Xihaier Luo

Hello there! At ‪Brookhaven National Laboratory, I work as a Research Associate in the Machine Learning Group. I collaborate with ‪Shinjae Yoo on machine learning and scientific computing. Previously, I received my Ph.D. in CE from the ‪University of Notre Dame, where I collaborated with ‪Ahsan Kareem on machine learning-based modeling, analysis, and simulation of dynamic systems.

Research work


Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response
IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2022
Luo, X., et al.
‪Conference's website   |   ‪Preprint

Zero or Infinite Data? Knowledge Synchronized Machine Learning Emulation
NeurIPS 2022 AI for Science Workshop
Luo, X., Ren, Y., Xu, W., Yoo, S, Nadiga, B.T. and Kareem, A.
‪Conference's website  

A Bayesian Deep Learning Approach to Near-Term Climate Prediction
Journal of Advances in Modeling Earth Systems
Luo, X., Nadiga, B.T., Ren, Y., Park, J.H., Xu, W. and Yoo, S.
‪Publisher's website   |   ‪Preprint   |   Code


Feature Importance in a Deep Learning Climate Emulator
ICLR 2021 Workshop on Modeling Oceans and Climate Change
Xu, W., Luo, X., Ren, Y., Park, J.H., Yoo, S. and Nadiga, B.T.
‪Conference's website   |   ‪Preprint

Dynamics of random pressure fields over bluff bodies: A dynamic mode decomposition perspective
Journal of Engineering Mechanics
Luo, X. and Kareem, A
‪Publisher's website   |   ‪Preprint   |   Code

Probabilistic evolution of stochastic dynamical systems: A meso-scale perspective
Structural Safety
Yin, C., Luo, X., and Kareem, A
‪Publisher's website   |   ‪Preprint


Bayesian deep learning with hierarchical prior: Predictions from limited and noisy data
Structural Safety
Luo, X. and Kareem, A
‪Publisher's website   |   ‪Preprint


Deep convolutional neural networks for uncertainty propagation in random fields
Computer‐Aided Civil and Infrastructure Engineering
Luo, X. and Kareem, A
‪Publisher's website   |   ‪Preprint   |   Code


  • Address

    Computational Science Initiative,
    Brookhaven National Laboratory,
    Bldg. 725, P.O. Box 5000,
    Upton, NY 11973-5000,
    United States