CV

Education

• Ph.D in Geography, Geographic Information Science (GIS), University of California, Santa Barbara, 2025 (expected)
• M.A. in Mathematical Statistics, University of California, Santa Barbara, 2024 (expected)
• M.A. in Geography, Geographic Information Science (GIS), University of California, Santa Barbara, 2022
• B.S. in Geographic Information Science (GIS), Wuhan University, 2020

Professional experience

University of California, Santa Barbara
Graduate Student Researcher

• Developed and implemented various movement analysis methodologies, including trajectory interpolation and route choice analysis, using machine/deep learning techniques, such as gated recurrent network (GRU), long short-term memory (LSTM), and generative adversarial network (GAN)
• Performed statistical analysis on movement data and associated movement with the environment to assess the environmental impact using Python
• Led research projects and actively collaborated with coworkers, mentored undergraduate students in research
• Authored 2 research papers so far, both as the 1st author
• Delivered research presentations at the Annual Meeting of American Association of Geographers (AAG), ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, and UCSB Geography Colloquium

University of California, Santa Barbara
Teaching Assistant & Teaching Associate (Instructor)

• Delivered summer course GEOG176A: Introduction to Geographic Information Systems and Science as sole instructor. Designed and presented 105-minute lectures, 4 days per week for 6 weeks, to teach GIS fundamentals and applications
• Actively engaged students for feedback in and out of class to constantly improve the course
• Led discussion and lab sections in different geography courses, including Introduction to GIS, Technical GIS, GIS Applications, and Remote Sensing of the Environment
• Supervised and guided undergraduate students to complete GIS projects, including designing a research question, collecting data, implementing analysis, and finalizing a report

Wuhan University
Research Assistant

• Initiated, designed, and executed 2 independent projects on movement trajectory data, using machine/deep learning models, such as decision tree and long short-term memory (LSTM), both published as journal papers
• Collaborated with classmates in a course project, which was published as a conference paper
• Authored 3 research papers, 2 of them as the 1st author, 1 as the 2nd author
• Attended the Annual Meeting of Geographical Society of China as a member

Skills

• Computer Skills: Proficiency in Python (machine/deep learning using PyTorch/TensorFlow, Scikit-Learn/SciPy for scientific computing, and other libraries), and intermediate proficiency in R, C++, MATLAB. Proficiency in ArcGIS Pro and QGIS for spatial analytics
• Involvement: Reviewer of peer-reviewed journals: Scientific Reports, International Journal of Geographical Information Science, Geographical Analysis, Journal of Spatial Information Science
• Languages: Professional proficiency in English, Native in Chinese

Publications

A Generative Trajectory Interpolation Method for Imputing Gaps in Wildlife Movement Data

Wan, Z. & Dodge, S. (2023). A Generative Trajectory Interpolation Method for Imputing Gaps in Wildlife Movement Data. In 1st ACM SIGSPATIAL International Workshop on AI-driven Spatio-temporal Data Analysis for Wildlife Conservation (GeoWildLife ’23), November 13, 2023, Hamburg, Germany. ACM, New York, NY, USA, 8 pages.

Leveraging similarity analysis to understand variability in movement behavior

Wan, Z., Dodge, S., & Bohrer, G. (2023). Leveraging similarity analysis to understand variability in movement behavior. Transactions in GIS, 27(5), 1441-1466.

A Long Short-Term Memory-Based Approach for Detecting Turns and Generating Road Intersections from Vehicle Trajectories

Wan, Z., Li, L., Yu, H., Yang, M. (2022). A Long Short-Term Memory-Based Approach for Detecting Turns and Generating Road Intersections from Vehicle Trajectories. Sensors, 22(18):6997.

Decision tree model for extracting road intersection feature from vehicle trajectory data

Wan, Z., Li, L., Yang, M., Zhou, X. (2019). Decision tree model for extracting road intersection feature from vehicle trajectory data. Acta Geodaetica et Cartographica Sinica, 48(11): 1391-1403.

Reconstructing Individual Activity Trajectories by Hidden Semi-Markov Model

Han, Z., Wan, Z., Guo, W., & Ren, C. (2018). Reconstructing Individual Activity Trajectories by Hidden Semi-Markov Model. In 2018 26th International Conference on Geoinformatics (pp. 1-6). IEEE.

Talks

A Generative Trajectory Interpolation Method for Imputing Gaps in Wildlife Movement Data

November 13, 2023

Talk at 1st ACM SIGSPATIAL International Workshop on AI-driven Spatio-temporal Data Analysis for Wildlife Conservation (GeoWildLife ’23), Hamburg, Germany

Trajectory interpolation: prediction of missing points in movement data using long short-term memory

March 23, 2023

Talk at American Association of Geographers (AAG) 2023, Denver, CO

Inferring environmental drivers of animal migration path choice

February 27, 2022

Talk at American Association of Geographers (AAG) 2022, New York, NY (Online)

Teaching

GEOG 176A: Introduction to Geographic Information Systems and Science

Teaching Assistant

Service

• 2023-present: Reviewer of International Journal of Geographical Information Science
• 2022-present: Reviewer of Journal of Spatial Information Science
• 2022-present: Reviewer of Scientific Reports
• 2021-present: Reviewer of Geographical Analysis
• 2017-2018: Vice Minister of WHU Youth Volunteer Association
• 2016-2017: Member of WHU Youth Volunteer Association

Awards & Honors

• 2022 March: SAM Student Travel Award, Spatial Analytics and Modeling (SAM) Specialty Group, AAG Annual Meeting
• 2020 June: Outstanding Bachelor Thesis, Wuhan University
• 2018 October: Elite Student, Wuhan University
• 2018 October: Second-class Scholarship, Wuhan University