Gordon Yip
Lecturer In Physics & AI at Ariel Space Mission
Stony Stratford, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolGordon Yip is a Lecturer in Physics & AI at King's College London with eight years of experience applying machine learning to exoplanet spectroscopy, decoding atmospheric signals from distant worlds. As Principal Investigator of the Ariel Data Challenge and coordinator of Ariel’s ML working group, he leads international collaborations that have engaged 200+ participants from 69 countries and influenced ESA mission data-analysis tools. His background spans academia and industry placements—UCL postdoc and Alan Turing Institute projects—bridging rigorous astrophysics, data-intensive science (PhD) and practical ML deployments. Gordon is drawn to interdisciplinary problem solving and often translates techniques from explainable AI and time-series modelling into novel approaches for remote-sensing and mission-ready pipelines. He combines hands-on research with teaching experience for MBA/MFin students, making complex data science accessible to diverse audiences.
8 years of coding experience
3 years of employment as a software developer
University College London
Chinese, English, Chinese
Github Skills (10)
science8
machine-learning7
data-science6
imputation4
deep-learning4
imaging4
codebase2
generative2
pytorch1
transit1
Programming languages (2)
Github contributions (5)
ucl-exoplanets/DI-Project
Apr 2019 - Sep 2019
Public Repository for Direct Imaging Project using CNN
Contributions:17 commits, 14 pushes, 2 branches in 5 months
public-repositorydeep-learningimagingdirectdirect-imaging
ucl-exoplanets/Spectra_Sensitivity_analysis
Jul 2020 - Mar 2021
This is a code repo for the paper Peeking inside the Black Box: Interpreting Deep Learning Models for Exoplanet Atmospheric Retrievals
Contributions:1 release, 56 commits, 7 pushes in 7 months
atmosphericboxdeep-learningexoplanetdeep-learning-models
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