Ganmin Yin

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Ph.D. Candidate,
Institute of Remote Sensing & GIS,
Peking University,
No. 5 Yiheyuan Road,
Beijing, China
E-mail: yinganmin6837@163.com

About Me

I am Ganmin Yin, currently a Ph.D. candidate (2020-2025, expected) majoring in GIScience at Peking University. I am also a research assistant in the Geocomputation Group of the Spatio-Temporal Social Sensing Lab (S3-Lab), supervised by Prof. Zhou Huang and Prof. Yu Liu. Before that, I received my B.S. Degree on GIScience at Peking University in 2020.

My research interests focus on urban analytics with geospatial big data and deep learning techniques, including sustainability issues like transportation and urbanization. My research goal is to introduce state-of-the-art theories and models to better understand the human-environment relationship.

Besides, I am also very interested in Hiking, Traveling, and Literature :).

Note: I am looking for a postdoc position starting in 2025, fall. Feel free to contact me!

My CV can be downloaded from here.

News

Education

Ph.D. Candidate, Cartography and GIScience, Peking University, 2020 - Present

  • GPA: 3.60 / 4.0, Top 30%

  • Supervisor: Prof. Zhou Huang & Prof. Yu Liu

B.S., GIScience, Peking University, 2016 - 2020

  • GPA: 3.53 / 4.0, Top 30%

  • Supervisor: Prof. Zhou Huang

Selected Awards

Rising Star Award, College GIS Forum of China, 2023

  • No. 1, About 10 winners per year for outstanding Chinese GIS students

Presidential Scholarship, Peking University, 2022, 2023 (Two years)

  • Top 5%, Highest honorary scholarship for graduate students of Peking University

Merit Student, Peking University, 2022

  • Top 20%, Annual award of Peking University

Selected Publications

*Corresponding author, #Equal contribution

  1. Yin, G., Huang, Z.*, Fu, C., Ren, S., Bao, Y., & Ma, X. (2024). Examining active travel behavior through explainable machine learning: Insights from Beijing, China. Transportation Research Part D: Transport and Environment, 127, 104038. (IF = 7.6, T1 Top) [pdf] [doi]

  2. Yin, G., Huang, Z.*, Yang, L., Ben-Elia, E., Xu, L., Scheuer, B., & Liu, Y. (2023). How to quantify the travel ratio of urban public transport at a high spatial resolution? A novel computational framework with geospatial big data. International Journal of Applied Earth Observation and Geoinformation, 118, 103245. (IF = 7.5, T1 Top) [pdf] [doi]

  3. Yin, G., Huang, Z.*, Bao, Y., Wang, H., Li, L., Ma, X., & Zhang, Y. (2023). ConvGCN-RF: A hybrid learning model for commuting flow prediction considering geographical semantics and neighborhood effects. GeoInformatica, 27(2), 137-157. (IF = 2.0, CCF-B) [pdf] [doi]

  4. Huang, Z., Yin, G., Peng, X.*, Zhou, X., & Dong, Q. (2023). Quantifying the environmental characteristics influencing the attractiveness of commercial agglomerations with big geo-data. Environment and Planning B: Urban Analytics and City Science, 50(9): 2470-2490. (IF = 3.5, ESI Highly Cited Paper) [pdf] [doi]

Full list of publications in Google Scholar.

Presentations

  1. Yin, G. "Exploring the influencing factors of urban commercial agglomeration attractiveness based on mobile signaling big data". The 18th China Annual Conference on GIS Theory and Method (Guilin, China, 2023). (Oral) [agenda]

  2. Yin, G. "Understanding public transport supply and demand from the perspective of public transport travel ratio in a fine spatial scale". The 28th International Conference on Geoinformatics (Nanchang, China, 2021). (Oral) [agenda]

Services

Peer Reviewer

  • Computers, Environment and Urban Systems, 2024

  • Cities, 2024

  • International Journal of Applied Earth Observation and Geoinformation, 2024

  • Urban Climate, 2023

  • Transactions in GIS, 2021

Session Chair

  • Session 2 - Geospatial Analysis, The 2021 International Graduate Workshop on GeoInformatics (IGWG 2021)