OxfordXML
Promoting a cross-disciplinary machine learning community to share, learn and connect
OxfordXML brings together researchers across different disciplines to share and learn about the impact of machine learning in their respective fields, such as physics, finance, social sciences, engineering, healthcare, and psychology.
“What we want is a machine that can learn from experience”
Alan Turing
Alan Turing
our mission
To provide a cross-disciplinary platform for Machine Learning researchers to share, learn and connect with other researchers across different disciplines
our community
We bring together researchers from various disciplines to build a community that promotes knowledge transfer, networking and interdisciplinary collaboration.
our activities
Termtime hybrid talks, held at Wolfson College and online, discussing different applications of Machine Learning in an informal and supportive setting.
our audience
We welcome anyone interested in learning more about Machine Learning applications across different fields. Past attendees of our events include postgraduate students, early career researchers and professors.

upcoming events

what's coming up

Please fill in this form if you're interested in joining as a student affiliate.

Stay updated on our latest events and news by joining our mailing list.

Interested in sharing your expertise? Apply to give a talk at our next seminar.

Wolfson college

30

Oct

2025
Graph AI generates mechanistic hypotheses validated across neurological systems

Speaker: Ayush Noori
Calendar Icon Time: 17:30-18:30
Location Icon Levett Room, Wolfson College & Online (Teams link).

Biography:

Ayush Noori is a Rhodes Scholar, Encode: AI for Science PhD Fellow, and D.Phil. student in Engineering Science in the Computational Health Informatics Lab at the University of Oxford. Driven by personal experiences, Ayush conducts research at the interface of artificial intelligence (AI), translational neuroscience, and precision medicine. He seeks to develop AI technologies that expand the frontier of personalized diagnosis and treatment for neurological disorders and other challenging medical conditions. His research efforts across Harvard Medical School, the Wyss Institute, and Massachusetts General Hospital have produced over 30 papers (including nine first or co-first author works) published in Cell, Nature Neuroscience, Nature Machine Intelligence, Nature Aging, npj Digital Medicine, Alzheimer’s & Dementia, and other peer-reviewed journals. Ayush received a Bachelor’s in Computer Science and Neuroscience and a concurrent Master’s in Computer Science from Harvard University.

Abstract:

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. We developed CIPHER, a graph AI model that generates mechanistic hypotheses for neurological disease. CIPHER uses a heterogeneous graph transformer contextualized to the adult human brain. CIPHER generated predictions across Parkinson’s disease (PD), bipolar disorder (BD), and Alzheimer’s disease (AD), which we validated using three independent biological systems. In PD, CIPHER linked genetic risk loci to genes essential for dopaminergic neuron survival and identified pesticides toxic to patient-derived neurons, including the insecticide Naled ranked within the top 6.75% of predictions. In silico CIPHER screens reproduced six genome-wide α-synuclein experiments, including a split-ubiquitin yeast two-hybrid system (normalized enrichment score [NES] = 2.27, FDR-adjusted p < 1E-4), an ascorbate peroxidase proximity labeling assay (NES = 2.22, FDR < 1E-4), and a high-depth targeted exome screen in 496 synucleinopathy patients (NES = 1.73, FDR < 1.9E-3). In BD, CIPHER nominated calcitriol as a candidate drug that reversed proteomic alterations in cortical organoids derived from BD patients. In AD, we conducted emulated clinical trials on cohorts involving n = 610,524 patients at Mass General Brigham, confirming that five CIPHER-predicted drugs were associated with reduced seven-year dementia risk (minimum hazard ratio = 0.63, 95% CI: 0.53–0.75, p < 1E-7). CIPHER generated and validated mechanistic hypotheses across molecular, organoid, and clinical systems, defining a path for AI-driven discovery in neurological disease.

Wolfson college

13

Nov

2025
AI for Atmospheric Systems

Speaker: Tim Reichelt
Calendar Icon Time: 17:30-18:30
Location Icon Levett Room, Wolfson College & Online (Teams link).

Biography:

I am an Encode AI Fellow in the Climate Processes group led by Prof Philip Stier. As part of the Encode fellowship, we are building a generative model for cloud structures with the primary goal is to constrain cloud climate feedbacks. Before starting the fellowship, I was conducting research on compression algorithms for climate and weather data funded by the Embed2Scale project.
I completed my PhD as part of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems here in Oxford. In my research I developed novel Bayesian inference algorithms for models defined through probabilistic programs.

