Gis Developer Computer Science

Hongpeng Fu Mobile: +(1-929******* / Email: ****@***.***.**

EDUCATION

• Northeastern University, Seattle, USA Sept 2023 - May 2025 M.S. in Computer Science (expected)

Sep 2019 - Jun 2022

• Peking University, Beijing, China

M.S. in Geography in Landscape Architecture

B.E. in Urban and Rural Planning Sep 2014 - Jun 2019 SKILLS AND SELECTED COURSES

Programming Languages Java, Python, SQL, C++ R, JavaScript, HTML/CSS Framework & Tools SpringBoot, SpringCloud, Flask, Node.js,React, MySQL, MongoDB, Maven, Jenkins, Docker, Postman, PyCharm

Data analysis SPSS, ArcGIS, Microsoft Word, Excel, QGIS, Stata,AutoCAD Selected Courses Data Structures Algorithms, GIS, Landscape Planning and Design; Urban Design PROFESSIONAL EXPERIENCE

• Geely - GIS Developer, Map Technology Department Jul 2022 - Dec 2022

– Developed and optimized a GIS-based Estimated Time of Arrival (ETA) service for dynamic route planning considering geographical, traffic, weather, and historical data, improving accuracy from 86.2% to 90.5%.

– Leveraged spatial databases and GIS libraries in Python for efficient geospatial computations and spatial data manipulation, contributing to the enhanced performance of the ETA engine.

– Utilized Redis for caching offline and real-time ETA data, and Hive for storing real-time data, reducing the data cache miss from 1500/month to 245/month and enhancing data retrieval accuracy by 15%.

– Implemented the ETA Data Annotation service using QGIS, facilitating information querying, geospatial metric calculation, and comparative analysis with competitors, saving over 3500 engineering hours.

• United Nations - GIS Developer Intern May 2022 - May 2022

– Participated in the Assessment and governance of ecological security in water conservation areas.

– Participated in analyzing the landuse data and its changes over time using ArcGIS.

– Built 10 scenarios analysis for integrating agricultural and urban development of different levels.

– Lead the simulation of water quality based on SWAT model in ArcGIS.

• Peking Univrsity - GIS research assistant - Peking Univ. Oct 2021 - Jun 2022

– Developed an AI-based park user flow system utilizing ArcGIS based on phone signal data and landuse data, saving over $10,000 annually.

– Participated in the automatic model employing Python, and GIS to predict park visitors flow map, and its influencing factors, improved the accrucy from by 77.3% to 90.5%.

– Leveraged GIS tools alongside React, Echarts to develop interactive charts and maps for data visualization, and utilized Redux for application state management.

• Turenscape - GIS Developer Intern, Smart City Department May 2020 - Sept 2020

– Integrated GIS and machine learning to predict and visualize public services based on social media data, achieving 81.7% accuracy.

– Participated in the automatic rating model employing Python, and GIS data to predict park visitors’ assessment and make the sentiment map

– Developed the backend using Flask, creating RESTful APIs to handle spatial data requests and responses.

– Implemented geospatial queries and data management in a MongoDB database, designing the schema and optimizing for efficient spatial data retrieval.

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