About me
I am a (final year) PhD candidate (with Tamara Broderick) in the EECS department at MIT. Previously I got two MSc degrees in Statistics and Ecology from the University of Wisconsin-Madison and a ScM degree from MIT in Computer Science. I did my undergraduate degree in Biology/Physics at Peking University.
I am primarily interested in probabilistic machine learning and statistics for low signal-to-noise ratio and data-scarce settings, where incorporating structure, designing data collection strategies, and carefully managing downstream risks due to imperfect predictions are essential. My work is broadly motivated by scientific problems in biology and physics that naturally operate in this regime, ranging from perturbation experiments in gene regulatory networks, intracellular fluid dynamics to wildlife population surveys and the calibration of standard candles in the cosmic distance ladder. I also have some interest towards financial market and spent a summer at Citadel Securities as a quantitative research intern.
Some examples of my research
- Inference of stochastic dynamics using Schrödinger bridges and distributional regression; identifiability theory of stochastic dynamics;
- Theory of learning human preference, corresponding experimental design and robustness checks, with applications in Large Language Model alignment and evaluations;
- Probabilistic machine learning and generative models in physics, especially supernovae science and time domain astronomy, focusing on methods for irregularly sampled sequence data (e.g., timeseries, spectra, etc.) and simulation based inference;
- Population ecology of apex predators and capture-recapture models (e.g., jaguars and wolves).
More about me
I am a wildlife photographer and angler in my spare time. I hold a technician class amateur radio license, bearing KD9TZJ call sign. I am also an ACG fan.