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Intelligent Environments Laboratory

The University of Texas at Austin
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    • Prof. Zoltan Nagy, PhD
    • June Young Park
    • José Ramón Vázquez-Canteli
    • Megan K. McHugh, MSE
    • Ayşegül Demir Dilsiz
    • Hagen Fritz
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January 21, 2022, Filed Under: News, Publication

IEL @ Healthy Buildings – America 2021

Our awesome PhD student Hagen Fritz presented his research on ventilation rates at Healthy-Building 2021. Title: Estimated Ventilation Rates and their Effect on Sleep Quality in Healthy, Young Adults Co-Authors: K. Kinney, D. Schnyer and Z. Nagy Read more 

August 8, 2021, Filed Under: News, Publication

New Paper with Empa: Using GANs for RL robustness

We have a new paper out on using generative adversarial networks to study the robustness of RL agents against uncertainties. We show how we can leverage past data to create a new dataset that helps us judge this. https://www.sciencedirect.com/science/article/pii/S0378778821006186?via%3Dihub F. Read more 

November 18, 2020, Filed Under: News, Publication

IEL @ ACM BuildSys’20

We were well represented at ACM BuildSys this year (http://buildsys.acm.org/2020/). See the presentations on YouTube: Jose kicked us off with a full paper presentation MARLISA: Multi-Agent Reinforcement Learning with Iterative Sequential Action Selection for Load Shaping of Grid-Interactive Read more 

February 27, 2020, Filed Under: Publication

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Our paper has been accepted in Energy and Buildings. The work is led by our awesome PhD student June, in collaboration with the National Renewable Energy Laboratory in Golden, CO. Check it out y'all. https://doi.org/10.1016/j.enbuild.2020.109892 Abstract: Reducing the overall energy Read more 

January 7, 2020, Filed Under: Publication

Wireless sensor network for estimating building performance

Our latest paper, led by colleagues from ETH Zurich,  deals with developing and deploying wireless sensor networks for building energy monitoring. https://doi.org/10.1016/j.autcon.2019.103043   Abstract Accurate building energy assessments are often limited by inaccurate assumptions Read more 

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Research Highlight

Reinforcement Learning in the Built Environment

We develop reinforcement learning techniques for energy efficient operation of buildings and systems without the need for mathematical models. Despite Read more 

About Us

The Intelligent Environments Laboratory (IEL), led by Prof. Zoltán Nagy, is an interdisciplinary research group within the Building Energy & Environments (BEE) and Sustainable Systems (SuS) Programs of the Department of Civil, Architectural and Environmental Engineering (CAEE) in the Cockrell School of Engineering of the University of Texas at Austin.

The aim of our research is to rethink the built environment and define Smart Buildings and Cities as spaces that adapt to their occupants and reduce their energy consumption.

We combine data science with building science and apply machine learning to the building and urban scale

Take a look at our projects !

Tags

air handling unit Annex 79 architecture artificial neural network Bluetooth city learn Community engaged research earthquakes environmental monitoring fault detection and diagnostics HVAC integrated design intelligent energy management Lighting Control machine learning Megan McHugh multi-agent systems Occupancy Occupant Centered Control Reinforcement Learning Review Smart Building smart city teaching Thermal Comfort
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UT Energy App – Privacy Policy

Fault detection and diagnostics of air handling units using machine learning and expert rule-sets

Reinforcement Learning in the Built Environment

Reinforcement learning for urban energy systems & demand response

Multi-Agent Reinforcement Learning for demand response & building coordination

IEA-EBC Annex 79: Occupant Centric Design and Operation of Buildings

People

  • Prof. Zoltan Nagy, PhD
  • June Young Park
  • José Ramón Vázquez-Canteli
  • Megan K. McHugh, MSE

Tags

air handling unit Annex 79 architecture artificial neural network Bluetooth city learn Community engaged research earthquakes environmental monitoring fault detection and diagnostics HVAC integrated design intelligent energy management Lighting Control machine learning Megan McHugh multi-agent systems Occupancy Occupant Centered Control Reinforcement Learning Review Smart Building smart city teaching Thermal Comfort
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301 E Dean Keeton St
Austin, TX 78712
512-555-5555
nagy@utexas.edu

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