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Dr Nagy leads research at the intersection of artificial intelligence and building energy systems. His work addresses a critical challenge: buildings consume 40% of global energy yet operate with outdated control systems that ignore the complex interconnections between occupants, energy systems, and urban infrastructure.

He develops model-free reinforcement learning algorithms that enable buildings to learn and adapt automatically. His research team leads the development of the CityLearn platform, used for benchmarking AI algorithms in smart buildings and communities. This open-source environment enables researchers worldwide to develop and compare intelligent building control strategies at the district level.

He coordinates international efforts (IEA-EBC, IBPSA) to rethink human-building relationships in our climate-changing world. My research bridges computer science, building physics, and urban energy systems, creating technologies that transform buildings from passive energy consumers into intelligent partners in sustainable urban development.

Everything is connected鈥攂uildings, occupants, communities, and climate. My passion is creating intelligent systems that optimize these connections for a sustainable future where technology serves humanity.

Dr Nagy earned his MSc and PhD in Mechanical Engineering from ETH Zurich, specializing in microrobotics and magnetic control systems. During his doctoral studies, he also co-founded FemtoTools, a successful high-tech company.

During a postdoctoral position at ETH Zurich's Department of Architecture, he transitioned from microrobotics to building systems, recognizing the similarity in the need for distributed intelligence and complex systems. He served as Assistant Professor at UT Austin from 2016-2024, where he developed the foundational research in reinforcement learning for buildings.

His interdisciplinary journey鈥攆rom molecular-scale robotics to building-scale intelligence鈥攑rovides a unique perspective on complex systems optimization, from occupant-centric control to district-level energy coordination.