Biography
Hi everyone! I am a Ph.D. candidate under the supervision of Dr. Andrew Crooks in the Department of Geography at the University at Buffalo. My research focuses on critically understanding urban space by leveraging (geo)computational techniques and data informatics. I am interested in Space and Place, Urban Perception, Agent-Based Modeling, Spatial Analysis and Visualization, Social Media and Big Data. I received a M.S. in Physics from National University of Singapore and B.S. in Physics from Minjiang University of China. Prior to starting my PhD, I worked as a Research Associate in the Singapore University of Technology and Design (SUTD) and as a Research Engineer in the Singapore-MIT Alliance for Research and Technology Centre (SMART).
Download my CV.
- GIScience
- Space and Place
- Urban Perception
- Agent-Based Modeling
- Social Media and Big Data
- Spatial Analysis & Visualization
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PhD in Geography, 2021 - present
University at Buffalo
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MSc in Physics, 2015
National University of Singapore
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BSc in Physics, 2014
Minjiang University of China
Research
A comparison between online social media discussions and vaccination rates: A tale of four vaccines
The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of public discussion. In this discussion, various social media platforms have a key role. While this has long been recognized, the way by which the public assigns attention to such topics remains largely unknown.
Categorizing urban space based on visitor density and diversity: A view through social media data
Analyses of urban spaces have often stressed the importance of both the density and diversity of the people they attract. However, the diversity of people is a challenging concept to operationalize within the context of urban spaces, which is why many evaluations of urban space have relied primarily on density-based measures.
Analyzing the vaccination debate in social media data Pre- and Post-COVID-19 pandemic
The COVID-19 virus has caused and continues to cause unprecedented impacts on the life trajectories of millions of people globally. Recently, to combat the transmission of the virus, vaccination campaigns around the world have become prevalent.
Delineating a ‘15-Minute City’: An Agent-based Modeling Approach to Estimate the Size of Local Communities
With progressively increased people living in cities, and lately the global COVID-19 outbreak, human mobility within cities has changed. Coinciding with this change, is the recent uptake of the ‘15-Minute City’ idea in urban planning around the world.
Understanding urban neighbourhoods by measuring distance, diversity, and direction of flows in Singapore
Traditional approaches to human mobility analysis in Geography often rely on census or survey data that is resource-intensive to collect and often has a limited spatio-temporal scope. The advent of new technologies (e.
Homelocator
Identifying meaningful locations, such as home or work, from human mobility data has become an increasingly common prerequisite for geographic research. Although location-based services (LBS) and other mobile technology have rapidly grown in recent years, it can be challenging to infer meaningful places from such data, which – compared to conventional datasets – can be devoid of context.
New Urban Kampung
The ‘New Urban Kampung’ is a S$6-million interdisciplinary research program with team members from architecture, humanities, and engineering pillars. This research aims to develop new strategies and platforms to enable public housing estates to become vibrant collaborative communities, replicating the spirit of the old ‘kampung’ (village) with their strong community care and resilience.
Publications
Teaching
Introduction to the use of high-speed digital computers in geographic research. Topics include advanced programming, introductory machine architecture, large file handling and data base management systems, computer graphics and digitizing. Students are expected to complete a major applications programming project as part of the course requirement. LEC/LAB
Responsibility:
Work Experience
Key Responsibilities:
- Analyzed and visualized large scale survey data and social media data
- Conducted Q method analysis to help identifying QoL indicators
- Conducted segmentation analysis with machine learning techniques
- Designed and developed interactive visualization dashboard for client-side
- Applied network analysis techniques to identify social networks and spatial features
- Developed cloud computing infrastructure to store and index large data sets
- Developed an R package to adopt different algorithms for inferring meaningful locations
- Performed data collection through web crawling and interfacing with APIs
Key Responsibilities:
- Prepared reagents for calibration, carried out laboratory data collection & analysis
- Investigated matrix effects on fluorescence properties & explored methods for algae classification
- Validated & qualified optical sensor in measuring standards samples & calibrated spectrometer wavelength
- Scheduled and trained 1 research assistant & 5 interns
- Organised lab test solutions, compounds and accurately ordered & inventoried lab chemicals and supplies
Technical Skills
Proficient in tidyverse, ggplot, spatial libraries, interactive visualization dashboard, package development, and project management
Basic knowledge of NumPy, and pandas
Familiar with regression, dimension reduction, clustering and classification
Good at sentiment analysis, tf-idf statistic, n-grams, and topic-modelling
Familiar with spatial autocorrelation, spatial regression modeling and network analysis; Proficient in descriptive and inferential statistics
ArcGIS Pro, Tableau, Elasticserach, Bash, Git, Markdown, Jupyter Notebooks, Anaconda
Certificates
Contact
- qchen47@buffalo.edu
- 105 Wilkeson Quad, Ellicott Complex, North Campus, Buffalo, New York 14261
- Monday - Friday 09:00 to 17:00
- Book an appointment