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 Analyst and Software Developer
- Git
- Rust
- Python
- HTML, CSS, Typescript
- React
- Java
- C#
- SQL
- ArcGIS Pro
- ArcGIS Enterprise
- ArcGIS Online
- ArcGIS Experience Builder
- ArcGIS Dashboard
- QGIS
Frontend web and software developer
C & K Instruments (HK) Limited, remote
May 2022 — September 2022
- 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
King's College London
London, UK
September 2019 — July 2022
- 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.
Rust, Typescript, HTML, CSS, Python, Dhall
- 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