Emma Von Hoene

Emma
Von Hoene

Ph.D. candidate in Earth Systems and Geoinformation Sciences, George Mason University

I develop and advance geospatial computational methods to model human behavior across space and time, with applications in public health.

Ph.D. expected May 2027

Emma Von Hoene in a green graduation gown, seated in front of the George Mason statue on the Fairfax campus.

About

I’m a Ph.D. candidate in Earth Systems and Geoinformation Sciences at George Mason University and a geospatial computational scientist specializing in methods for representing human behavior and populations across space and time. My research develops methods for spatially-explicit agent-based modeling, population synthesis, microsimulation, machine learning, and artificial intelligence (AI), with applications in public health. These methods are designed to extend beyond public health to address other human challenges, such as those in urban systems, climate adaptation, environmental change, disaster response, and national security.

My dissertation, Advancing Spatial Agent-Based Modeling and Microsimulation for Public Health Applications, is advised by Drs. Taylor Anderson, Hamdi Kavak, Amira Roess, and Chaowei Yang. I also hold an M.S. in Geoinformatics and Geospatial Intelligence and a B.S. in Geography, graduating summa cum laude from George Mason’s Honors College.

Since 2024, I have also worked part-time as a geospatial and imagery analyst with the U.S. Department of Defense, applying spatial data science to large-scale datasets and translating analytical findings into insights for senior decision-makers.

I work in Python, R, Java, MATLAB, and SQL (PostgreSQL/PostGIS, MongoDB, Neo4j), build models in NetLogo and Repast/Repast4Py, and map with ArcGIS Pro, ArcPy, and QGIS.

An illustrative simulation of disease spread at George Mason University, Fairfax, Virginia, USA campus. This is a simplification of my work at GIScience (2023) and ACM SIGSPATIAL GeoSim (2023). Each dot is one simulated person.

Recognition

  • 2023–

    Presidential Scholarship

    Office of the Provost, George Mason University

  • 2024

    Ph.D. Colloquium Runner-Up Paper

    Annual Modeling and Simulation Conference (ANNSIM)

  • 2022

    Outstanding Bachelor of Science Student

    Department of Geography, George Mason University

  • 2022

    Outstanding Service to the Department

    Department of Geography, George Mason University

  • 2021

    DigitalGlobe Scholar

    DigitalGlobe Foundation

Research

My research advances spatial data science, machine learning, AI and computational modeling and simulation to better represent human behavior and population differences across space and time. I develop methods that address challenges in representing individual decision-making, generating realistic populations, estimating health outcomes at fine geographic scales, and identifying spatial variation in the factors associated with those outcomes.

Public health provides a central application for this work, offering complex problems that require detailed representations of people, behavior, and place. The methods are designed to be transferable to other complex social and environmental systems, including urban systems, climate adaptation, environmental change, disaster response, and national security.

Much of this research is part of the NSF-funded project Data-Driven Modeling to Improve Understanding of Human Behavior, Mobility, and Disease Spread.

Research Areas and Framework

Select an area to learn more and see how it connects to the others.

Applied to public health, and transferable to other areas including urban systems, climate adaptation, environmental change, disaster response, and national security.

01Individual decision-making in agent-based models

I develop data-driven methods for representing how individual behaviors respond to changing conditions in agent-based models (ABMs). Rather than assigning behaviors such as vaccination using fixed probabilities, these approaches incorporate relationships between individual characteristics, contextual factors, and behavioral outcomes. This work supports more realistic simulations, such as how health behaviors evolve during an outbreak and influence disease transmission.

GIScience (2023); ACM SIGSPATIAL GeoSim (2023); ANNSIM Ph.D. Colloquium runner-up paper (2024); Journal of Artificial Societies and Social Simulation (2026).

02Population synthesis for realistic agents

I develop population synthesis methods that integrate individual-level survey data with population data to represent demographic characteristics, behaviors, attitudes, and perceptions. By extending methods such as iterative proportional fitting (IPF), I investigate how to generate more realistic agents and preserve meaningful relationships among their attributes and behaviors. These methods support ABMs and other applications that require detailed representations of populations.

PLOS Computational Biology (2025); Winter Simulation Conference (2025); invited talks at MITRE and Epistemix.

03Small-area estimation and spatial microsimulation

I develop spatial microsimulation methods to estimate aggregated behaviors and outcomes at fine spatial scales where direct measurements are limited or unavailable, particularly in the public health domain. Through leading the development of SHAPE (Spatial Health and Population Estimator), I integrate survey and population data to generate estimates of 13 health conditions across geographic areas and population subgroups throughout the United States. This work addresses gaps in the availability of fine-scale health data and supports analyses of geographic disparities that cannot be captured through national or state-level estimates alone.

International Journal of Health Geographics (2026); a national dataset forthcoming in Scientific Data.