Abstract:

We are building a generative model for cloud structures conditioned on environmental conditions, integrating both high-resolution satellite data and reanalysis data. By being able to generate and reconstruct cloud structures under varying environmental conditions, the model will allow us to reduce uncertainties in future climate predictions and facilitate the detection and quantification of cloud feedbacks across the satellite record. This purely data-driven approach to constraining cloud feedbacks will be complementary to existing work that relies on physics-based models.

Wolfson college

20

Nov

2025
Learning multi-scale representations of human tissue

Speaker: Konstantin Hemker
Calendar Icon Time: 17:30-18:30
Location Icon Levett Room, Wolfson College & Online (Teams link).

Biography:

I grew up in the beautiful city of Hamburg in Germany and moved to the UK after high school for my undergraduate degree at the London School of Economics. About a year into my time at LSE, I realised that I was more interested in mathematics & statistics than the economics aspects of my degree, which eventually led me to self-educate myself in Computer Science on the side. I then did a Master's in Computer Science at Imperial College London, where I focussed on various disciplines ranging from Cybersecurity to Natural Language Processing. I really enjoyed Natural Language Processing and Machine Learning more generally and started working as a Senior Data Scientist for the Boston Consulting Group for a few years. At BCG, I primarily worked on drug yield optimisation of Pharmaceutical API production as well as various other interesting modelling challenges in the pharmaceutical industry, travel & tourism industry, the public sector, and even the dating app market. Working alongside chemical engineers on pharma production sites originally piqued my interest in bioinformatics and my current research is an evolution of this (after many, many iterations).

Abstract:

We are building an automated platform that uses artificial intelligence to design and optimize nanoparticles for medical applications such as enabling brain-specific delivery. Our system combines robotic laboratory equipment with AI algorithms that learn from experimental results to rapidly discover optimal nanoparticle recipes, replacing the current time-consuming trial-and-error approach. The platform will process hundreds of different nanoparticle formulations simultaneously, using real-time measurements of particle properties to guide the AI in selecting the most promising combinations. By automating and accelerating nanoparticle development, we aim to reduce optimization time from months to days while creating better-performing particles for medical applications such as neurological diseases, potentially accelerating the development of new treatments and therapies.

Past events (2022-2024)

Events held and scheduled by us

Watch recordings of past events on our YouTube channel.

