Ruda Zhang

Ruda Zhang

Postdoctoral Fellow

The Statistical and Applied Mathematical Sciences Institutey

My research aims to combine machine learning (ML) and uncertainty quantification (UQ) for computational and data-enabled science and engineering, especially for applications in infrastructure and engineering systems. My current research focus is probabilistic learning on manifolds (PLoM), a framework that uses ML to exploit topological properties of data for UQ and predictive modeling. ML techniques such as manifold learning can discover low-dimensional structures within high-dimensional data, and PLoM exploits the learned structure to efficiently build probabilistic models for UQ problems.

I am also interested in the interaction between human and technology, especially the use of games and mechanism design in engineering and social systems.

My curriculum vitae.

Interests

  • Uncertainty Quantification
  • Machine Learning
  • Big Data Analysis
  • Transportation
  • Game Theory

Education

  • PhD, Civil Engineering, 2018

    University of Southern California

  • MA, Economics, 2018

    University of Southern California

  • BEng, Engineering Structure Analysis, 2012

    Peking University

Projects

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PLoM

Probabilistic Learning on Manifolds.

Scholar

Bibliographic analysis with Google Scholar.

Taxi

Analysis of the iconic yellow cabs in NYC.

Accessibility

Multi-modal analysis of Portland, OR.

Wiki

My personal knowledge system.

Contact