Esther joined the Professorship of Architecture and Building Systems as a Postdoctoral Researcher in February 2022. With a strong background in modeling, programming, data science, and optimization, she specializes in implementing, testing, and fine-tuning control algorithms for innovative solutions for buildings and the systems that serve them. Esther’s current research in the A/S group focuses on developing a data-driven model utilizing machine learning techniques to create a building controller capable of balancing energy flexibility with energy efficiency. She is also an active member of IEA EBC Annex 81 on Data-Driven Smart Buildings. Besides her research work, Esther teaches students in programs such as the Bachelor and Master of Architecture, coordinates the Hive MOOC, and manages the A/S Knowledge Platform.

In her Ph.D. at the Institute for Environmental Design and Engineering at University College London (UCL), which was fully funded by the Foundation of German Business (Stiftung der Deutschen Wirtschaft), Esther developed an integrated modeling approach for control algorithms of adaptive façades using co-simulation, under the supervision of Dr. Rokia Raslan and Dr. Dimitrios Rovas. Before her Ph.D., Esther gained several years of experience in engineering and environmental consultancy and graduated with an M.Sc. in Environmental Design and Engineering from the Bartlett School of Graduate Studies, UCL.

Esther's research interests center around leveraging technology to create energy-efficient and energy-flexible buildings that benefit both people and the environment and using numerical and learning methods to achieve these goals. In particular, she is interested in the optimal control of smart buildings, including the development of models and simulation tools, analytical processing of sensor information, improving the accuracy of simulation tools, and, more generally, data science, artificial intelligence, and building physics.

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