Oxford Machine Learning Summer School 2020
OxML.2020 aims to provide the participants with best-in-class training on a broad range of advanced topics and developments in machine learning (ML) — including, deep learning. While the school covers the key topics in domains such as Bayesian ML, Computer Vision, NLP and reinforcement learning (as well as areas such as Causal ML, Topological ML, and Transfer Learning that the field is showing a growing interest in), there will be a special focus on medicine (the UN’s sustainable development goal #3), through a range of applied talks at the interface of machine learning and healthcare/biomedical sciences (e.g., medical imaging, genetics, drug discovery, and learning from multi-modal medical data). Participants (i.e., graduate students, post-docs and professionals) learn directly from world-renowned researchers and lecturers in ML (and biomedicine) in Oxford’s unique academic environment.
MACHINE LEARNING & HEALTHCARE
The field of Machine Learning (including Deep Learning) has seen tremendous growth, in the past decade. Accumulation of large datasets, availability of affordable computing power at scale, and new developments in intelligent algorithms are known to be the key drivers of this growth in the field. The number of ML papers on arXiv has grown faster than Moore's law, surpassing 100 papers per day, last year, and keeps growing. While such developments have simultaneously led to both optimistic and pessimistic views on AI and the future of society/humanity, one thing everyone agrees on is that certain industries and domains have benefited from AI more than others.
Healthcare can be one of the biggest beneficiaries of AI. Today, we spend 10 trillion dollars on healthcare, globally (that is 10% of global GDP). Despite such a huge spend, according to a report by Geneva Association, there is still a healthcare protection gap of 3.6 trillion dollars outside the US and EU; that is the out-of-pocket spending on health that entails a high risk of financial hardship and even impoverishment. Therefore, "Good health and well-being" is one of the important goals in the UN's Global Goals and the pledge to leave no one behind.
Oxford ML Summer School 2020 aims to bring some of the best talents in AI and medicine/healthcare together with the primary goal of providing them with world-class training in ML/DL and Deep Medicine. It will be a unique opportunity to learn about past, present and future of ML research in healthcare (from EHR, imaging, and genetics to wearable, drug discovery and more).
IMPORTANT DATES
January 2020
Applications Open
April 2020
Applications Close
May 2020
Acceptance Notification
August 2020
Oxford ML Summer School
TARGET AUDIENCES
To qualify for admission, applicants need to complete and submit an application form and have the necessary technical and academic qualifications (e.g., programming skills, and education in maths/stats/computer science/engineering/biomedical science or other related fields).
Expected participants:
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Postgraduate students (MSc, PhD)
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Academics (postdocs and faculty) in fields such as Machine Learning and Biomedical Sciences
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Industry practitioners in related fields.
SCHEDULE
A provisional program for the school is shared here; this will be updated in the coming weeks (see the timeline for more information).
PARTNERS
OXML 2020 is organised by AI for Global Goals and in partnership with Oxford Saïd Business School and CIFAR.
CONTACT US
If you are interested in attending our schools, discuss sponsorship/partnership opportunities, or simply stay updated about our progress, please send us an e-mail, or subscribe to our mailing list, below.