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PhD Candidate in the Mobility and Behavior Lab at Northwestern University

Education

Northwestern University (Evanston, IL)
PhD Candidate, Transportation Systems Analysis and Planning (Sep. 21 - Present)
NSF Graduate Research Fellow (Sep. 23 - Present)

Goshen College (Goshen, IN)
B.A., Physics, minor in Mathematics (2019)

Major Awards and Achievements

  • National Science Foundation Graduate Research Fellowship recipient (Sep. 2023 - Present)
  • NAIA Men’s Soccer Academic All-American (2017, 2018)

Publications and Presentations

Journal Articles

  • Aeschliman, S. & Stathopoulos, A. (2025). “Trade-off is transit public safety interventions: balancing enforcement and quality improvements.” Transportation Research Part A: Policy and Practice.
  • Aeschliman, S., Huang, E., Hofstra, A., & Stathopoulos, A. (2025). “Examining riders’ subjective equity standards for transit service: How will they shape future transit planning and operations?” Transport Policy.
  • Said, M., Aeschliman, S., & Stathopoulos, A. (2023). “Robots at your doorstep: acceptance of near-future technologies for automated parcel delivery.” Scientific Reports.
  • Alam, Md.R., Hou, C., Aeschliman, S., Zhou, Y., & Guo, Z. (2022). “Optimization-based trip chain emulation for electrified ride-sourcing charging demand analyses.” Transportation Letters.
  • Zhou, Y., Aeschliman, S., & Gohlke, D. (2021). “Affordability and household transportation fuel costs by region and socioeconomic factors.” Transportation Research Record.

Conference Papers and Presentations

  • Aeschliman, S., Pougala, J., & Stathopoulos, A. “Choice-survival models for trasit panel survey participation.” TRB 2026, Washington, DC.
  • Aeschliman, S. & Stathopoulos, A. “Fully-Bayesian Imputation for Transit Panel Survey Data.” Modeling Mobility 2025, Minneapolis, MN.
  • Aeschliman, S. & Stathopoulos, A. “Improving transit panel survey inferences: imputation, selection models, and survival analysis.” ITEA 2025, Evanston, IL.
  • Aeschliman, S. & Stathopoulos, A. “Tracking Public Transit Satisfaction with Longitudinal Mulitilevel Models.” TRB 2025, Washington, DC.
  • Aeschliman, S. & Stathopoulos, A. “Counter-productive safety interventions? Satisfaction and safety trade-offs in post-pandemic transit ridership.” IATBR 2024, Vienna.
  • Aeschliman, S. & Stathopoulos, A. “The Return to Transit in a Changing Landscape: Telework and Safety Concerns.” TRB 2024, Washington, DC.
  • Said, M., Aeschliman, S., & Stathopoulos, A. “Robots at Your Doorstep? Acceptance of Near-Future Modes for Parcel Delivery.” TRB 2023, Washington, DC.
  • Aeschliman, S., Zhou, Y., Macal. C., & Zhou, Z., “Agent-based modeling of electric vehicles with time-of-use electricity rates”, EVS 33, Portland, OR, June 14-17, 2020.
  • Hou, C., Guo, Z., Aeschliman, S., Zhou, Y., Afifah, F., & Huang, J., “Energy impact analyses of electrified ride-sourcing services without trip chain data”, TRB 2021.

Technical Reports

  • Zhou, Y., Siddique, N., Mintz, M., Aeschliman, S., & Macal, C. (2022). “Electric Vehicle and Infrastructure Systems Modeling in Washington D.C. and Baltimore” (ANL-22/28). Argonne National Lab. (ANL), Argonne, IL (United States); Exelon, Chicago, IL (United States).
  • Zhou, Y., Mintz, M., Stephens, T., Aeschliman, S., & Macal, C., “Electric Vehicle Adoption in Illinois”, Energy Systems Division, Argonne National Laboratory, June 2020.
  • Zhou, Y., Aeschliman, S., & Gohlke, D., “Affordability and Household Transportation Fuel Costs by Region and Socioeconomic Factors”, Energy Systems Division, Argonne National Laboratory, December 2020.

Other Presentations

  • “Simulating Forest Fires” (with Luke Rush), Goshen College Academic Symposium, March 15, 2019.

Teaching

Graduate TA: Engineering Analysis II
Northwestern University, McCormick School of Engineering (Winter 2023)
  Weekly recitations, office hours, and grading

Professional Experience

Systems Modeling and Software Engineer
Argonne National Laboratory, Energy Systems Division (May 2020 - Sep. 2021)

  • Ran and maintained the agent-based transportation energy analysis model (ATEAM) using the Repast Simphony modeling platform
  • Performed data analysis and visualization with Python and R on various transportation energy-related projects for government and corporate sponsors
  • Used machine learning techniques such as gradient boosting and deep neural networks for predictions on vehicle miles traveled, freight mobility, and more
  • Contributed to technical reports prepared by the group for public access
  • Maintained database of alternative fuel vehicle sales data in the U.S

Internships

Department of Energy Science Undergraduate Laboratory Internship
Argonne National Laboratory (Sep. 2019 - Apr. 2020)

  • Learned Java and its implementation in ATEAM agent-based model
  • Devised and performed a case study on time-of-use electricity rates in ATEAM, which culminated in a conference paper submission and acceptance
  • Maintained Argonne’s alternative fuel vehicle sales database on a monthly basis

Maple Scholars Research Program
Goshen College (May 2017 - July 2017)

  • Designed and built small, car battery-powered air quality sensors (for Ozone, CO, VOCs, and particulates) with a Raspberry Pi controller
  • Programmed the controller’s data collection (including communication with sensors), power management, and GPS tracking using Python and C
  • Visualized Goshen-area spatial air quality data on a website using the Google Maps API