Yik Ching, Tsui

I love having fun applying my programming and analytical skills, and I take pride in my innovative and creative work. As a lifelong learner, I view challenges as opportunities to grow.

Employment

GIS Programmer

• Technologies used: Rust, Typescript, React, Python, C#, SQL, Git, ArcGIS Pro, ArcGIS Enterprise, ArcGIS Online, ArcGIS Experience Bulider, ArcGIS Dashboard, QGIS.

Frontend web and software developer

• Rewrote legacy website with statically typed languages to increase maintainability (it was unmaintainable for years)
• Sped up site performance by 37% (total load time), 36.7% (time to interactive), 40% (onload time), 56% (DOM interactive time)
• Increased flexibility of codebase suitable for non-technical staff, enabling them to finish a year-long backlog of tasks
• Teamwork: Worked in a team of two and collaborated with the administrative, sales, and calibration departments to design the maintenance system.
• Technologies used: Haskell, Rust, Typescript, Python, Makefile, Git, GitHub Actions

Education

• First Class Honours, Bachelors of Arts (Hons) in Geography (Spatial Data Science Pathway)
• Visual communication: all coursework below used maps, charts, and statistics to communicate analysis and evaluation.
• Undergraduate Thesis: Evaluating the algorithms used in site suitability analysis: an open source implementation for photovoltaic solar farms in Arizona (achieved 74%, officially published in the Student Handbook)
• Creativity and innovation: evaluated the impact of different buffers by overlaying contour lines on a map.
• I evaluated the impact of standardization functions by overlaying the standardization functions on a histogram of the actual dataset.
• Attention to detail: accounted for edge effects due to study area boundary
• Directed Readings project: Railway network design and transfers in Greater Tokyo and London (achieved 70%)
• I researched origin-destination data myself, and used QGIS to visualize railway coverage and transport accessibility.
• Applications of Spatial Data Science coursework: Comparative public bus transportation network and accessibility analysis: a case study for Greater London and Hong Kong (achieved 82%)
• Self learning: I went the extra mile and used methods beyond what was taught in the classroom, and applied the latest advances in academia
• Creativity: I used a novel scatterplot quadrant method to segmentate the cities into high and low bus stop accessibility relative to the local population

Personal projects

• Data visualization: cumulative accessibility of rail transport, categorizing population by accessibility type to illustrate the urban form of cities
• Resilience and tenacity: Original analysis was on a random sample as the dataset was too large to fit in memory. I tackled the problem again by using a more efficient data structure and streaming algorithm, calculating the entire dataset in seconds.

• Visualizations of proportional representation methods, with an interactive webapp hosted at akazukin5151.github.io/approportionment
• Rigorously unit tested with real ballot data from Scottish Council elections
• Applied to real world elections including Finland 2023, Estonia 2023, Sweden 2022, and Germany 2021
• Fine tuned algorithms and data structures for high performance, including perfect hash functions and bitarrays.

• Temporal data visualization: Train schedule diagrams for Japanese railways, using pandas and matplotlib
• Used by a PhD research on intercity and interregional train travel in Japan

• Data modelling and statistical probability: Models the spatial distribution of passengers inside a train along its journey, using plotters

• Terminal browser with images for an online art community

• Interactive password manager for the terminal, written in a purely functional language