be demonstrated that the "hot bands" of absorption spectra can be used as an optical thermometer which helps to demonstrate actual temperatures of the rare earth-doped crystals.

Other Research Interests: Science outreach and communication, machine learning, climate policy, sustainability