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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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February 9, 2019, Filed Under: Publication

Artificial Neural Network‐Based Framework for Developing Ground‐Motion Models for Natural and Induced Earthquakes in Oklahoma, Kansas, and Texas

This paper led by PhD student Farid Khosravikia from Patricia Clayton's group has been published in Seismological Research Letters. Check it out y'all. Farid developed neural network based models for earthquakes. DOI: https://doi.org/10.1785/0220180218 This paper, as well as our recent Read more 

January 30, 2019, Filed Under: Publication

Temperature-preference learning with neural networks for occupant-centric building indoor climate controls

Our paper led by Yuzhen Peng from ETH Zurich has been recently published in Building & Environment. We propose an intelligent building control strategy with machine learning techniques together with its design process for creating occupant-centric indoor climate. We demonstrate 4%–25% energy Read more 

January 13, 2019, Filed Under: Publication

Apples or Oranges? New benchmarking paper published in Applied Energy

We collected a building energy dataset (2 years, hourly data) of unprecedented size (3829 buildings) and variety (75 programs). And using machine learning, we discovered three fundamental load shape profiles that characterize the temporal energy use in any of the buildings. The existence of Read more 

December 2, 2018, Filed Under: Publication

Fusing TensorFlow with CitySim for Smart Cities

The journal Sustainable Cities and Society has published our paper Fusing TensorFlow with building energy simulation for intelligent energy management in smart cities led by our awesome PhD student Jose. We have developed CitySim, a framework to study multi-agent reinforcement learning using Read more 

November 19, 2018, Filed Under: Publication

Review paper published & selected for special section in APEN

Our paper Reinforcement learning for demand response: A review of algorithms and modeling techniques led by IEL's PhD student Jose has been published in Applied Energy. We're thrilled that it has been selected by the editors to be included into the Special Section Progress in Applied Energy. J.R. Read more 

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Research Highlight

Occupant centered building control

The energy savings of buildings promised by automatic control systems are often ineffective due to occupants who may not use the features of the 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 !

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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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Research

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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
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nagy@utexas.edu

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