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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 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 

February 20, 2020, Filed Under: News

Kaitlyn named CAEE Legacy Scholar

Our awesome undergraduate researcher Kaitlyn has received the prestigious Legacy Scholarship of our CAEE department. Her research contributes to our CityDNN project modeling urban energy demand using deep neural networks. The scholarship is a testimony to the fantastic research that our Read more 

February 13, 2020, Filed Under: News

Sustainable Dog House Challenge

Student teams participating in the 2020 CAEE Sustainable Dog House Competition must work together to design and build a formidable shelter for dogs. Successful student designs will score top marks in seven categories to be judge by UT faculty, UT staff, and local engineering Read more 

February 10, 2020, Filed Under: News

Teaching Reinforcement Learning in Australia

Our very own Phd candidate Jose has jetted around the globe to Adelaide, Australia to teach Reinforcement Learning in The Adelaide Power Systems Summer School 2020. He introduced a hands-on approach and worked from the basics of RL all the way up to applying the latest research in our CityLearn Read more 

January 27, 2020, Filed Under: GitHub

CityLearn

An OpenAI Gym environment for Multi-Agent Reinforcement Learning Systems applied to intelligent energy management. https://github.com/intelligent-environments-lab/CityLearn Read more 

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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

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