USA – Fully Funded PhD in Human–Building Interaction at The University of Texas
PhDFinder, San Antonio, TX, United States
About The University or Research Institute
The University of Texas at San Antonio (UT San Antonio) stands as a leading Tier One research institution and ranks as the third-largest public research university in Texas. Renowned for its commitment to student achievement, research excellence, and community engagement, UT San Antonio is situated in one of the fastest-growing and most vibrant cities in the United States. The university’s Klesse College of Engineering and Integrated Design (KCEID) is recognized for fostering interdisciplinary innovation, housing state‑of‑the‑art facilities, and supporting a thriving ecosystem for research and entrepreneurship. PhD students at UT San Antonio benefit from a collaborative academic culture, access to pioneering research centers, and strong connections to industry and public sector partners, all within a dynamic urban setting that encourages real‑world impact.
Research Topic and Significance The Ambient Intelligence Lab (AmI Lab) at UT San Antonio is at the forefront of research in human–building interaction, focusing on the integration of artificial intelligence (AI), embedded sensing, simulation, and mixed reality (VR/AR/MR) to develop smart, adaptive environments. The lab’s work addresses crucial challenges in designing proactive, intuitive interfaces that facilitate occupant interactions with buildings, optimizing energy management, and enhancing safety and comfort through advanced sensing and automation.
This research is highly relevant in today’s context, as urbanization and sustainability imperatives drive the need for intelligent infrastructure. By developing digital twins, AI agents, and immersive systems, the AmI Lab aims to bridge the gap between physical and virtual spaces, enabling real‑time monitoring, simulation, and control of building environments. The outcomes of this research have the potential to revolutionize how buildings are designed, operated, and experienced, contributing to smarter cities and improved quality of life.
Project Details The fully funded PhD position is offered within the Ambient Intelligence Lab, part of the School of Civil & Environmental Engineering and Construction Management at KCEID, UT San Antonio. The lab is directed by Dr. Tianzhi He, an Assistant Professor whose research expertise spans data‑driven reasoning, physiological sensing, and intelligent interface design for smart built environments. Dr. He brings a distinguished academic background, with advanced degrees from Virginia Tech and a proven record of research leadership.
PhD Students in the AmI Lab will engage in interdisciplinary collaborations, both within the department and across related fields, to advance academic research and develop practical systems. Research topics include:
Human–Building Interaction: Development of intuitive interfaces for seamless occupant engagement.
AI Agents: Creation of agent‑based systems for building data analysis and energy management.
Embedded Sensing: Integration of physiological and environmental sensors for human state inference.
Mixed Reality: Application of VR/AR/MR technologies for immersive design, training, and operations.
Digital Twins: Synchronization of virtual and physical assets for enhanced monitoring and control.
World Modeling: Implementation of vision‑language models, sensor simulations, and infrastructure modeling.
The position offers comprehensive funding, including a tuition waiver and a competitive stipend, supporting doctoral research starting in Fall 2026.
Candidate Profile This opportunity is ideal for academically driven individuals with a passion for intelligent infrastructure and interdisciplinary research. Suitable candidates will have:
A Master’s degree in Civil Engineering, Construction Management, Architectural Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, or a closely related field.
Demonstrated programming experience in languages such as Python, R, or MATLAB.
Prior research experience and/or publications in relevant areas.
Experience with machine learning, deep learning, or large language models (e.g., PyTorch, TensorFlow, prompt engineering).
Background in Building Information Modeling (BIM), building automation, IoT, sensors, or time‑series data analysis.
Exposure to VR/AR/MR workflows (Unity/Unreal Engine) or digital twin platforms.
Successful applicants will be motivated, collaborative, and eager to contribute to the advancement of smart built environments through innovative research.
Application Process To apply, candidates should:
Send an email to Dr. Tianzhi He with the subject line: "AmI Lab PhD Application – Your Full Name". Attach a CV/resume and a cover letter describing research interests and relevant experience.
Shortlisted candidates will be contacted for further inquiries and potential interviews.
Applicants must also submit a formal application to the UT San Antonio Graduate Application portal.
