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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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Prof. Zoltan Nagy, PhD

Dr. Nagy is an assistant professor in the Department of Civil, Architectural, and Environmental Engineering at The University of Texas at Austin, directing the Intelligent Environments Laboratory since 2016. A roboticist turned building engineer, his research interests are in smart buildings and cities, renewable energy systems, control systems for zero emission building operation, machine learning and artificial intelligence for the built environment, complex fenestration systems and the influence of building occupants on energy performance.

Prior to joining UT, Austin, Dr. Nagy was a senior scientist at the Swiss Institute of Technology (ETH) in Zurich, in the Department of Architecture. He worked with Prof. Arno Schlueter in the Architecture & Building Systems research group on control systems for sustainable building operation, as well as wireless sensor networks and applications of machine learning in building retrofit. Dr. Nagy has co-founded the award-winning high-tech spin-off Femtotools in 2007, and was member of its board of directors until 2011.

Dr. Nagy received a PhD in robotics in 2011 working in the MultiScale Robotics Lab of Prof. Brad Nelson, and an MSc in Mechanical Engineering (2006) with a focus on micro-electro-mechanical systems (MEMS) and robotics, both from ETH Zurich, Switzerland. He spent an academic exchange semester at the Danish Technical University in 2005, and was a visiting researcher in the Distributed Robotics Laboratory  of Prof. Daniela Rus at MIT in 2009.

Dr Nagy has an Erdös number of 6: 1 (Shallit)→ 2 (Breitbart)→ 3 (Schek)→ 4 (Linkwitz)→ 5 (Veenendaal)→ 6 (Nagy)

According to Robotree, his academic ancestors can be traced to Japan, i.e., probably Samurai – how cool is that?

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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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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
ITS

301 E Dean Keeton St
Austin, TX 78712
512-555-5555
nagy@utexas.edu

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