Madison Lore

Madison Lore is an Assistant Professor of Urban Planning and Data Analytics, where her research explores the intersection of urban data science, social processes, and sustainable transitions. Her work examines socially responsible uses of large-scale data methods to reveal how environments of information overload can influence public perception and uptake of sustainable behaviors. These core conditions form the basis for research in equitable distribution of resources, institutional influences on behaviors, and individual support for sustainable policies. Madison received her Ph.D. from the School of Community and Regional Planning at the University of British Columbia. She also holds a Master's degree in Applied Mathematics and a Bachelor's in Mathematics and Physics from Rensselaer Polytechnic Institute.

Academic Research/Specialty Areas

  • Infrastructure planning
  • Land use/spatial planning
  • Social policy
  • Sustainability
  • Transportation planning
  • Data analytics
  • Energy planning
  • Machine learning

Awards, Grants, and Fellowships (Selected)

  • "Deciphering the Language of Big Oil's Role in Climate Action Denial, Delay, and Deception," Climate Social Science Network (2024)
  • Vanier Canada Graduate Scholarship (2023-2026)
  • Bombardier Sustainable Transportation Fellowship (2022)
  • The Bill and Nancy Siegmann Applied Mathematical Modeling Prize (2018)
  • Leonhard Euler Award for Excellence in Mathematical Modeling (2016)

Exhibitions and Presentations (Selected)

  • "Pathways of Support and Opposition to Renewable Energy Projects", Association of Collegiate Schools of Planning Annual Conference, Seattle, Washington (2024)
  • "Identifying Large-scale Social Norms in Mode Share through Crowdsource Passive Data", 17th International Conference on Travel Behavior Research, Vienna, Austria (2024)
  • "Dynamics of Social Media on Transit Choice", American Planning Association National Planning Conference, Philadelphia, PA (2023)

Publications (Selected)

  • Lore, M., Harten, J. G., & Boeing, G. (2024). "A hybrid deep learning method for identifying topics in large-scale urban text data: Benefits and trade-offs." Computers, Environment, and Urban Systems, 111, 102131. 
  • Hosford, K., Yanagawa, C., Lore, M., & Winters, M. (2024). "Effects of Mobi's equity initiatives on public bike share access and use." Transportation Research Part D, 131, 104223. 
  • Lore, M., & Tran, M. (2023). "Learning transportation preferences from online business review language." Transportation Research Board Annual Meeting. Washington, DC.
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