Dates: July 8-16, 2023 (Oxford Mathematical Institute + Virtual)
Application deadline: 27 March 2023
Everyone is welcome to apply to OxML 2023 regardless of their origin, nationality, and country of residence.
Our target audience are (1) PhD students with a good technical background whose research topics are related to ML, plus (2) researchers and engineers in both academia and industry with advanced levels of technical knowledge.
All applicants are subject to a selection process; we aim to select strongly motivated participants, who are interested in broadening their knowledge of the advanced topics in the field of ML/DL and their applications.
Given the overwhelming number of applications we receive, the application portal may close earlier than the deadline (March 27th) if the number of applications exceeds our capacity to review. Furthermore, we already began the review process in January, which will lead to notifications of acceptance being sent gradually, as we go applications. Please make sure you apply ASAP, to avoid disappointment.
Below is the list of our confirmed speakers to date — we will announce additional speakers in the coming weeks (follow the updates via the school’s website
, or Twitter
accounts). Note that, participants of both ML x Health and ML x Finance modules will have access to / can attend both ML x Fundamentals and ML x Cases module (as optional modules).
ML x Healthcare
(Ludwig Maximilian University of Munich) — Mathematics & theory of ML/DL
(NYU, CIFAR, Genentech) —Advanced topics in RL & ML for comp. bio.
(University of Cambridge) — ML, multi-omics, and oncology
(Facebook AI Research) — ML, computer vision, and learning with reduced supervision
(Microsoft Research) — Probabilistic ML & causal ML
ML x Finance
(University of Oxford) — Quantitative finance, ML for building market simulators
(University of Oxford) — Representation learning & (financial) time series
(University of Oxford) — Networks, statistical ML, and quant. finance
(University of Oxford) — Market Simulators, Deep Hedging
(ETH Zürich, University of Cambridge) — Computational linguistics, NLP & ML
(University of Liverpool , The Allen Turing Institute) — RL in Finance & Automated Trading
ML x Fundamentals
ML x Cases
(Meta) — ML Ops, PyTorch, DL software architectures
(Quickscale.ai) — ML applications, ML Ops
About OxML 2023
OxML schools have a special focus on ML and SDG
s. That is, in addition to theoretical ML lectures, it will have lectures on the application of ML in various SDGs areas.
OxML 2023 will have two separate 4-day schools: (1) ML x Health, and (2) ML x Finance.
To provide all participants with the necessary background in fundamental theory and implementation and coding of ML/DL models, our 2023 program will also have two additional modules: MLx Fundamentals, and MLx Cases (more info on the website). They will take place online, during May and June 2023, and are open to all accepted participants.
We aim to host ~250 participants in person (plus 300 virtually) in each school.
You can find out more about the previous schools — including the previous speakers — here
The schools' theoretical tutorials on modern ML (including DL) will cover topics such as:
Neural networks, deep learning / representation learning (with, with little, or without supervision), ...
Statistical/probabilistic ML (e.g., Bayesian ML, causal ML, variational inference, Bayesian neural networks)
NLP, computer vision, and multi-modal representation learning
On the applied side, the school will cover topics such as:
MLx Health: The applications of ML in imaging, genomics, electronic health records (EHR), drug discovery, ...
MLx Finance: The applications of ML in investment and asset mgmt., banking, insurance and emerging risks , hedging and options trading, ...
Reza Khorshidi, D.Phil. (Oxon)
Deep Medicine Program, The University of Oxford