04Spatial data science for health disparities

I use spatial statistical and machine learning methods to investigate how relationships between social, demographic, and environmental factors and health outcomes vary across places and spatial scales. By developing and applying approaches such as multiscale geographically weighted regression and geographically weighted random forests, I examine where associations differ and how these differences shape geographic patterns, such as health disparities. This work can help identify locally relevant factors for further investigation and inform place-based interventions.

International Cartographic Conference (2025), on suicide determinants across U.S. counties.

05Generative AI for population modeling and simulation

I investigate how generative AI and large language models can support the representation of human populations and behavior in computational models. This work explores the use of LLMs to generate synthetic survey data, represent behavioral characteristics, and support data-driven population synthesis. I am interested in evaluating when AI-generated data can meaningfully complement observed data and how these approaches can improve the representation of human behavior in simulation.

Winter Simulation Conference (2026); American Association of Geographers Annual Meeting (2027, accepted).

Applications

Across these research areas, I apply computational methods to public health challenges, including COVID-19 transmission and vaccination behavior, chronic conditions and health behaviors such as heart disease, cancer, smoking, and depression, suicide risk, and school-entry vaccine exemptions in Virginia. I am also extending this work to investigate zoonotic disease transmission involving white-tailed deer and interactions between humans and deer.

Although public health is a central focus, the underlying methodological challenges extend beyond any single domain. The same approaches to population representation, behavioral modeling, spatial estimation, and geographic analysis can inform research on complex human-environment systems, including climate adaptation, disaster response, urban development, and the effects of environmental and economic change on human behavior and mobility.

Publications

Published Peer-Reviewed Journal Articles 3

  1. 2026

    Evaluation of a Spatial Microsimulation Framework for Small-Area Estimation of Population Health Outcomes Using the Behavioral Risk Factor Surveillance System

    Von Hoene, E., Gupta, A., Kavak, H., Roess, A., & Anderson, T. International Journal of Health Geographics.

    Article GitHub

  2. 2026

    All Models Are Wrong, But Can They Be Useful? Lessons from COVID-19 Agent-Based Models: A Systematic Review

    Von Hoene, E., Von Hoene, S., Péter, S., Hopson, E., Csizmadia, E., Fenyk, F., Barner, K., Leslie, T., Kavak, H., Züfle, A., Roess, A., & Anderson, T. Journal of Artificial Societies and Social Simulation, 29(1), 7.

    Article

  3. 2025

    Synthetic Population Generation with Public Health Characteristics for Spatial Agent-Based Models

    Von Hoene, E., Roess, A., Kavak, H., & Anderson, T. PLOS Computational Biology.

    Article GitHub

Published Peer-Reviewed Conference Papers 4

  1. 2026

    Evaluating the Transferability of a Synthetic Population Generation Approach for Public Health Applications

    Von Hoene, E., Gupta, A., Kavak, H., Roess, A., & Anderson, T. Proceedings of the 2025 Winter Simulation Conference.

    Article

  2. 2025

    Identifying Geographic Disparities in Suicide Determinants Across United States Counties with Spatial Modeling

    Von Hoene, E., Roess, A., Adams, L., Yang, R., & Anderson, T. Proceedings of the 32nd International Cartographic Conference.

    Article

  3. 2023

    A Framework for Simulating Emergent Health Behaviors in Spatial Agent-Based Models of Disease Spread

    Von Hoene, E., Roess, A., Achuthan, S., & Anderson, T. Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation.

    Article

  4. 2023

    A Data-Driven Decision-Making Framework for Spatial Agent-Based Models of Infectious Disease Spread (Short Paper)

    Von Hoene, E., Roess, A., & Anderson, T. 12th International Conference on Geographic Information Science (GIScience 2023).

    Article

Accepted and Forthcoming 4

  1. 2026

    A Synthetic Population and Small-area Estimate Dataset for Health Behaviors and Outcomes in the United States

    Von Hoene, E., Gupta, A., Von Hoene, S., Kavak, H., Roess, A., & Anderson, T. Scientific Data.

  2. 2026

    Integrating Agentic AI with Agent-Based Models for Mobile Vaccination Allocation

    Zhang, V., Von Hoene, E., & Anderson, T. Proceedings of the 1st ACM SIGSPATIAL Student Challenge on Open Agents with Spatial Intelligence for Social Good (OASIS 2026).

  3. 2026

    Using Zero-Shot LLM-Generated Survey Data for Geographically Explicit Population Synthesis

    Anderson, T., Von Hoene, S., Cinar, O., Von Hoene, E., Roess, A., Crooks, A., & Kavak, H. Proceedings of the 2026 Winter Simulation Conference.

