Xiong Yu

Professor

Case Western Reserve University

United States

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Professor Xiong Yu is a faculty member at Case Western Reserve University, USA. His research focuses on machine learning applications in epidemic dynamics and environmental engineering, including real-time forecasts and predictive optimization in construction and water management systems. Professor Yu has also explored innovative materials such as photocatalytic cement and antifungal coatings, contributing to advancements in sustainable engineering practices.

Articles (19)

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2025

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2022

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2022

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2021

Collaborators (4)

Xijin Zhang

assistant professor

George Mason University

UNITED STATES

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Anna Cristina Samia

Associate Professor

Case Western Reserve University

UNITED STATES

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Juncai Xu

Case Western Reserve University

UNITED STATES

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juncai xu

Case Western Reserve University

UNITED STATES

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Xiong Yu

Research Interests

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Articles (19)

A transferable machine learning model for real-time forecast of epidemic dynamics and pre-trigger event warning

Data-driven analysis in 3D concrete printing: predicting and optimizing construction mixtures

A Novel Machine Learning Based Cluster-Then-Forecast Framework for Sensor Placement Optimization and Real-Time Water Level Prediction in Low Impact Development (LID) Stormwater System

Photocatalytic Cement Mortar with Durable Self-Cleaning Performance

Innovative Antifungal Photocatalytic Paint for Improving Indoor Environment

Effect of Nitrogen Doping on the Photocatalytic Properties and Antibiofilm Efficacy of Reduced TiO2 Nanoparticles

A multiphysics model for assessing the stability of cold region slope subjected to environmental dynamics

Optimizing Photodegradation Rate Prediction of Organic Contaminants: Models with Fine-Tuned Hyperparameters and SHAP Feature Analysis for Informed Decision Making

A Multiphysics Simulation of the Effects of Wicking Geotextile on Mitigating Frost Heave under Cold Region Pavement

Insight into on compression behaviors of clay from a novel discrete element model considering non-contact interparticle forces

Uncertainty quantification of a deep learning model for failure rate prediction of water distribution networks

A novel method to improve the soil erosion resistance with fungi

Deep learning based on connected vehicles for icing pavement detection

Pavement Roughness Grade Recognition Based on One-dimensional Residual Convolutional Neural Network

Predicting Active Sites in Photocatalytic Degradation Process Using an Interpretable Molecular-Image Combined Convolutional Neural Network

An innovative machine learning based framework for water distribution network leakage detection and localization

Naturally grown mycelium-composite as sustainable building insulation materials

Energy, environmental and economic performance evaluation of energy pile system under different climate conditions

Machine learning model and strategy for fast and accurate detection of leaks in water supply network

Collaborators (4)

Xijin Zhang

Anna Cristina Samia

Juncai Xu

juncai xu

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