BEEE is delighted to announce the appointment of Prof. Guo Zhiling as an Assistant Professor, effective from 19th May 2025. Prof. Guo has been an integral part of our community, and we look forward to his continued contributions in his new role.
Prof. Guo Zhiling earned his Master's and PhD degrees in Japan at the Center for Spatial Information Science, The University of Tokyo.
Prof. Guo’s research spans a broad range of interdisciplinary areas, including smart energy, data science, artificial internet of things (AIoT), and remote sensing. Upon completing his Ph.D., he gained valuable industrial experience as a Data Scientist in the R&D and IoT division of LocationMind Inc., Tokyo. He also held research positions at The University of Tokyo and served as a fellow under the prestigious Japan Society for the Promotion of Science (JSPS).
In 2023, Prof. Guo joined the BEEE at The Hong Kong Polytechnic University. He currently serves as Director of the DigiEnergy Lab under the International Centre of Urban Energy Nexus (UEX). He also serves as Assistant Editor for Nexus (Cell Press) and Advances in Applied Energy (Elsevier).
Prof. Guo has contributed to a number of publications in reputable journals and conferences, with more than 1,700 citations, an h-index of 23, and an i10-index of 33. He has secured competitive research funding across Japan, Hong Kong, and Mainland China, including as Principal Investigator (PI) of the JSPS Young Scientists Fund and Co-PI of the National Key R&D Program of China.
Prof. Guo’s current research focuses on the development of high-resolution spatiotemporal datasets through generative AI-enhanced geospatial data, with applications for renewable energy mapping at a global scale. His work integrates remote sensing and machine learning to analyze building envelopes and identify photovoltaic (PV) panel characteristics. He also develops spatial-temporal models for estimating renewable energy generation potential, leveraging advanced spatial-physical modeling and deep learning techniques to deliver real-time, accurate, and scalable simulation results. In addition, Prof. Guo is leading the development of an interactive Renewable Energy Simulation and Digital Twin Toolkit, designed to support the design of smart energy infrastructure and facilitate data-driven decision-making for sustainable urban energy systems.