For full details on the doctoral program and application process, please refer to the official program page: https://future.utsa.edu/programs/doctoral/civil-engineering/
This position was advertised by Dr. Tianzhi He on LinkedIn. For more information and updates, visit: https://www.linkedin.com/posts/tianzhi-he_ami-lab-phd-position-notice-ugcPost-7438730211505971200-lG0C
Conclusion If you are passionate about shaping the future of smart, sustainable built environments through advanced AI, sensing, and immersive technologies, this fully funded PhD position at UT San Antonio offers an exceptional platform to develop your expertise and make a lasting impact. We encourage motivated candidates to apply and to explore similar opportunities to further their academic and professional journeys.
Questions & Answers What are the main benefits of pursuing a PhD at UT San Antonio? UT San Antonio offers a world‑class research environment, competitive funding, access to cutting‑edge facilities, and strong industry connections, all within a vibrant and growing city.
Which academic backgrounds are eligible for this PhD position? Eligible backgrounds include civil engineering, construction management, architectural engineering, mechanical engineering, electrical engineering, computer science, or closely related fields.
What kind of research experience is preferred? Applicants with prior research experience, especially those with publications, and experience in machine learning, AI, sensing, or immersive technologies are preferred.
What is the funding package for this PhD position? The position is fully funded, including a tuition waiver and a competitive stipend for the duration of the program.
Who will supervise the research? The research will be supervised by Dr. Tianzhi He, Assistant Professor and Director of the Ambient Intelligence Lab at UT San Antonio.
What is the application deadline? The advertisement does not specify a deadline. Early application is encouraged.
Where can I find more information about the program and application process? Visit the official doctoral program page at https://future.utsa.edu/programs/doctoral/civil-engineering/ and the LinkedIn post at https://www.linkedin.com/posts/tianzhi-he_ami-lab-phd-position-notice-ugcPost-7438730211505971200-lG0C for further details.
Are international students eligible to apply? Yes, international students with relevant backgrounds and qualifications are encouraged to apply.
Also See
Comprehensive Guide to Graduate Application Deadlines for US Universities (Fall 2026 Intake)
Italy – PhD in XR Technologies at University of Trento
USA – Fully Funded PhD in Smart Infrastructure at University of Mississippi
USA – Funded PhD in Digital Twin Ecosystems at Purdue University
UK – Distance Learning PhD in Structural Engineering at University of West London
#J-18808-Ljbffr
Research Topic and Significance The Ambient Intelligence Lab (AmI Lab) at UT San Antonio is at the forefront of research in human–building interaction, focusing on the integration of artificial intelligence (AI), embedded sensing, simulation, and mixed reality (VR/AR/MR) to develop smart, adaptive environments. The lab’s work addresses crucial challenges in designing proactive, intuitive interfaces that facilitate occupant interactions with buildings, optimizing energy management, and enhancing safety and comfort through advanced sensing and automation.
This research is highly relevant in today’s context, as urbanization and sustainability imperatives drive the need for intelligent infrastructure. By developing digital twins, AI agents, and immersive systems, the AmI Lab aims to bridge the gap between physical and virtual spaces, enabling real‑time monitoring, simulation, and control of building environments. The outcomes of this research have the potential to revolutionize how buildings are designed, operated, and experienced, contributing to smarter cities and improved quality of life.
Project Details The fully funded PhD position is offered within the Ambient Intelligence Lab, part of the School of Civil & Environmental Engineering and Construction Management at KCEID, UT San Antonio. The lab is directed by Dr. Tianzhi He, an Assistant Professor whose research expertise spans data‑driven reasoning, physiological sensing, and intelligent interface design for smart built environments. Dr. He brings a distinguished academic background, with advanced degrees from Virginia Tech and a proven record of research leadership.
PhD Students in the AmI Lab will engage in interdisciplinary collaborations, both within the department and across related fields, to advance academic research and develop practical systems. Research topics include:
Human–Building Interaction: Development of intuitive interfaces for seamless occupant engagement.
