Ashrant Aryal

Assitant Professor

Texas A&M University

United States

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About

Ashrant Aryal is an Assistant Professor at Texas A&M University in the United States. His research primarily focuses on building energy efficiency, human-building interaction, and the application of machine learning in construction and architectural design. Recent articles authored by Dr. Aryal explore innovative frameworks for building retrofits, stakeholder perceptions in robot adoption, and the effects of materials on the thermal-mechanical properties of building envelopes.

Articles (13)

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2025

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2024

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2020

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2020

Collaborators (3)

Yong-Rak Kim

A.P. and Florence Wiley Professor

Texas A&M University

UNITED STATES

View details

Manish Dixit

Associate Professor

Texas A&M University

UNITED STATES

View details

PETROS SIDERIS

Assistant Professor

Texas A&M University

UNITED STATES

View details

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Ashrant Aryal

Research Interests

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About

Articles (13)

An automated framework for tailored building envelope retrofit planning

Investigating Stakeholder Perception and Developing a Decision Framework for Robot Adoption in Construction

Toward the application of a machine learning framework for building life cycle energy assessment

Effects of shape-stabilized phase change materials in cementitious composites on thermal-mechanical properties and economic benefits

Toward the Application of a Machine Learning Framework for Building Life Cycle Energy Assessment

Effects of alkali-activated slag binder and shape-stabilized phase change material on thermal and mechanical characteristics and environmental impact of cementitious composite for building envelopes

The field of human building interaction for convergent research and innovation for intelligent built environments

Ten questions concerning human-building interaction research for improving the quality of life

Quantifying the impact of personal comfort systems on thermal satisfaction and energy consumption in office buildings under different U.S. climates

Ergonomic assessment of office worker postures using 3D automated joint angle assessment

Understanding the influence of orientation, time-of-day and blind use on user’s lighting choices and energy consumption using immersive virtual environments

Intelligent Agents to Improve Thermal Satisfaction by Controlling Personal Comfort Systems Under Different Levels of Automation

Thermal comfort modeling when personalized comfort systems are in use: Comparison of sensing and learning methods

Collaborators (3)

Yong-Rak Kim

Manish Dixit

PETROS SIDERIS

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