I completed by PhD (viva pending) in Modern Statistics and Statistical Machine Learning at Imperial College London, in the EPSRC CDT in Modern Statistics and Statistical Machine Learning at Imperial and Oxford, supervised by Seth Flaxman and Yingzhen Li. My PhD was partially supported by Cervest through the StatML CDT. I am generally interested in topics in Bayesian machine learning, such as Gaussian processes, deep generative modelling, probabilistic modelling and approximate inference for high-dimensional data, with applications for climate data, images and videos.

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• November 2023: I will be joining as a Research Scientist at Fano Labs in HKSAR, China!
• Fall 2022: I visited David Duvenaud at the Vector Institute in Toronto, Canada.
• Summer 2021: I was an applied scientist intern at Amazon in Cambridge, United Kingdom, supervised by James Hensman and Xiaoyu Lu.
• Fall 2019: I started my PhD at Imperial College London, in the Modern Statistics and Statistical Machine Learning Centre of Doctoral Training (StatML)
• I obtained my MSci in Mathematics from Imperial College London, where I had the great opportunity of studying at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland as a visiting student during my 3rd year.

Feel free to reach out to me at harrisonzhu5080 [at] gmail [dot] com.