Resume

Xinlan Luo

Urban spatial behavior · ABM · RL · LLM

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Education

Avg 87/100, GPA 4.21/5.0

Relevant: Geo-spatial Information Analysis Methods (96/100); Spatio-Temporal Behavior and Planning (92/100); Quantitative Analytics for Planning (87/100)

Avg 92/100, GPA 4.7/5.0 · Rank 6/81

Relevant: Introduction to Python Programming; Urban Analytical Methods; Urban Roads and Transportation

Projects / Experience

Project 1 — Behavioral Modeling and Agentic Simulation of High-Density Campus Dining Dynamics [Project Leader]

  • Phase I (Jan. 2024 – May 2025): Reconstructed ≈27,800 students’ dining sequences from >6M smart-card records fused with class, access, weather, and distance data; built entropy-based concentration index; estimated MNL & IRL for time/venue choice under constraints.
  • Evaluated demand-management strategies (e.g., staggered classes, dorm reassignment) via genetic algorithm: up to ~57% fewer peak waiting incidents and ~18.5% lower spatial imbalance.
  • Phase II (Jul. 2024 – Present): Integrated Mesa ABM with an LLM (DeepSeek) as cognitive engine for departure time, venue, mode, and route; memory-augmented reasoning with interpretable rationale traces; dynamic perception of dining congestion and walkway/bikeway crowding; ~54% Top-3 joint accuracy in time–venue prediction, outperforming MNL and approaching IRL.

Project 2 — Urban Commuting Congestion Behavioral Analysis and Simulation Platform [Team Member]

  • Processed large-scale mobile signaling: stay-point extraction, commuting route abstraction, grid-based spatiotemporal representation.
  • Built trajectory visualization & behavioral pattern dashboard to identify recurrent chains and temporal synchronization.
  • Configured simulation scenarios and interpreted outputs; co-developed platform (software copyright registered).

Class “Urban Analytical Methods” [Teaching Assistant]

  • Graded SPSS/NLOGIT statistical assignments for senior undergraduates and delivered in-class feedback summaries.

Publications

  • Luo, X., Hu, Y., Zhu, W., & Wang, D. (2025). Behavioral Demand Management for Sustainable Campus Dining: An Integrated Spatiotemporal Optimization Approach. Socio-Economic Planning Sciences. (Under Review).
  • Hu, Y., Luo, X., Liu, Y., Wei, D., & Wang, D. (2025). From Differentiation to Integration: The Spatiotemporal Turn and Strategic Exploration of Planning Paradigms. Urban Development Studies. (Accepted). [in Chinese]
  • Chen, Z., Luo, X., Wang, D., You, Z., & Zhou, X. (2024). Study on Spatio-Temporal Behavior Planning Strategies for Alleviating Morning Peak Congestion in Shanghai's Urban Rail Transit: A Case Study of Metro Line 9. Shanghai Urban Planning Review, 4, 132–139. [in Chinese]

Skills

  • Research & Modeling: Spatiotemporal behavior analysis; discrete-choice & inverse RL; agent-based simulation; LLM-based decision simulation
  • Technical: Python (pandas, geopandas, NumPy, PyTorch), LangChain, Mesa ABM, Bokeh/Plotly
  • Language: Mandarin Chinese (native), English (IELTS 6.5)

Awards

  • Outstanding Graduate of Shanghai (Undergraduate Level), 2023
  • First-Class Undergraduate Scholarship for Outstanding Students, Tongji University, 2019 & 2022
  • Second-Class Undergraduate Scholarship for Outstanding Students, Tongji University, 2020 & 2021