14
Oct 2025
Mastery - Why Deeper Learning is Essential in an Age of Distraction
Dr Ulrik Juul Christensen and Jessica White
  • Wolfson College
    02:00 PM - 03:00 PM
  • Wolfson College
    Wolfson College
19
Jun 2025
Machine Learning at Autotrader and MLOps Practices in Production
Ahmed Osman
  • Wolfson College
    06:00 PM - 07:00 PM
  • Wolfson College
    Wolfson College
10
Jun 2025
From Thermograms to Concepts: Using Concept Bottleneck Models to Balance Accuracy and Interpretability in Clinical AI Thermography
Mustafa Alghali
  • Wolfson College
    01:00 PM - 02:00 PM
  • Wolfson College
    Wolfson College
29
May 2025
Engineering the Digital Universe
Dr Sepideh Chakaveh
  • Wolfson College
    01:00 PM - 02:00 PM
  • Wolfson College
    Wolfson College
6
Mar 2025
Scalable and low-cost federated learning in the NHS using micro-computing
Andrew Soltan
  • Wolfson College
    06:00 PM - 07:00 PM
  • Wolfson College
    Wolfson College
25
Feb 2025
Beyond the Benchmark: Bridging the Clinical AI Implementation Gap
Dr Brad Segal
  • Wolfson College
    06:00 PM - 07:00 PM
  • Wolfson College
    Wolfson College
6
Feb 2025
Demystifying AI
Dr Sepideh Chakaveh
  • Wolfson College
    06:00 PM - 07:00 PM
  • Wolfson College
    Wolfson College
26
Nov 2024
What have Large Language Models actually learned about language(s)? Lessons from linguistics and mechanistic interpretability
Dominik Lukeš
  • Wolfson College
    05:30 PM - 06:30 PM
  • Wolfson College
    Wolfson College
7
Nov 2024
Active Learning for Billion Scale Data
Dr. Talfan Evans
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
23
Oct 2024
Bridging AI-Adaptive and Human Teaching: A Dialogic Approach to Blended, Multimodal Learning
Jessica White
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
19
Oct 2024
Linking creative clay models with AI 3D Printing and design
Margaret O'Rorke & Dr. Yi Yin
  • Wolfson College
    07:00 PM - 09:00 PM
  • Wolfson College
    Wolfson College
16
Oct 2024
Combining AI and imaging to understand cardiovascular diseases
Prof Paul Leeson
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
5
Jun 2024
THE EMOTIONAL CONTENT OF CHILDREN'S WRITING: A DATA-DRIVEN APPROACH
Rainy Dong
  • Wolfson College
    05:30 PM - 06:30 PM
  • Wolfson College
    Wolfson College
30
May 2024
DEMONS: ROBUST SELF SUPERVISED DEPTH AND MOTION NETWORKS FOR ALL-DAY IMAGES
Madhu Vankadari
  • Wolfson College
    05:30 PM - 06:30 PM
  • Wolfson College
    Wolfson College
23
May 2024
GEOMETRIC MACHINE LEARNING FOR PATIENT-SPECIFIC 3D CARDIAC ANATOMY RECONSTRUCTION
Abhirup Banerjee
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
15
May 2024
ADVANCING AI-ECG DIAGNOSIS USING DEEP LEARNING AND NEURAL ARCHITECTURE SEARCH
Lei Lu
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
1
May 2024
The Law and Economics of AI
George R Barker
  • Wolfson College
    01:00 PM - 02:00 PM
  • Wolfson College
    Wolfson College
21
Mar 2024
RESURRECTING RECURRENT NEURAL NETWORKS FOR LANGUAGE MODELLING
Razvan Pascanu
Recording of the seminar can be viewed here.
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
13
Mar 2024
Citizen Weather Data and Machine Learning to identify urban climate risk at high spatio-temporal resolution
Prof Jesus Lizana
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
7
Mar 2024
MULTI-AGENT REINFORCEMENT LEARNING
Jakob Foerster
Recording of the seminar can be viewed here.
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
6
Mar 2024
LINKING DISCIPLINES, OMICS AND AI TO IMPROVE HUMAN HEALTH
Prof James Crabbe
Recording of the seminar can be viewed here.
  • Wolfson College
    01:00 PM - 02:00 PM
  • Wolfson College
    Wolfson College
27
Feb 2024
ARTIFICIAL INTELLIGENCE FOR MATHEMATICAL DISCOVERY
Daattavya Aggarwal
Recording of the seminar can be viewed here.
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
19
Feb 2024
USER PROFILING FOR PERSONALIZATION
Dr Huizhi Liang
  • Wolfson College
    01:00 PM - 02:00 PM
  • Wolfson College
    Wolfson College
15
Feb 2024
SEEING THE UNSEEN: MACHINE LEARNING IN CARDIAC ELECTROPHYSIOLOGY
Dr Rasheda Chowdhury
  • Wolfson College
    01:00 PM - 02:00 PM
  • Wolfson College
    Wolfson College
8
Feb 2024
RISKS AND BENEFITS OF OPEN SOURCING LANGUAGE MODELS
Jakob Foerster, Christian Schroeder, Aleksandar Petrov,
Francisco Girbal, Fazl Barez, Joshua Loo
Recording of the seminar can be viewed here.
  • Wolfson College
    05:00 PM - 07:00 PM
  • Wolfson College
    Engineering Science Department, Thom Building
31
Jan 2024
Multi-Agent Security
Christian Schroeder
