Research Focus

My current research focus is to apply machine learning and explainable AI (XAI) methods to explore factors impacting forecast accuracy on subseasonal to seasonal (S2S) timescales.

Bio

Hello and welcome! My name is Jolan, pronounced ‘yo – lawn‘, and I am a graduate student, engineer, endurance athlete, and artist. I am extremely grateful to be working through exciting questions at the intersection of machine learning and S2S forecasting.

In autumn 2025 I will be defending my masters thesis in Atmospheric Science at Colorado State University, and beginning my studies as a PhD student in Boston University’s Computing and Data Sciences unit.

Prior to this work, I completed degrees in mechanical engineering (Duke University B.S. ’21, UCBerkeley MEng ’22), and applied my mechanical design skills as a product design engineer at Apple (2022-2023).

Shifting to the atmospheric science and computing space allows me to connect with my deeper interests of mastering the art of developing beautiful code and thinking about the planet’s impressive dynamics every day.

Outside of the lab, you’ll find me on a bike or in the mountains (ideally both at once). Whether in my home state of Colorado or the far mountains of the world, I am passionate about my training as an endurance athlete and love to explore and challenge myself in the out-of-doors!

Get in touch!

If you would like to talk with me about research, please don’t hesitate to reach out via email!

Find my Github code, Publications/Presentations, and LinkedIn in the menu above.