Oxford
Machine Learning
Summer School


At AI for Global Goals, we aim to provide our global participants with best-in-class training on a broad range of advanced topics and developments in machine learning (ML) -- including deep learning (DL).
Similar to our past schools, OxML 2023 will cover some of the most important topics in machine learning (ML) and deep learning (DL) that the field is showing a growing interest in (e.g., statistical/probabilistic ML, representation learning, reinforcement learning, causal inference, vision & NLP, geometrical DL, ...) and their applications in sustainable development goals (SDGs).
Our 2023's program consists of multiple schools such as MLx Health, MLx Finance, NLP, MLx Cases, ML Fundamentals, MLx Products, MLx Ops, etc. OxML Health and Finance schools will take place at the University of Oxford's Mathematical Institute between 8-16 July, 2023, and will follow a hybrid format (i.e., participants can choose to attend online or in-person).

MLx Fundamentals
8-10 May 2023
ONLINE
MLx Cases
30 May – 30 June
ONLINE

MLx Finance & NLP

MLx Health
IMPORTANT DATES

8-11 July:
ML x Finance & NLP
13-16 July:
ML x Health

8-10 May:
ML x Fundamentals
June: ML x Cases
April 2023
Notification of Acceptance
27 March 2023
Applications Close

6 November 2022
Applications Open
MACHINE LEARNING & SDGs
The field of Machine Learning (ML), including Deep Learning (DL), has seen tremendous growth, in the past decade. 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.
On the other hand, the Global Goals (i.e., the 17 goals officially known as the UN Sustainable Development Goals, or SDGs) can be among the biggest beneficiaries of AI. According to a report by PwC, by 2030, the use of AI for environmental applications could contribute up to $5.2T to the global economy; it could also create 38.2 million net new jobs globally. Adding the impact to overlapping industries such as healthcare, finance, education and more, the size of this impact can be even bigger.
OxML aims to bring some of the best talents in machine learning together with the primary goal of providing them with world-class training in ML/DL, with the main objective of raising awareness about AI+SDG. Our goal is to train and inspire more scientists and engineers in ML to pursue research towards the pledge to leave no one behind, that lies at the core of SDG’s. This year's program consists of two main modules: ML x Finance/NLP (July 08-11) and ML x Health (July 13-16); participants of both modules will have complementary access to modules such as ML Fundamentals 8-10 May) and ML Cases (June).
PROGRAM COMMITEE
OxML 2023 SPEAKERS
ML x HEALTH

Gitta Kutyniok
Professor of Applied Maths
University of Munich

Kyunghyun Cho
Associate Prof. of computer science & data science, NYU
Senior Director of Frontier Research, Genentech
CIFAR Fellow

Mireia Crispin
Lecturer in Integrated Cancer Medicine
University of Cambridge

Louis-Philippe Morency
Associate Prof. of Computer Science
Carnegie Mellon University

Cheng Zhang
Principal Researcher
Microsoft Research

Munmun De Choudhury
Associate Prof. of Interactive Computing
Georgia Tech

Marwin Segler
Principal Researcher
Microsoft Research

Ishan Misra
Research Scientist
Facebook AI Research (FAIR)

Kazem Rahimi
Professor of Cardiovascular Medicine
University of Oxfor

Ali Eslami
Research Scientist
Google DeepMind
MLx FINANCE & NLP

Rama Cont
Professor of Mathematical Finance
University of Oxford

Stefan Zohren
Director of Oxford-Man Institute
University of Oxford

Blanka Horvath
Professor in Oxford Math Finance Group
University of Oxford

Svetlana Bryzgalova
Assistant Professor of Finance
London Business School

Mihai Cucuringu
Associate Professor of Statistics
University of Oxford

He He
Assistant Professor of computer science
NYU

Rahul Savani
Professor of Computer Science
University of Liverpool

Edward Grefenstette
Head of ML at Cohere,
Honorary Professor at UCL

Diyi Yang
Assistant Professor
Stanford University

Ryan Cotterell
Assistant Professor of Computer Science
ETH Zürich

Pasquale Minervini
Lecturer in NLP
University of Edinburgh, UCL

Stephen Clark
Head of AI
Quantinuum,
ML x FUNDAMENTALS

Yali Du
Lecturer in AI
King's College London

Haitham Bou Ammar
RL Team Leader
Huawei Research

Matthieu Zimmer
Senior Research Scientist
Huawei

Rasul Tutunov
Research Scientist
Huawei

Eduardo C. Garrido-Merchán
Research Scientist
Universidad Pontificia Comillas
ML x CASES

Khémon BEH
Founder & CEO
Quickscale.ai

Vincent Moens
Research Engineer,
Meta
PARTNERS
OxML schools are organised by AI for Global Goals and in partnership with CIFAR and the University of Oxford's Deep Medicine Program.
SPONSORS
COMMUNITY PARTNERS
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.