Dr Clayton Miller
National University of Singapore, SingaporeLeveraging Open Energy Data for Buildings - From the ASHRAE Great Energy Predictor III Competition to the Annex 81 Open Data Sandbox
Abstract:
A surge in data-driven methods for building energy analysis is occurring due to the increase in publicly-available open data sets from the industry and research communities. Dr. Miller will discuss a recent and prominent example of utilising such resources in the context of the Great Energy Predictor III Kaggle Competition (https://www.kaggle.com/c/ashrae-energy-prediction) held in Oct-Dec. 2019 that was hosted by the ASHRAE organization. Over 3,600 teams from around the world competed for US$25k in prize money to create the most accurate data-driven hourly building energy models for over 2,300 energy meters collected from 1,448 buildings. Dr. Miller will cover the process of crowdsourcing and capturing open and closed data sets from across the world for the competition. He will also overview the potential applications of these winning solutions and discuss their common attributes, such as the use of large ensembles of various types of gradient boosting trees. He will discuss how and where the top five winning models and two-thirds of the competition data set have been released as new open data sets for building energy research and industry professionals to use. Dr. Miller will then cover the initial stages for a large data sandbox environment being driven by the Annex 81 Data-driven Smart Buildings (https://annex81.iea-ebc.org/) community that is collecting open data sets from numerous applications and organise them in the Kaggle platform with code examples and documentation. This sandbox will enhance the accessibility and ease-of-use for researchers seeking open data or sharing their own data online as well as a library of tutorials for those who want to learn data science.
Biography:
Dr. Clayton Miller is an Assistant Professor at the National University of Singapore (NUS) as the leader of the Building and Urban Data Science (BUDS) Lab. He is the Co-Leader of Theme D - Data Analytics at the UC Berkeley SinBerBEST2 Lab and Subtask 4 of the IEA Annex 79 Occupant-Centric Building Design and Operation. He was recently a Fellow at the Institute of Technology in Architecture (ITA) at the ETH Zürich (Swiss Federal Institute of Technology - Zurich). His research focuses on performance data analytics using thousands of real-world case study buildings collected from facilities around the world. He was formerly the CTO of a Singaporean startup company, Optiras Pte Ltd. that developed monitoring technologies for buildings. Clayton holds a Doctorate of Sciences (Dr. sc. ETH Zurich) from the ETH Zürich, a MSc. (Building) from the National University of Singapore (NUS), and a Master of Architectural Engineering (MAE) and BSc. from the University of Nebraska. He is a former U.S. Fulbright Student Scholar to Singapore at NUS and a Walter Scott Jr. Scholar in Nebraska.
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