Hi, I’m Xiaolan. Nice to meet you.
I’m a research scientist at NASA’s Jet Propulsion Laboratory. My field is the microwave electromagnetic wave physics of natural terrain — how radio waves interact with snow, soil, and vegetation — and for more than a decade I’ve used it to build the models and retrieval algorithms that turn satellite measurements into soil moisture, snow, and freeze–thaw products for missions including SMAP, NISAR, and CYGNSS. JPL profiles this work on its official Radar Science pages for soil moisture and snow.
What drives me now is a question that sits underneath all of that work: the equations we retrieve with are simplified versions of deeper physics, and the assumptions we make to simplify them are rarely written down, tested, or corrected when the data disagrees. I want to close that loop — and I think the tools to finally do it now exist.
My research program
The thing I genuinely own is a specific piece of physics: the microwave electromagnetic wave physics of natural terrain — how radio waves at microwave frequencies scatter from, and propagate through, snow, soil, and vegetation. This is the backbone of microwave remote sensing itself: the measurement only means something if you understand how the wave met the ground. Around that core I’ve built the algorithms that turn the physics into satellite data products, and worked in the mission science that puts those products in front of the world. Being able to follow a problem all the way from Maxwell’s equations in a snowpack to an operational data product is the part of the work I’m best at — and it’s only ever useful when it meets other people’s expertise.
Over the past decade I’ve been a lead developer of the SMAP freeze/thaw algorithm, built JPL’s soil-moisture product for the CYGNSS mission, and developed the physics-based scattering models that underpin snow and soil retrievals — work that has been cited roughly 1,900 times and recognized with the URSI Santimay Basu Prize and NASA group achievement awards. I owe a lot of it to generous mentors and collaborators, and to a field that has always been willing to argue with me in good faith.
My current direction carries that physics into the NISAR era and pushes on a harder problem — closing the loop, so that data doesn’t just check our retrieval equations but actually improves them, while keeping them physically understandable. I don’t think anyone solves this alone, and I certainly can’t: it needs physics, hydrology, statistics, and verification all in the same room. The pieces I can contribute are the physics and the algorithms; I’m always looking for people who hold the others. I treat AI not as a replacement scientist but as the connective tissue that finally makes that kind of cross-field collaboration practical.
Education
- Ph.D. / M.S. in Electrical Engineering — University of Washington, Seattle, WA (2011)
- B.Eng. in Electrical Engineering — Zhejiang University, Hangzhou, China (2006); Chu Kochen Honors College (top 5%)
Blog
The Question After the Demo
A demo went well. Then someone asked a question that had nothing to do with what I’d just shown, and I spent the next week realizing it applied to everything I work on.
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Beyond Binary: Continuous Freeze-Thaw from L-band Missions
An invited seminar on continuous (non-binary) freeze-thaw retrieval from L-band missions.
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