The Intelligent Environments Laboratory (IEL), led by Prof. Zoltán Nagy, is an interdisciplinary research group in the Department of Civil, Architectural and Environmental Engineering (CAEE) at The University of Texas at Austin.

IEL advances science, engineering and education towards an intelligent and human-responsive energy infrastructure in the built environment. We develop methods in Machine Learning (Supervised, Unsupervised and Reinforcement), Internet of Things, Data Analytics and System Integration/Deployment, with applications in Occupant-Centric Building Design and Operation and Grid-Interactive Smart Communities.

Latest News

AI and Electric Power Summit
Together with EPRI we are organizing a session on the AI Grand Challenge on Grid Interactive Smart Communities. We are meeting in person to take our summit journey to Rome where we will move the AI and electric power dial even further.
AI and Electric Power Summit
EPRI AI Grand Challenge Webinar
This month’s webinar was focused on reinforcement learning as we had presentations from Dr Henze and his research team at CU Boulder. They discussed the advanced control test bed (ACTB) for buildings as well as opportunities, challenges and cases studies for reinforcement learning control in buildings.
EPRI AI Grand Challenge Webinar
Dr Nagy speaks at Amazon
Dr Nagy was the guest speaker in Amazon’s SSI speaker series on Sustainability. He talked about our research on CityLearn. Amazon is sponsoring AWS compute credits for the CityLearn Challenge 2022
Dr Nagy joins scientific and program committee of CISBAT
Focused on the built environment’s transition to carbon neutrality and sustainability, CISBAT 2023 offers a scientific platform for the presentation of research that pushes the boundaries of energy efficiency and renewable energy technologies.
Dr Nagy receives the 2022 IBPSA-USA Outstanding Researcher Award
This award recognizes one or more individuals who have provided outstanding leadership in the promotion of building simulation through research in the course of their career. The award has be announced at the 2022 ASHRAE/IBPSA-USA BPAC/SimBuild Conference .
Dr Nagy receives the 2022 IBPSA-USA Outstanding Researcher Award

Meet the Team

Principal Investigators

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Zoltan Nagy

Assistant Professor

Grad Students

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Kingsley Nweye

PhD Student

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Ting-Yu Dai

PhD Student

Alumni

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Dr. Aysha Demir

Assistant Instructional Professor

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Dr. Jose Vázquez-Canteli

Machine Learning Engineer

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Dr. June Young Park

Assistant Professor

Research Projects

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(BEVO) Beacon: A rapidly-deployable and affordable indoor environmental quality monitor

(BEVO) Beacon: A rapidly-deployable and affordable indoor environmental quality monitor

Indoor Air Quality (IAQ) monitoring is essential to assess occupant exposure to the wide range of pollutants present in indoor environments. Accurate research-grade monitors are often used to monitor IAQ but the expense and logistics associated with these devices often limits the temporal and spatial scale of monitoring efforts.

GridLearn

GridLearn

Led by CU Boulder - Griffin Lab (Dr Kyri Baker): Increasing amounts of distributed generation in distribution networkscan provide both challenges and opportunities for voltage regulation across the network. Intelligent control of smart inverters and other smart building energy management systems can be leveraged to alleviate these issues.

CityLearn

CityLearn

CityLearn is an open source OpenAI Gym environment for the implementation of Multi-Agent Reinforcement Learning (RL) for building energy coordination and demand response in cities. Its objective is to facilitiate and standardize the evaluation of RL agents such that different algorithms can be easily compared with each other. Try it out using our example in Google Colab! More details and installation on GitHub: https://github.com/intelligent-environments-lab/CityLearn