PhD Student (Year 4)

TAN Hongjun 谭鸿骏

EIES-Lab · The Hong Kong Polytechnic University

I am an interdisciplinary researcher working across climate change, renewable energy, artificial intelligence, and urban sustainability, with expertise in AI, generative AI, remote sensing, GIS, photovoltaics, and data-driven modelling. My strength lies in connecting advanced computational approaches with real-world energy and sustainability challenges, supported by a strong track record of interdisciplinary research and publication.

I have gained international research experience at the Environmental Change Institute (ECI), University of Oxford, supported by the competitive RSAP and ICRF Scholarships. This experience has further shaped my ability to work across disciplines, institutions, and international research environments.

Beyond research, I built strong leadership, communication, and organizational skills. I have organized and supported 10+ international conferences across the UK, Qatar, Japan, South Korea, Thailand, and beyond, with individual events attracting up to 600 participants. My experience also extends to academic publishing and peer-review coordination.

Outside academia, 5+ years of dance teaching and 3+ years of scuba diving have strengthened my communication, adaptability, creativity, and teamwork.

Together, these experiences allow me to bring scientific expertise, technical capability, international perspective, and people-centered leadership to collaborative and interdisciplinary environments.

TAN Hongjun

Research Interests

  1. 01Climate change
  2. 02Renewable energy
  3. 03Artificial Intelligence
  4. 04Urban sustainability

Education

  1. 2026

    Exchange

    University of Oxford

  2. 2023 – 2026

    PhD

    The Hong Kong Polytechnic University

  3. 2020 – 2023

    Master of Engineering

    Tongji University

Featured Publications

Solar energy

Global estimation of building-integrated facade and rooftop photovoltaic potential by integrating 3D building footprint and spatio-temporal datasets

Combines 3D building footprints with meteorological data to estimate building-integrated PV potential in 120 cities worldwide; facade potential averages 68.2% of rooftop potential.

· Nexus

See all publications

Talks

Talks to come.

Projects

Projects to come.

Skills

Skills to come.

Awards

Awards to come.