Lu Chen
Analytics | CS | GIS
chen.lu.g50@gmail.com
Based in the U.S.
Welcome to My Digital Space
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Hello, I'm Lu!
Fueled by a deep curiosity and a love for data, I dedicate my work to unraveling complex challenges through innovative analysis and programming. I love transforming complex information into fun, interactive visualizations that anyone can enjoy.
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Thank you for dropping by!
Remote Work and Energy Consumption in Office Buildings
Post-COVID-19, the WFH trend has seen a significant shift worldwide, raising questions about its regional variations and impacts on building energy consumption. This research leverages census data, building energy consumption big data and employs statistical modeling methods, including OLS and random forest, to forecast WFH adoption rates and their implications. The study also delves into how urban planning should adjust, particularly in the context of mixed-use versus single-use CBD blocks.
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Skills: Python, Random Forest, OLS, ArcGIS Pro, ArcGIS Urban
Machine Learning and Web App:
Taxi Usage and City Popularity
With the increased coverage of sensors in the cities, researchers now have access to trajectory big data. However, the majority of existing techniques either emphasize statistics or lack context-sensitive interactive visualization capabilities. To address these shortcomings, We intend to provide a dashboard or an interactive visualization tool that can give users more customized insights on the taxi trip in Manhattan by analyzing the coordinate-level temporal and spatial patterns of taxi trips in 2021 with context such as local popular time.
Big Data Activity Patterns and Real-time Energy Estimate in Tokyo
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Web-scraped and processed 1M+ GPS and 5000+ Google Maps data, analyzed and visualized activity patterns with heatmaps, animated charts, and data dashboards.
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Analyzed temporal and spatial activity patterns and extract insights about urban development.
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Built a real-time energy demand model that estimates energy consumption per hour on the building level.
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Skills: Python, ArcGIS Pro, R, Tableau
Quantifying the Social Impact of Demolishing a Historic Street for A New Metro Station
[Publication Accepted by 2022 ACSP 62nd Annual Conference]
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In September 2020, the Guangzhou city government released an opinion draft to ask for public inputs for the plan to demolish Miaoqianzhi ‘jie’, the historic old town area to build a large interchange metro station in Guangzhou, China.
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We teamed up with social activists, scholars and artists, using participatory GIS approaches to show the social networks attached to the district and its strong emotional values to local people.
ArcGIS StoryMaps: "Clearing the Air"
Power Plant Emissions, Incidence of Asthma and Social Vulnerability
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This research is to analyze the spatial relationship between fossil fuel-burning power plants, and petroleum as energy sources and the incidence of asthma in respect to other demographic characteristics.
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Skills: ArcGIS StoryMaps, ArcGIS Pro, Python, OLS
