Zhongtian Sun holds a Ph.D. in Computer Science from Durham University, where he specialised in enhancing the expressive power of computational models through knowledge representation learning. Prior to his doctoral studies, he obtained Bachelor's and Master's degrees in Finance.

He is affiliated with the Alan Turing Institute Knowledge Graph Interest Group and has showcased his proficiency in machine learning and human-computer interaction through a UKRI research assistant role focused on chatbot development.

Currently, Zhongtian is a Research Associate, conducting research on disease transmission dynamics by leveraging Large Language Models (LLMs) and Knowledge Graphs (KGs).

Zhongtian's primary research interests lie in the field of knowledge representation learning (KRL) and its applications across a wide range of domains, such as natural language processing, healthcare, finance, molecular science, and networks. He is dedicated to advancing the representation capabilities of deep learning models.

I studied at Trinity College Dublin and the University of Edinburgh, and did my PhD on the Oxford-Warwick Statistics Programme. I was then a postdoc at the University of Oxford, and then a Lecturer in Statistics at the University of Glasgow.

My research lies at the intersection of probability, statistics and computation, applied to problems in genetics. I am interested in what we can learn about evolution by analysing sequenced genomes: for instance, through reconstructing the shared genetic history of a sample of individuals, we can gain insights into past demography, understand how genetic variation arises and how it is shaped by natural selection to produce the patterns we observe in the data. 

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