IDEAS Lab

Integrated Data, Energy Analysis + Simulation

A Passion for Better Buildings

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IDEAS Lab is a research group in the Department of the Built Environment in the College of Design and Engineering at the National University of Singapore (NUS) that engages in the integration building performance simulation with real-time data and machine learning. The group focuses on various aspects of building performance simulation including uncertainty quantification, model calibration, and building data analytics with the aim of creating energy efficient and healthier buildings.

Also, check out our two sibling labs: the Building and Urban Data Science (BUDS) Lab and the Urban Analytics Lab (UAL), with whom we collaborate closely within NUS.

Projects

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Advanced machine learning based control for HVAC systems

Advanced machine learning based control for the HVAC systems

An automated framework for model predictive control

This study aims at improving the scalability of MPC by addressing modeling-related issues and establishing an automated framework.

Epwshiftr: an R package for creating future weather files under climate changes for building energy simulation

An R package for creating future weather files under climate changes for building energy simulation

Life cycle cost optimization

Life cycle cost optimization

eplusr: A framework for integrating building energy simulation and data-driven analytics

A framework for seamless integration between Building Energy Simulation (BES) and data-driven analytics.

Generating certified energy models in Singapore through an M&V framework.

Generating certified energy models in Singapore through an M&V framework.An NUS project in collaboration with Professor Godfried L. Augenbroe (Georgia Institute of Technology)

Postdoctoral Researchers

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Wei Liang

Postdoctoral Research Associate

Robotics for Building Management, Building Controls and Diagnostics, Smart Energy Management Systems, Indoor Environmental Quality, IoT Applications, Building Energy Simulation

PhD Students / Research Assistants

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Jintong Han

PhD Student

Continual Learning, Physical-based Deep Learning

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Kazuki Horikoshi

PhD Student

Applied Machine Learning, Building Performance Modeling, Building Information Modeling

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Siyu Cheng

PhD Student

Building Performance Modelling and Optimization

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Yaonan (Claire) Gu

PhD Student

Building Energy Simulation, Bayesian Calibration, Data Analytics and Applied Machine Learning

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Yiting Zhang

PhD Student

Building Performance Modeling, Large-scale Building Energy Simulation, Data Analytics and Machine Learning

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Yue Lei

PhD Student

Building Performance Modelling and Optimization, Model Prodictive Control (MPC), Indoor CFD Application, Data Analytics

Alumni

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Hongyuan Jia

Assistant Professor (Chongqing University of Science and Technology)

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Mingya Zhu

Lead Research Scientist (Siemens Ltd., China)

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Xilei Dai

Research Fellow (Nanyang Technological University)

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Wenxin Li

Associate Professor (Southeast University)

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Long Zheng

Research Fellow (National University of Singapore)

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Sicheng Zhan

Research Fellow (Massachusetts Institute of Technology)

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Yuzhen Peng

Senior Research Scientist (Bosch Research)

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Zeynep Duygu Tekler

Postdoctoral Researcher (University of Oxford)

Contact

  • +65 98210638
  • Department of the built environment, College of Design and Engineering, National University of Singapore, Singapore
  • email

Recent Publications

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Building energy flexibility is crucial for improving the local consumption of renewable energy and enhancing building self-sufficiency. …

The application of mixed-mode ventilation (MMV) in the tropics is challenging, given its hot and humid climate. Consequently, there are …

The proliferation of sensing technologies has allowed the collection of occupancy-related data to support various building …

The proliferation of sensing technologies has allowed the collection of occupancy-related data to support various building …

Renewable energy usage is continuing to increase as many countries worldwide are aiming to reach peak carbon emission and achieve …