Chao Wang

Assistant Professor

Iowa State University

United States

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About

Dr. Chao Wang is an Assistant Professor at the University of Iowa, USA. His research focuses on climate change impacts, particularly in Alaska and Hawaii, as well as advanced methodologies in data science such as transfer learning and time series analysis. Recent articles authored by Dr. Wang explore topics including downscaled climate datasets, flooding changes due to precipitation and temperature, and the uncertainty in climate predictions from a military installation perspective.

Articles (20)

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2025

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2022

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2022

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2022

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2022

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2022

Collaborators (6)

Sandeep Laroia

University of Iowa Hospitals and Clinics

UNITED STATES

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Geb Thomas

Professor

The University of Iowa

UNITED STATES

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Xin Zan

The University of Iowa

UNITED STATES

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Beiwen Li

Iowa State University

UNITED STATES

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Andreas Prein

Professor

ETH Zürich

SWITZERLAND

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Thomas M. Peters

UNITED STATES

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Chao Wang

Research Interests

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About

Articles (20)

Ensemble downscaled climate dataset for Alaska and Hawaii under historical and future conditions

Variational inference-based transfer learning for profile monitoring with incomplete data

Climate change reduces the wind chill hazard across Alaska

Precipitation‐ and Temperature‐Driven Future Changes to Flooding in Alaska

Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering

Transfer Learning of Stochastic Kriging for Individualized Prediction

Dominant Sources of Uncertainty for Downscaled Climate: A Military Installation Perspective

Adaptive sampling and monitoring of partially observed images

Causality-aware social recommender system with network homophily informed multi-treatment confounders

Causality-aware social recommender system with network homophily informed multi-treatment confounders

Adaptive Sampling for Monitoring Multi-Profile Data with Within-and-between Profile Correlation

Data-level transfer learning for degradation modeling and prognosis

Gaussian Process Latent Variable Model-Based Multi-Output Modeling of Incomplete Data

Sequential Active Contour Based on Morphological-Driven Thresholding for Ultrasound Image Segmentation of Ascites

Landmark-embedded Gaussian process with applications for functional data modeling

Transfer learning of degradation modeling and prognosis based on multivariate functional analysis with heterogeneous sampling rates

Transfer learning of degradation modeling and prognosis based on multivariate functional analysis with heterogeneous sampling rates

Combining physics-based and Kriging models to improve the estimation of noise exposure

Nonlinear Online Multioutput Gaussian Process for Multistream Data Informatics

Estimating Size and Number Density of Three-Dimensional Particles Using Truncated Cross-Sectional Data

Collaborators (6)

Sandeep Laroia

Geb Thomas

Xin Zan

Beiwen Li

Andreas Prein

Thomas M. Peters

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