Transforming Green & Sustainable Datacenter in Tropics with Machine Learning
Datacenter industry is growing four times faster than global GDP at the expense of high energy consumption and carbon emission. High energy cost has evolved to be the most pressing issue, contributing to 50% of life cycle operating cost. The industry-level risk-averse mind-set raises a barrier for technology adoption due to the unknown impact to business continuity. To make it worse, the silo operation between IT and non–IT department also makes it harder to take common actions towards efficient and sustainable operations. Our research will disrupt the traditional human-based control by offering data-driven solutions for energy saving and transforming Green & Sustainable Datacenter with deep learning.
Gary received his B.Eng. (1st Class Honours) in Computer Engineering from NTU, and M.Sc. in Industrial & Systems Engineering from NUS in 2012 and 2016 respectively. He worked with an American energy firm from 2012 to 2016. He published three research papers during his final year project with A/P Wen Yonggang and he was in the Deans’ List for all academic years. His current research interest is machine learning and its applications in energy optimization.