    Article

  4. 2026

    Leveraging Large Language Models for Systematic Literature Review of Disease Spread Models

    Cinar, O., Ozkose, T., Von Hoene, E., Roess, A., Anderson, T., & Kavak, H. Proceedings of the 2026 Winter Simulation Conference.

    Article

Submitted and Under Review 3

  1. 2026

    Synthetic Populations for Public Health Policy and Planning (Book Chapter)

    Von Hoene, E., Kavak, H., & Anderson, T. Invited chapter in Synthetic Population (Simulation Foundations, Methods, and Applications series). Springer Nature.

  2. 2026

    Mobility and Contact Networks Shape Epidemic Outcomes: A Large-Scale Agent-Based Modeling Study

    Singh Atwal, K., Von Hoene, E., Amiri, H., Pfoser, D., Züfle, A., & Anderson, T. Nature Communications.

    Article

  3. 2026

    Geographically Weighted Surrogate Models for Rapid Small-Area Chronic Disease Estimation

    Gupta, A., Péter, S., Von Hoene, S., Von Hoene, E., & Anderson, T. Applied Geography.

    Article

In Preparation 2

  1. 2026

    Evaluating the Effects of Health Behavior Initialization on Demographic and Spatial Disparities in Agent-Based Models of Infectious Disease Spread

    Von Hoene, E., & Anderson, T. For International Journal of Geographical Information Science.

  2. 2026

    School-Entry MMR Vaccine Exemption in Private and Public Schools in Virginia, 2008–2023

    Roess, A., McNally, K., Von Hoene, E., Karably, B., & Anderson, T. For Vaccine.

Talks and Presentations

Invited

  1. 2026

    Advancing Synthetic Population Generation with Health Characteristics for Agent-based Models and Small-area Estimation

    Lauren Gardner’s Lab, Johns Hopkins University, February 3

    Slides

  2. 2025

    SHAPE: Spatial Health and Population Estimator

    GIS Day Graduate Research Lightning Talk, George Mason University, November 20

  3. 2025

    Synthetic Population Generation with Public Health Characteristics for Spatial Agent-Based Models

    Modeling and Analysis Innovation Center Brown Bag, MITRE, April 24

    Slides

  4. 2025

    Generating Synthetic Populations with Realistic Attitudes and Perceptions

    With T. Anderson. Epistemix, January 7

Conference Presentations

  1. 2027

    Generative AI for Population Synthesis in Spatial Agent-Based Models: A Case Study of COVID-19 Vaccination and Disease Spread

    American Association of Geographers Annual Meeting, New York, February 8–12

  2. 2026

    Using Zero-Shot LLM-Generated Survey Data for Geographically Explicit Population Synthesis

    Winter Simulation Conference, Glasgow, Scotland, December 6–9

  3. 2025

    Evaluating the Transferability of a Synthetic Population Generation Approach for Public Health Applications

    Winter Simulation Conference, Seattle, December 7–10

    Slides

  4. 2025

    SHAPE: Spatial Health and Population Estimator

    18th Annual Symposium on Biomathematics and Ecology Education and Research, Fairfax, Virginia, November 7–9

  5. 2025

    Characteristics of Human, Pet and Deer Contact Captured on Social Media and Implications for Zoonotic Disease Transmission

    American Public Health Association Annual Meeting, Washington, D.C., November 2–5

  6. 2025

    Identifying Geographic Disparities in Suicide Determinants Across United States Counties with Spatial Modeling

    32nd International Cartographic Conference, Vancouver, August 18–22

    Slides

  7. 2024

    Leveraging Supervised Machine Learning to Predict Health Behaviors in Spatial Agent-Based Models of Disease Spread

    Annual Modeling and Simulation Conference, Washington, D.C., May 20–23

  8. 2023

    A Framework for Simulating Emergent Health Behaviors in Spatial Agent-Based Models of Disease Spread

    31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Hamburg, November 13–16

    Slides

  9. 2023

    A Data-Driven Decision-Making Framework for Spatial Agent-Based Models of Infectious Disease Spread

    12th International Conference on Geographic Information Science, Leeds, September 12–15

  10. 2022

    Integrating Behavioral Theories and Agent-Based Models of Disease Spread

    69th North American Meetings of the Regional Science Association International, Montreal, November 9–12

    Slides

Teaching and Mentoring

Teaching Philosophy

Drawing on my work in spatial data science and computational modeling, I help students develop strong technical skills while learning to apply them to questions involving people, places, and environmental and societal challenges.

My teaching emphasizes systematic, interactive, and collaborative learning, grounded in enthusiasm for the subject and tailored to students’ diverse learning needs. In practice, this means connecting course concepts to current events, pairing step-by-step demonstrations with hands-on exercises, and designing projects that ask students to analyze real-world problems and communicate their findings to an audience. My goal is for students to leave my courses with not only technical knowledge, but also the critical thinking, problem-solving, and communication skills to apply what they have learned in their careers and communities.

