Fazel Khayatian

Assistant Professor

University of Texas at San Antonio

United States

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About

Fazel Khayatian is an Assistant Professor at the University of Texas at San Antonio, USA. His research primarily focuses on digitalization of urban multi-energy systems, predictive control for demand side management, and integrated assessments of building performance. Recent publications explore advanced methodologies including artificial neural networks, generative adversarial networks, and unsupervised learning in the context of energy management and building systems.

Articles (10)

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2024

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2024

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2024

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2023

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2023

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2022

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2022

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2021

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2021

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2020

Collaborators (3)

honeyeh Ramezan Sefat

Northumbria University

UNITED KINGDOM

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Matthias Sulzer

Head

Empa

SWITZERLAND

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Marco Corradi

Full Professor of Civil engineering

University of Huddersfield

UNITED KINGDOM

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Fazel Khayatian

Research Interests

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About

Articles (10)

A new bond-slip model for NSM FRP systems using cement-based adhesives through artificial neural networks (ANN)

Digitalization of urban multi-energy systems – Advances in digital twin applications across life-cycle phases

Data-driven predictive control for demand side management: Theoretical and experimental results

Integrated assessment of buildings visual and thermal performance with translucent bricks

Phase change material (PCM) integrations into buildings in hot climates with simulation access for energy performance and thermal comfort: A review

Quantifying the climate and human-system-driven uncertainties in energy planning by using GANs

A data-driven approach for window opening predictions in non-air-conditioned buildings

Experiment strategy for evaluating advanced building energy management system

Using generative adversarial networks to evaluate robustness of reinforcement learning agents against uncertainties

Unsupervised learning for feature projection: Extracting patterns from multidimensional building measurements

Collaborators (3)

honeyeh Ramezan Sefat

Matthias Sulzer

Marco Corradi

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