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
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
Lunchtime and predinner talks during term time and an annual conference to inform on the latest, cutting-edge machine learning research in different disciplines.
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 event
what's coming up

Myocardial infarction (MI) results in the loss of millions of cardiomyocytes, and the formation of a non-contractile scar, ultimately leading to heart failure. Despite more than a decade of research on cardiac regeneration, clinical study results using standard stem cell approaches have been disappointing and currently the only cure is heart transplantation. Our group has previously demonstrated that the epicardium can be activated during MI, through a process called Epithelial-to-Mesenchymal Transition (EMT). More specifically, epicardium-derived cells undergo morphological changes, migrate, and can replenish lost cardiac tissue and ultimately preserve heart function. This provided proof-of-principle for a novel resident cell-based therapeutic approach for heart attack treatment. The aim of this project is to identify novel small molecules that can activate the resident epicardial cells in the human heart, by promoting EMT, and regenerate the infarcted heart. To achieve this, we are conducting phenotypic small molecule screens, assessing the EMT characteristics of human stem cell-derived epicardial cells, miniaturised in a 384 well-plate format. To evaluate the results of the drug screens we developed an image analysis protocol utilising machine learning, based on software training with CellProfiler, which allows us to automatically calculate the percentage of EMT for each experimental image. We are currently performing a Pilot screen, as the first stage of a drug discovery programme.

FREE PIZZA WILL BE SERVED AFTER THE TALK
list of events
Events held and scheduled by us
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oct 2020
  • 10:30 AM - 05:30 PM
  • To be confirmed
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may 2020
  • 05:30 PM - 06:30 PM
  • To be confirmed
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apr 2020
  • 12:30 PM - 01:30 PM
  • To be confirmed
27
feb 2020
  • 12:30 PM - 1:30 PM
  • Haldane Room, Wolfson College
14
jun 2019
About Us
A vision for an open, cross-disciplinary machine learning network
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
  • Psychology representative: Dr Yaling Hsiao
  • Engineering representative: Dr Stephen Suryasentana
  • Physics representative: Dr Peter Hatfield
  • Healthcare representative: Dr Antoniya Georgieva
Contact us below if you are interested in speaking at our events