# Andrey Kormilitzin

is a team lead and a senior researcher in machine learning and clinical artificial intelligence.

# Qiang Liu

is a postdoctoral researcher at the Department of Psychiatry, University of Oxford. Qiang's expertise is in computer vision, data engineering and deep learning for personalised medicine. He works on the development of neural network frameworks for fluorescent microscopy and cellular phenotyping and personalised recommendations of medications in depression and dementia. Qiang holds PhD in Computer Science from the University of Essex.

# Doctoral students:

# Niall Taylor

is a DPhil students in Health Data Science at the Big Data Institute and the Department of Psychiatry, University of Oxford. Niall has a background in experimental psychology, with a Bachelors from the University of Plymouth, followed by a Masters by Research at the University of Bristol. Niall's overarching interests focus on the application and uptake of machine and deep learning in the realm of mental health, with the aid of big data and wearable devices.

Niall works on Natural Language Processing, prompt ingineering and explainable methods for clinical decision support with free-text data from UK-CRIS and MIMIC. He is developing method to generate abstractive salient reasons derived from texts to underpin the decisions made by models.

# Master's students (2022-2023)

# Vivian Kessler

# Jay Milligan

# Ying Chen

# Louis Clarke

**Alumni**

**Alumni**

# Yi Zhang

is a research assistant at the Department of Psychiatry, University of Oxford. Yi works on high-content image recognition, geometric deep learning (GDL) and graph neural networks (GNN). His particular interest is in the application of GDL and GNN to de novo drug discovery and phenotypic screening. Yi recieved BSc (University of Manchester) and MSc (University if Oxford) both in Mathematics . His dissertation was on matrix perturbation theory, numerical linear algebra and the theory of random walks.

Yi Zhang has been a research assistant in machine learning for Natural Language Processing and has been leading on the developing of a Large Langauge Modelling approach to long-text classification tasks using electronic health records in secondary mental health as part of the CHRONOSIG project.

Now is a PhD student in machine learning and artificial intelligence at the Technische Universiteit Delft.

# Master's students (2021-2022)

# Tianyang (Derek) Li

is currently a MMath Mathematics student at the Mathematical Institute, University of Oxford. Tianyang‘s research interests lie within natural language processing and statistical analysis and works on reducing the self-attention complexity in Transformers architectures by using low-rank tensor approximations. The aim of Tianyang‘s work is to allow transformers-based models, in particular for NLP tasks, to capture long range dependencies in electronic health records to support clinical decision making.

Tianyang has successfully completed a dissertation titled: "*Kerformer: Linear Transformer with Kernelised Self-Attention*"

# Jacob Barker

is currently a MMath Mathematics student at the Mathematical Institute, University of Oxford. Jacob's background is in machine learning and data science, with a particular interest in a hospital the scalability and accuracy of machine learning systems. Jacob's research is dedicated to modelling the path of a patient over the course of a treatment period. In particular I am excited about using neural controlled differential equations to try and understand the dynamics of a care plan over time.

Jacob Barker has completed with distinction a dissertation titled: "*On the Applications of Neural Differential Equations For Clinical Decision Support*"

Now is a Quantitative Researcher at Aspect Capital

# Haobo Yuan

is currently a MMath Mathematics student at the Mathematical Institute, University of Oxford. Haobo has a background in statistics and statistical machine learning. Haobo's research is dedicated to learning models for actionable recourse in healthcare. He uses methods of adversarial neural network learning and optimisation to derive counterfactual explanations for decision support systems.

Haobo Yuan has successfully completed a dissertation titled: "*Learning models for actionable recourse and optimization for machine learning** **augmented decision making*"

# Ziming Gao

is currently a MMath Mathematics student at the Mathematical Institute, University of Oxford. Ziming has a background in computational statistics, machine learning and Natural Language Processing. Ziming’s research is dedicated to a new approach for zero-short learning with very large pre-trained language models – the Prompt Learning (PL) paradigm. He explores whether PL can be adapted to downstream analytical tasks to support clinical decision making, derive explanations and how to optimise the learning process.

Ziming Gao has successfully completed a dissertation titled "*Clinical-Prompt: a systematic analysis of prompt learning to inform clinical decision making*"

Now is pursuing a MSc in Financial Mathematics at the University of Oxford.

# Master's students (2020-2021)

# Yuchen Lu

studied towards Part C dissertation at the Mathematical Institute, University of Oxford. Yuchen's research is focused on statistical analysis and machine learning modelling for drug discovery for Alzhemer's disease. He analyses glial fluorecent cell images generated using the Cell Painting method with the aim to understand the mechanism of action of candidate drug compunds with higher accuracy than existing approaches.

Yuchen Lu has successfully completed a dissertation titled "*Image-based profiling and machine learning for Alzheimer's disease drug discovery using human glial cells*"

Now at Squarepoint Capital.

# Piotr Kalinowski

studied towards Part C dissertation at the Mathematical Institute, University of Oxford. Piotr's research focused on the development of deep learning convolutional models for analysing fluorescent microscopy images and the development of fast screening tool for morphological changes of cells treated with various compounds. Mr Kalinowski has been a machine learning researcher at the University of Oxford (2021-2022) leading on the development of deep learning tools for high-content image analysis and to characterise cell health phenotypes and pattern recognition in mechanism of action of candidate drug for Alzheimer’s disease.

Piotr Kalinowski has successfully completed a dissertation titled: "*Machine learning methods for cell feature extraction in drug discovery for Alzheimer's disease*"

Now is a PhD student in artificial intelligence at the University of Heidelberg.

# Wooseok Jung

studied towards Part C dissertation at the Mathematical Institute, University of Oxford. Wooseok's research is focused on the interface between deep learning methods for fluorecent microscopy image segmentation and topological data analysis. He developed a novel approach to derive persistence silhouettes and landscape signatures to quantify the geometry of cells' nucleui for downstream computational tasks.

Wooseok Jung has successfully completed a dissertation titled: "*From Augmented Microscopy to Topological Transformer: New Breakthrough in Deep Learning-based Cell Image Analysis in Alzheimer's Research*"

Now is a research scientist at Vuno

# Alexander Davi

studied towards the MSc Mathematical Sciences dissertation at the Mathematical Institute, University of Oxford. Alec's research is focused on artificial cell painting, whereas he develops deep learning methods to translate fluorescent information from stained images to non-stained ones. His work can speed up the statistical analyses of image-derived features and help biologists to study the morphological changes in cells by using bright-field images.

Alexander Davi has successfully completed a dissertation titled: "*Artificial Cell Pai**nting*"

Now is a Owkin working on AI for drug discovery.

# Pawel Paradysz

studied towards Part C dissertation at the Mathematical Institute, University of Oxford. Pawel's research is focused on developing new methods for generating high-resolution fluorecent images through adversarial training.

2019 Adam (Xinyu) Yang,

*"**Deep learning for drug discovery in Alzheimer’s disease"*(Mathematical Institute). Now a PhD student at Bristol Computational Neuroscience Unit. University of Bristol, UK2018 Rattana Pukdee,

*"The signature-based pricing models"*(Mathematical Institute). Now a PhD student in the Machine Learning Department at Carnegie Mellon University, USA.2018 William Stone,

*"Deep learning for estimation of neuronal health"*(Mathematical Institute). Now a Geophysicist at Compagnie Générale de Géophysique (CGG).2018 Maximilian Hofer,

*"Few-shot Learning for Named Entity Recognition in Medical Text"*, (Computer Science). Now a PhD student at the Swiss Federal Institute of Technology in Lausanne