Hi I am Gordon (or you may know me as Kai/Kai Hou from my publications) 
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So I gathered if you bump into this page, you probably want to learn about my background. I am a PhD student pursuing a CDT in Data Intensive Science at UCL. I am also a member of CSED, ExoAI and the Ariel Consortium. My research focuses on applying Machine Learning and Deep Learning techniques to help us better understand exoplanets (aka planets outside our solar system), and in particular their atmospheres. You can find my past and current works in Projects.
Python
90%
Tensorflow
80%
Keras
80%
SQL
80%
Exoplanet-related theory
90%
Bayesian Analysis
80%
Deep learning models
80%
My PhD research focuses on applying machine learning techniques within the context of exoplanet characterisation. I pioneered the use of Explainable AI techniques in exoplanetary science and showed that deep learning models can learn molecular features without any prior physical knowledge.
I was responsible to a build a prototype deep learning based model to predict the onset of traffic incidents. I have also written a dedicated data pipeline to extract, clean and transform raw data from live traffic record into data product ready for machine learning applications or data visualisations.
My 6 months placement at ATI was split between two projects. 1. "Learning Machine Project" The primary focus of the project is to design and build a dedicated framework to update, train and interpret machine learning models for healthcare and justice application. 2. "DECOVID-19". The second half of my placement is spent to develop a dedicated python package to produce descriptive statistics for incoming COVID-19 data.
I obtained a Master's degree in Astrophysics with First Class Honour at UCL. I won the Best Performance in Astrophysics during my 3rd and 4th Year.