Huan He

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Huan He, Postdoctoral fellow at Harvard Medical School,
Harvard University, Boston, United States

[Google Scholar][Curriculem Vitae]

My current research includes but is not limited to the following topics:

  • Efficient training algorithms (e.g., parallel computing, optimization, numerical analysis)

  • Transfer learning (e.g., domain adaptation/generalization)

  • Trustworthy learning (e.g., short-cut learning, calibration, robustness)

  • Deep generative model for graph-structured data (e.g., transaction networks, social networks, 3D molecular conformation)


About me

I am currently a postdoctoral fellow at Harvard Medical School, Harvard University, working with Prof. Marinka Zitnik. I got my Ph.D. in Computer Science at Emory University, under the guidance of Dr. Yuanzhe Xi and Joyce Ho. My research interests lie primarily in machine learning, and span the entire theory-to-application spectrum from foundational advances all the way to deployment in real systems. Recently, I am working on numerical methods for accelerating large-scale models (e.g., tensor decomposition, deep generative models, neural networks).


  • Ph.D. in Computer Science, Emory University, Aug. 2018 - May. 2022

  • M.S. in Computer Science, Emory University, Aug. 2016 - Jun. 2018

  • M.S. in Financial Mathematics, University of Connecticut, Aug. 2014- Jun. 2016

  • B.S. in Financial Enginnering, Shanghai Finance University, Sept. 2010 - May. 2014

Research Focus

  • Statistical Machine Learning, Deep Learning, Graph Neural Network

  • Numerical Analysis, Iterative Algorithms, Optimization