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Dongxia (Allen) Wu

PhD student

Education

Ph.D. student in CompSci

UC San Diego
2020 - Present

B.S in Applied Mathematics

UW-Madison
2017 - 2020

Interests

  • Viola (Solo, Quartet, Orchestra)
  • Fencing (Foil)

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 Bayesian Deep Learning, especially for spatiotemporal data. My works have been applied to forecasting spatiotemporal systems in epidemiology, traffic and climate science.

Publications

  • Deep Bayesian Active Learning for Accelerating Stochastic Simulation
    • Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yian Ma, Rose Yu.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023
  • Disentangled Multi-Fidelity Deep Bayesian Active Learning
    • Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu.
    International Conference on Machine Learning (ICML) 2023
  • DeepViFi: detecting oncoviral infections in cancer genomes using transformers
    • Utkrisht Rajkumar, Sara Javadzadeh, Mihir Bafna, Dongxia Wu, Rose Yu, Jingbo Shang, Vineet Bafna.
    ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB) 2022
  • Multi-fidelity Hierarchical Neural Processes
    • Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2022
  • Quantifying Uncertainty in Deep Spatiotemporal Forecasting
    • Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yian Ma, Rose Yu.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2021
  • Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
    • Estee Cramer, [et al, including Dongxia Wu]
    Proceedings of the National Academy of Sciences, 2022, 119.15: e2113561119.
  • DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting
    • Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yian Ma, Rose Yu.
    Under review
  • A deep learning based automatic defect analysis framework for In-situ TEM ion irradiations
    • Mingren Shen, Guanzhao Li, Dongxia Wu, et al.
    Computational Materials Science, 2021, 197: 110560.
  • Multi defect detection and analysis of electron microscopy images with deep learning
    • Mingren Shen, Guanzhao Li, Dongxia Wu, et al.
    Computational Materials Science, 2021, 197: 110560.

    Experiences

    Research Assistant

    2020 - Present
    UC San Diego, La Jolla, CA
    • Spearheaded the uncertainty quantification study for spatiotemporal forecasting, compared Bayesian and Frequentist methods on traffic and COVID-19 predictions.

    AI Intern

    June 2022 - September 2022
    IBM Thomas J. Watson Research Center, Yorktown Heights, NY
    • Spearheaded the causal inference study on multivariate point processes.

    Awards/Honors

    HDSI Ph.D. Fellowship (2021-2024), top 10 in admitted HDSI Ph.D. students - UC San Diego (2021)
    College of Letters & Science Dean’s List - UW–Madison (2018, 2019)
    Undergraduate Summer Scholarship - UW-Madison (2018)
    The First Prize in China Region and the Fourth Prize in the final - The Third Hong Kong International Chamber Music Competition (2016)