Recording of the seminar can be viewed here.
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
24
Jan 2024
Speech recognition from brain scans
Dulhan Jayalath
Recording of the seminar can be viewed here.
  • Wolfson College
    05:00 PM - 06:00 PM
  • Wolfson College
    Wolfson College
17
Jan 2024
MORAL UNCERTAINTY IN AUTONOMOUS AGENTS
Jázon Szabó
Recording of the seminar can be viewed here.
  • Wolfson College
    06:00 PM - 07:00 PM
  • Wolfson College
    Wolfson College
06
Dec 2023
Physics-informed generative networks
Dr Fabio Pizzati
  • Wolfson College
    01:00 PM - 02:30 PM
  • Wolfson College
    Wolfson College
30
Nov 2023
Bridging Millennia: Machine Learning's Impact on Assyriology
Ms Émilie Pagé-Perron
  • Wolfson College
    01:00 PM - 02:30 PM
  • Wolfson College
    Wolfson College
23
Nov 2023
Embeddings for Knowledge Graphs and Multimodal Representations
Dr Nitisha Jain
  • 01:00 PM - 02:30 PM
  • Wolfson College
    Wolfson College
25
Oct 2023
Some applications of AI in Mathematics and Theoretical Physics
Dr Andrei Constantin
  • 01:00 PM - 02:30 PM
  • Wolfson College
13
Jun 2023
Personalised Treatment for Mental Health
Dr Qiang Liu
  • 02:00 PM - 03:30 PM
  • Wolfson College
2
Jun 2023
INNOVATING IN MEDICAL DEVICE DEVELOPMENT
Dr Miguel Xochicale
  • 02:30 PM - 04:00 PM
  • Wolfson College
26
May 2023
Towards Safe & Robust AI for Image-Guided Diagnosis and Intervention
Dr Mobarakol Islam
  • 02:30 PM - 04:00 PM
  • Wolfson College
19
May 2023
Feature Attribution for Neural Network Explanation & Diversified Dynamic Routing for Vision Tasks
Csaba Botos & Ashkan Khakzar
  • 02:30 PM - 04:00 PM
  • Wolfson College
13
Mar 2023
Intelligence, artificial or not: conversations between developmental neuroscience and AI
Dr. Martin Frasch
Recording of the seminar can be viewed here.
More information: FraschLab.org
  • 02:30 PM - 04:00 PM
  • Wolfson College
21
Feb 2023
How Do Language Models Like ChatGPT Process Complex Words?
Mr. Valentin Hofmann
Recording of the seminar can be viewed here.
  • 02:30 PM - 04:00 PM
  • Wolfson College
9
Feb 2023
Advances in Sentiment Analysis of the Large Mass-Media Documents
Dr. Nicolay Rusnachenko
  • 02:30 PM - 04:00 PM
  • Wolfson College
19
Jan 2023
An Arms Race in Intellectual Property Protection of Deep Learning Models
Dr Youcheng Sun
  • 02:30 PM - 04:00 PM
  • Wolfson College
12
Jan 2023
GENERATING PATIENT RECORDS USING DIFFUSION MODELS
Dr Taha Ceritli
  • 02:30 PM - 04:00 PM
  • Wolfson College
12
Dec 2022
LEVERAGING MACHINE LEARNING TO IDENTIFY BLOOD CANCER TYPES
Ms Helen Theissen
  • 02:30 PM - 04:00 PM
  • Wolfson College
21
Jun 2022
Application of deep learning in fetal heart rate monitoring
Dr Daniel Asfaw
  • 03:30 PM - 05:00 PM
  • Florey Room, Wolfson College
30
jun 2022
Deep learning strategies for ultrasound in pregnancy
Dr Yi Yin
  • 1:00 PM - 2:30 PM
  • Florey Room, Wolfson College
15
jul 2022
Predicting activity patterns of regulatory elements in zebrafish using ML
Ms Andrea Rodriguez Delherbe
  • 3:00 PM - 4:30 PM
26
jul 2022
Agent-based modelling of accent retraction in Balto-Slavic
Mr Toby Hudson
  • 4:00 PM - 5:30 PM
About Us
A vision for an open, cross-disciplinary machine learning network
Founded in 2019 by Dr Stephen Suryasentana (now at University of Strathclyde) and Dr Yaling Hsiao (now at Birmingham University), OxfordXML (where XML stands for Cross-disciplinary Machine Learning) is a research cluster based in Wolfson College that aims to provide a cross-disciplinary platform for researchers across different disciplines to come and share their experience on how machine learning or artificial intelligence has impacted on their research. Furthermore, it hopes to provide an open community for researchers across different departments to connect and initiate interdisciplinary collaboration.
Committee
  • Prof Antoniya Georgieva (Cluster Head) - Research focus on Health ML/AI
  • Prof Konstantinos Kamnitsas (Governing Body Fellow Overseeing the Cluster) - Research focus on Health ML/AI
  • Dr Yi Yin (Lead Organiser) - Research focus on Health ML/AI
  • Dr George Barker (Treasurer) - Research focus on Economics, Finance, Law, Public Policy & ML/AI
Cluster Affiliates
  • Dr Csaba Botos (Member of Events Organisation Team) - Industry Affiliate
  • Hussein Ibrahim (MSc Student in Applied Digital Health) - Research focus on Health ML/AI
To join our mailing list: CLICK HERE
Please fill in this form if you're interested in joining as a student affiliate.
Contact us below if you are interested in speaking at our events