AI Agents: Creation of agent‑based systems for building data analysis and energy management.
Embedded Sensing: Integration of physiological and environmental sensors for human state inference.
Mixed Reality: Application of VR/AR/MR technologies for immersive design, training, and operations.
Digital Twins: Synchronization of virtual and physical assets for enhanced monitoring and control.
World Modeling: Implementation of vision‑language models, sensor simulations, and infrastructure modeling.
The position offers comprehensive funding, including a tuition waiver and a competitive stipend, supporting doctoral research starting in Fall 2026.
Candidate Profile This opportunity is ideal for academically driven individuals with a passion for intelligent infrastructure and interdisciplinary research. Suitable candidates will have:
A Master’s degree in Civil Engineering, Construction Management, Architectural Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, or a closely related field.
Demonstrated programming experience in languages such as Python, R, or MATLAB.
Prior research experience and/or publications in relevant areas.
Experience with machine learning, deep learning, or large language models (e.g., PyTorch, TensorFlow, prompt engineering).
Background in Building Information Modeling (BIM), building automation, IoT, sensors, or time‑series data analysis.
Exposure to VR/AR/MR workflows (Unity/Unreal Engine) or digital twin platforms.
Successful applicants will be motivated, collaborative, and eager to contribute to the advancement of smart built environments through innovative research.
Application Process To apply, candidates should:
Send an email to Dr. Tianzhi He with the subject line: "AmI Lab PhD Application – Your Full Name". Attach a CV/resume and a cover letter describing research interests and relevant experience.
Shortlisted candidates will be contacted for further inquiries and potential interviews.
Applicants must also submit a formal application to the UT San Antonio Graduate Application portal.
For full details on the doctoral program and application process, please refer to the official program page: https://future.utsa.edu/programs/doctoral/civil-engineering/
This position was advertised by Dr. Tianzhi He on LinkedIn. For more information and updates, visit: https://www.linkedin.com/posts/tianzhi-he_ami-lab-phd-position-notice-ugcPost-7438730211505971200-lG0C
Conclusion If you are passionate about shaping the future of smart, sustainable built environments through advanced AI, sensing, and immersive technologies, this fully funded PhD position at UT San Antonio offers an exceptional platform to develop your expertise and make a lasting impact. We encourage motivated candidates to apply and to explore similar opportunities to further their academic and professional journeys.
Questions & Answers What are the main benefits of pursuing a PhD at UT San Antonio? UT San Antonio offers a world‑class research environment, competitive funding, access to cutting‑edge facilities, and strong industry connections, all within a vibrant and growing city.
Which academic backgrounds are eligible for this PhD position? Eligible backgrounds include civil engineering, construction management, architectural engineering, mechanical engineering, electrical engineering, computer science, or closely related fields.
What kind of research experience is preferred? Applicants with prior research experience, especially those with publications, and experience in machine learning, AI, sensing, or immersive technologies are preferred.
What is the funding package for this PhD position? The position is fully funded, including a tuition waiver and a competitive stipend for the duration of the program.
Who will supervise the research? The research will be supervised by Dr. Tianzhi He, Assistant Professor and Director of the Ambient Intelligence Lab at UT San Antonio.
What is the application deadline? The advertisement does not specify a deadline. Early application is encouraged.
Where can I find more information about the program and application process? Visit the official doctoral program page at https://future.utsa.edu/programs/doctoral/civil-engineering/ and the LinkedIn post at https://www.linkedin.com/posts/tianzhi-he_ami-lab-phd-position-notice-ugcPost-7438730211505971200-lG0C for further details.
Are international students eligible to apply? Yes, international students with relevant backgrounds and qualifications are encouraged to apply.
Also See
Comprehensive Guide to Graduate Application Deadlines for US Universities (Fall 2026 Intake)
Italy – PhD in XR Technologies at University of Trento
USA – Fully Funded PhD in Smart Infrastructure at University of Mississippi
USA – Funded PhD in Digital Twin Ecosystems at Purdue University
UK – Distance Learning PhD in Structural Engineering at University of West London
#J-18808-Ljbffr