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Mingqian Wang
Mingqian Wang
MSc Geographical Information Science student, the University of Manchester
Mingqian‘s professional bio / interests
My obsession with built environments started when I was young, and landscapes became a gateway to help me to understand better the environment we live. My academic explorations at the undergraduate and postgraduate levels allowed me to realise that there are three sub-areas of the landscape discipline - planning, design, and management, which align with the taxonomy of the MA Landscape Architecture course I completed in Sheffield a year and a half ago. I am particularly interested in the planning aspect as it is rational, strategic, and comprehensive. So I mainly focused on the landscape planning field during my postgraduate studies at Sheffield, while Geographical Information System (GIS) was one of the most crucial approaches towards many of my coursework and internship projects, as it stores, manages, displays, analyses, and explains different kinds of spatial and land information in a broad spatial scale, and helped me to conduct the spatial analysis during many of my planning-based projects. After studying landscapes for six years, including completing a postgraduate degree programme with in-depth GIS application, I found that the field related to spatial data science and analysis is much more intriguing to me than the traditional landscape discipline. In the past year's work life, I engaged in several research projects on China's urban planning & construction market, which involved many regional market distribution laws and decisions that could be revealed through GIS. Besides, I have worked with several spatial planning projects focusing on GIS functions to store, manage, display, and explain land information. Aiming to develop the ability to solve more diverse and complex problems, both academically and practically, I will soon do a second master's degree in GIS at the University of Manchester. Through the upcoming experience at Manchester, I will mainly focus on the improvement of my numerate and quantitative skills, including data modelling, machine learning & statistical analysis, programmatic computation & automatic data processing, and database technologies. Whether it's spatial data science or the broader data science applications in different fields, that will be my focus.
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Joined Guild
25 June, 2023