Ruixiao Yang

Ruixiao Yang

Mr

 https://orcid.org/0009-0009-3317-6401

Personal profile

Biography

I am a Spatial Data Science PhD candidate in the Spatial Policy and Analysis Laboratory (SPA-Lab) at the Department of Planning and Environmental Management, where I am supervised by Dr. Ransford Antwi Acheampong and Prof. Richard Kingston. I am also the recipient of the SEED PGR Scholarship. 

Prior to my Ph.D. study, I received my MSc degree from University College London (UCL) (Distinction) and BEng degree from King's College London (KCL). I also had professional experience working at companies and research institutions in engineering, public policy, and investment banking fields in Asia and Europe.

Research interests

My research interests widely incorporate the interdisciplinary areas of computer science, geographic information science, and urban spatial science, including: 

  • Spatiotemporal Data Mining
  • Urban Analytics
  • Transport/ Human Mobility Behaviour
  • Geospatial Artificial Intelligence

I am particularly interested in improving urban policy-making using multi-source big data and GeoAI techniques. My current PhD research is titled ‘Optimising Shared (e)Mobility Hub Location Planning: An Integrated Machine Learning and Agent-based Modelling Approach’. It aims to enhance the seamless transport network and optimise emerging shared mobility service deployment in terms of improving urban accessibility, local business vibrancy, and transport decarbonisation, thereby facilitating future sustainable transport development. This PhD research mainly consists of the following aspects:

  • Geospatial Artificial Intelligence for Understanding Urban Geo-semantics.
  • Spatiotemporal Analysis on Emerging Transport Mobility Behaviours.
  • E-mobility Hub Location Planning and Optimisation.

In addition to my PhD research directions, I’m also interested in topics related to GeoAI for sustainable investments. Please feel free to contact me for potential collaboration if any of my research areas interest you.

Methodological knowledge

My research employs quantitative methodologies, mainly including:

  • Spatiotemporal Big Data Analytics
  • Natural Language Processing
  • Deep Learning
  • Agent-based Modelling

Teaching

I contribute to the following modules as a graduate teaching assistant:

2024/2025 academic year:

  • PLAN40761/60761 Digital Planning - Spatial and Policy Analysis
  • PLAN61061 Real Estate Markets
  • PLAN10092 GIS & Digital Tools for Decision Making

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 8 - Decent Work and Economic Growth
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action
  • SDG 15 - Life on Land

Education/Academic qualification

Master in Science, Spatio-temporal Analytics and Big Data Mining, University College London (UCL)

Award Date: 1 Dec 2021

Bachelor of Engineering, Electronic Engineering, King's College London

Award Date: 1 Aug 2020

Research Beacons, Institutes and Platforms

  • Manchester Urban Institute
  • Digital Futures
  • Institute for Data Science and AI

Keywords

  • Urban Analytics
  • Geographic Information Science (GISc)
  • Spatiotemporal Data Mining
  • GeoAI Applications
  • Urban Mobility
  • Urban Big Data
  • Travel Behaviour
  • Transport Planning

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