BIOGRAPHY
I am a PhD student at UC San Diego department of Computer Science and Engineering, advised by Prof. Rose Yu and Prof. Yian Ma. I received my Bachelor degree of science in Applied Math, Physics, and Computer Sciences from the University of Wisconsin-Madison in 2020. My research primarily lies in Uncertainty Quantification, Bayesian Deep Learning, Spatiotemporal Modeling, Deep Generative Modeling, and Computational Epidemiology. My works have been applied to forecasting spatiotemporal systems in epidemiology, traffic and climate science. I designed DeepGLEAM for COVID-19 incident death forecasts. It was ranked 1st for coverage in CDC forecasting hub and featured in KPBS and Jacobs School of Engineering.
I am currently on the job market, primarily seeking opportunities in academia. You can view my CV here. If you believe I would be a good fit for your department, feel free to contact me at dowu at ucsd dot edu.
Publications
Experiences
- Spearheaded the uncertainty quantification study for spatiotemporal forecasting, compared Bayesian and Frequentist methods on traffic and COVID-19 predictions.
- Designed Time Series Foundation Model for Anomaly Detection.
- Designed the contextual offer estimation method to understand and model customer preferences.
- Spearheaded the causal inference study on multivariate point processes.