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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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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 

November 17, 2020, Filed Under: News

1st RLEM Workshop @ BuildSys’20

Together with colleagues from Carnegie Mellon University and University of Texas at Arlington, IEL organized the first ACM Workshop on Reinforcement Learning for Energy Management in Buildings and Cities (RLEM'20) at ACM BuildSys on November 17th, 2020, the details are on www.rlem-workshop.net. Read more 

November 11, 2020, Filed Under: News

Impact of COVID-19 on civil infrastructure and citizen needs in Austin, TX

Our research has been presented at UT Austin's COVID research showcase. Watch the video here https://youtu.be/0JlhwvWW2Gs Read more 

August 17, 2020, Filed Under: News

Jose → Dr Vazquez-Canteli!

Jose is the next awesome IEL student to successfully defend his PhD entitled Multi-Agent Reinforcement Learning for Demand Response and Load Shaping of Grid-Interactive Connected Buildings. We congratulate him for this great piece of work and wish him good luck for his future Read more 

July 9, 2020, Filed Under: News

CFP: RLEM’20 @ BuildSys’20

Together with Prof. Mario Bergés (CMU), we are organizing the first Workshop on Reinforcement Learning for Energy Management in Buildings and Cities (RLEM’20) co-located with ACM BuildSys’20, and held virtually. We invite original submissions that explore the use of reinforcement learning Read more 

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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

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

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