Russell Richie

About

I am Director of Strategy and Content at the Progress and Poverty Institute, where I lead strategic planning, fundraising, and research in support of land value taxation and Georgist political economy. I also serve as Treasurer of 5th Square Advocacy, Philadelphia's urbanist advocacy organization focused on housing, transit, and street safety.

My research centers on land economics and urban policy — particularly the measurement of land values, the fiscal and distributional effects of land value taxation, and how Georgist ideas apply to contemporary housing and transportation challenges. I bring a computational and empirical lens to these questions, drawing on methods from data science, econometrics, and applied machine learning.

Before turning to land economics, I spent two decades in cognitive and behavioral science. I was Associate Director of Cognitive Science and MindCORE at the University of Pennsylvania, preceded by a postdoc in the Computational Behavioral Science Lab at Penn, and a stint as a data scientist at the Children's Hospital of Philadelphia. I received my PhD in Developmental Psychology from the University of Connecticut in 2017.

Curriculum vitae (PDF)

Research

Land Economics & Urban Policy

• Richie, R. (in prep). Land values can be estimated more accurately than property values in parameter recovery simulations. Preprint (SSRN). Accepted · RSAI 2025
• Richie, R., Miller, G., Hoskins, S., Faas, J. (in prep). Challenges and opportunities in messaging land value tax.
• Richie, R. (2024). Using aerial parcel imagery to predict single-family home sale prices.
  Unpublished manuscript. Final paper for MUSA 6500: Remote Sensing.

Cognitive & Behavioral Science

• Han, S., Richie, R., Shi, L., Tsui, F.R. (2024). Automated Matchmaking of Researcher Biosketches and Funder Requests for Proposals using Deep Neural Networks.
  IEEE Access, 12, 98096–98106.
• Richie, R., Ajmal, N.*, & Hebart, M. (2024). Unrealized promise of joint modeling of choice and reaction time in improving representation learning. *Student collaborator.
  46th Annual Meeting of the Cognitive Science Society.
• He, L.*, Richie, R.*, & Bhatia, S. (2024). Limitations to optimal search in naturalistic active learning. *Equal contribution.
  Journal of Experimental Psychology: General, 153(5), 1165–1188.
• Richie, R.*, Ruiz, V.*, Han, S., Shi, L., Tsui, F.R. (2023). Extracting social determinants of health events with transformer-based multitask, multilabel named entity recognition. *Equal contribution.
  Journal of the American Medical Informatics Association.
• Han, S., Shi, L., Richie, R., Tsui, F.R. (2022). Building Siamese attention-augmented-recurrent convolutional neural networks for document similarity scoring.
  Information Sciences, 615, 90–102.
• Richie, R., Aka, A., & Bhatia, S. (2022). Free association in bidirectional memory networks.
  Psychological Review.
• Bhatia, S., & Richie, R. (2022). Transformer networks of human concept knowledge.
  Psychological Review.
• Richie, R., Grover, S., Tsui, F.R. (2022). Inter-annotator agreement is not the ceiling of machine learning performance.
  Proceedings of the 21st Workshop on Biomedical Language Processing. ACL.
• Han, S., Zhang, R.F., Shi, L., Richie, R., et al. (2022). Classifying social determinants of health from unstructured electronic health records using deep learning-based NLP.
  Journal of Biomedical Informatics, 103984.
• Singh, M.*, Richie, R.*, & Bhatia, S. (2022). Representing and predicting everyday behavior. *Equal contribution.
  Computational Brain & Behavior, 5(1), 1–21.
• Zhao, W.J., Richie, R., & Bhatia, S. (2022). Process and content in decisions from memory.
  Psychological Review, 129(1), 73–106.
• Richie, R., & Bhatia, S. (2022). Knowledge in everyday judgment and decision making: An introduction to the distributed semantics approach.
  In Boyd & Dehghani (Eds.), The Atlas of Language Analysis in Psychology. Guilford Press.
• Richie, R., & Bhatia, S. (2021). Similarity judgment within and across categories: A comprehensive model comparison.
  Cognitive Science, 45(8), e13030.
• Richie, R., & Verheyen, S. (2020). Using cross-validation to select dimensionality in multidimensional scaling.
  ICCM 2020 (extended abstract).
• Richie, R.*, Hall, M.*, Cho, P.W., & Coppola, M. (2020). Converging evidence: Enhanced conventionalization of gestural referring expressions in richly-connected networks. *Equal contribution.
  Language Dynamics and Change, 10(2), 259–290.
• Richie, R., White, B., Hout, M.C., & Bhatia, S. (2020). The spatial arrangement method of measuring similarity can capture high-dimensional, semantic structures.
  Behavior Research Methods, 52, 1906–1928.
• Richie, R., Zou, W., & Bhatia, S. (2019). Predicting high-level human judgment across diverse behavioral domains.
  Collabra: Psychology, 5(1), 50.
• Bhatia, S., Richie, R., & Zou, W. (2019). Distributed semantic representations for modeling human judgment.
  Current Opinion in Behavioral Sciences, 29, 31–36.
• Richie, R. (2016). Functionalism in the lexicon: Where is it, and how did it get there?
  The Mental Lexicon, 11(3), 429–466.
• Richie, R., Yang, C., & Coppola, M. (2014). Modeling the emergence of natural language lexicons in homesign systems.
  Topics in Cognitive Science, 6(1), 183–195.
• Roseberry, S., Richie, R., Hirsh-Pasek, K., Golinkoff, R.M., & Shipley, T. (2011). Babies catch a break: 7- to 9-month-olds track transitional probabilities in continuous dynamic events.
  Psychological Science, 22(11), 1422–1424.

Writing

• Mayor-elect Zohran Mamdani, Champion of the Landless
  Progress & Poverty · November 2025
  On the parallels between Mamdani's mayoral campaign and Henry George's 1886 run, and what his victory means for land tax politics in New York.
• A Georgist's Reflections on YIMBYtown
  Progress & Poverty · October 2025
  Why land value taxation and congestion pricing remain underrepresented in the pro-housing movement, and what message-testing research can offer.

Connect

The best way to reach me is by email: drussellmrichie@gmail.com