Instructor of Record

Human Geography (GGS 103), George Mason University, Spring 2026, Fall 2026 semesters

I independently developed and teach this in-person undergraduate course.

Spring 2026 student evaluations, mean out of 5 (scale shown from 4.0 to 5.0). 11 of 21 students responded.
My course Department mean University mean

Learning outcomes 4.52dept 4.33univ 4.27
Course environment 4.56dept 4.41univ 4.33
Course organization 4.67dept 4.43univ 4.33
Overall, three areas 4.58dept 4.39univ 4.31

Overall is the average of the 12 questions in these three areas. University averages are calculated from the question-level university means in the evaluation report.

Selected Course Materials

  • SyllabusGGS 103-001: Human Geography, Spring 2026Syllabus
  • Lecture slidesPopulation Geography: Distribution and DensitySlides
  • Lecture slidesPopulation Geography: Dynamics and MigrationSlides
  • Lecture slidesEnvironmental GeographySlides
  • Active learning activityMapping Global Patterns of HDIInstructions
  • Active learning activityCampus Mapping Scavenger Hunt: Human–Environment InteractionsInstructions

Course Development and Guest Lectures

  1. 2025

    Course Co-Developer, Advanced Geographic Information Systems (GGS 563)

    George Mason University. Co-developed the graduate course in Summer 2025 and assisted with teaching its modules in Fall 2025.

  2. 2022–26

    Guest Lecturer, 10 lectures

    George Mason University. Introduction to GIS (GGS 311); Advanced GIS (GGS 563); Spatial Modeling for Public Health (GGS 432/632); Spatial Agent-Based Models of Human-Environment Interactions (CSS 645/GGS 631). Topics ranged from vector analysis and cartography to geographically weighted regression, NetLogo, and synthetic population generation.

    Selected Lecture Slides

    • CSS 645 / GGS 631, 2026Module 14: Synthetic PopulationsSlides
    • GGS 563, Fall 2025Geographically Weighted RegressionSlides
    • GGS 563, Fall 2025Spatial Autocorrelation and Local Moran’s ISlides
    • GGS 563, Fall 2025Introduction to Spatial Modeling and RegressionSlides
    • GGS 311, 2022Vector Spatial Analysis: Fairfax County CrimeSlides
  3. 2019–21

    Learning Assistant

    George Mason University. Undergraduate instruction, course development, and peer tutoring and mentoring.

Mentoring

  1. 2025

    Co-Mentor, Summer Team Impact Project (STIP)

    George Mason University. Seven undergraduate students.

  2. 2022–26

    Co-Mentor, Aspiring Scientists Summer Internship Program (ASSIP)

    George Mason University. Three high school researchers, across five summers.

Tutoring

GIS Tutor, Wyzant

I tutor students one-on-one in geographic information systems through Wyzant, helping them build software skills in ArcMap and ArcGIS Pro and work through course projects.

  • 5.0average star rating
  • 101student reviews
  • 500+tutoring hours

Student Reviews

Awesome tutor! Very knowledgeable and patient.

Emma is an amazing GIS tutor that helped me with 7 different GIS projects working in ArcMap. She is very knowledgeable and was able to help me complete projects in a timely manner, following the specific instructions given by my professor. Emma is always on time, patient, and answered any questions I had. Highly recommend!

Student review on Wyzant

Knowledgeable and patient tutor

I had an excellent experience with my tutor Emma. They were extremely knowledgeable on ArcGis and went above and beyond to ensure that I understood the material. They were very attentive and responsive with great communication.

Student review on Wyzant

So patient & knowledgeable!

Emma is amazing, she has an expansive knowledge on anything GIS programming, and does a great job of simplifying it ! She was so good at breaking things down, discussing the options and seeing what my comfort level is. Emma has helped so much with my Geographic Information Systems minor and introductions to ArcGISPro. Don’t hesitate to call her for your GIS needs, she knows her stuff & makes it look easy!

Student review on Wyzant

Service and Outreach

I co-organized George Mason’s workshops for Females of Color and those Underrepresented in STEM (2022, 2023) and the STEM Bridge Camp (2023), and have reviewed research posters for the Loudoun County Public Schools Dual-Enrollment STEM Research Symposium (2023, 2026). I’ve spoken on student panels about graduate research and STEM at Mason, and volunteered at Science Connect, GIS Day, and Bull Run Elementary’s STEAM Night.

Selected Workshop Materials

  • FOCUS WorkshopExploring and Mapping George Mason University with Geospatial Technologies (with T. Anderson) SlidesInstruction sheet

Contact

I’m glad to hear about collaborations, talks, and opportunities. Email is the best way to reach me.

evonhoen@gmu.edu
Department of Geography and Geoinformation Science
George Mason University, Fairfax, Virginia