Hi, I'm Euan.
I am a 17yo A level student currently studying Maths, Further Maths, Physics, Biology, and Computer Science,
with a strong focus on programming and computational thinking. My interests in academia are centred heavily in Natural Science
, particularly genetics and astrophysics - which often serve as inspiration for my independent projects.
I have lots of experience with a wide range of different programming languages, my most used being Python (8 yrs), followed by JavaScript (3 yrs) and Rust (2 yrs).
I currently attend Wymondham College, a state-boarding sixth-form school, located to the west of Norwich. It is here that I study (Further) Maths, Biology, Physics, and Computer Science.
Graduated with 10 GCSEs at a 7 or above, and a language qualification in German.
Alongside formal education, I’ve pursued a wide range of extracurricular academic and programming activities.
I scored highly in the BEBRAS Computational Thinking Challenge and placed first in the OAT Codes national competition, earning £200 worth of tech prizes.
In Year 10, I independently worked through the full set of University of Manchester Computer Science lectures.
More recently I was selected for a work experience placement at BT in 2025.
One of my proudest achievements was having my code run on the International Space Station — a solar storm predictor project that returned real telemetry data from orbit.
Repository: cchan083/AstroPi
The primary objective of the AstroPi project is to estimate the velocity of the International Space Station (ISS) using a computer vision approach. This involves analyzing sequential images captured from space and applying image feature detection algorithms (notably SIFT) to track visual changes that correlate with motion.
The secondary goal is to identify and classify solar activity using magnetometer data from the Sense HAT onboard the ISS. This involved analyzing solar wind dataset features and building a machine learning model to classify irregular solar activity events.
SIFT (Scale-Invariant Feature Transform) instead of ORB for better image feature detection.
Converted images to greyscale to enhance accuracy in feature comparison.
Referenced and modified techniques from the official AstroPi guide: ISS Speed Estimation.
Developed by me and Christopher Chan as part of the AstroPi Mission Space Lab project.
Repository: CURRENTLY PRIVATE
The primary objective of this project is to develop and implement a custom genetic circuit file format designed to describe synthetic biological systems in a modular and computationally interpretable way. The format captures genetic elements such as promoters, genes, operators, and logic gates, allowing for layered abstraction and reuse across multiple designs.
The secondary goal is to integrate this file format with a stochastic simulation engine capable of modeling the temporal dynamics of genetic circuits. This simulator uses a modified Gillespie algorithm to simulate biochemical reactions and stochastic gene expression, directly ingesting the custom file structure as input.
Developed by me as part of my Computer Science NEA
Reach out via email or find me on social media.