Upcoming schools

March 1-12, 2027 Onna (Okinawa), Japan Event Website

Organizers: Makoto Yamada, Kenji Fukumizu, Masashi Sugiyama, Amedeo Roberto Esposito

MLSS 2027 Okinawa is the next edition of MLSS 2024 Okinawa. It is open to all applicants, and we aim to select 200 highly motivated participants. Our main target audience is master's and Ph.D. students with a strong technical background in machine learning related areas. A small number of industry practitioners, professors, researchers, and outstanding undergraduate students may also be considered depending on space and availability. Industry applicants may be able to attend through sponsorship from their company. All participants are expected to have experience programming in Python, a strong interest in machine learning, and a basic understanding of linear algebra, calculus, probability, and statistics.

OIST is located in Onna Village, Okinawa, Japan, which is known as a beautiful resort area. The average temperature in Okinawa in March is around 16–21°C (61–70°F), and there are many beaches near OIST. One of the participants from MLSS 2024 made a YouTube video about the event (https://www.youtube.com/watch?v=ZvD8mQ8_UG4), so please take a look!

Venue: OIST Auditorium

August 31st to September 11th, 2026 Tübingen, Germany Event Website

Organizers: Lancelot Da Costa, Kateryna Kononenko, Vincent Berenz, Hsiao-Ru Pan, Simon Buchholz, Bernhard Schölkopf

The Machine Learning Summer School returns to the Max Planck Institute for Intelligent Systems, from 31 August to 11 September 2026. This year marks a special milestone: the 50th edition of MLSS. Since its founding in 2002, MLSS has become one of the most respected venues in the field, bringing together graduate students, researchers, and professionals for a deep dive into modern machine learning, data analysis, and inference. This year is no exception: we are thrilled to welcome a faculty of world-renowned speakers who will share both the foundations and the cutting edge of the field. Through lectures, tutorials, and poster sessions, participants gain direct access to cutting-edge ideas and the people driving them.

Hosted once again in the beautiful medieval university town of Tübingen, southwestern Germany, the school combines academic rigour with a warm and open atmosphere. Beyond the talks, participants are encouraged to exchange ideas during informal discussions and social events, and to engage with speakers in a relaxed setting.

We hope you will join us for this special occasion and build lasting connections with fellow researchers from every corner of the globe!

Venue: Max Planck Institute for Intelligent Systems, Tübingen

June 15-26, 2026 Columbia University, New York City, USA Event Website

Organizers: Ali Hirsa, Gary Kazantsev, David Rosenberg, Alex Smola, Paola Cascante-Bonilla, Carlos Fernandez-Granda, Andrew Owens

We are pleased to announce that the Machine Learning Summer School 2026 will run for two weeks in June 2026 in New York City, at the Columbia University campus. We will host approximately 200 PhD students alongside key faculty, industry speakers, and invited practitioners to take part in a rigorous program that will balance practical training on state-of-the-art systems (evaluation, agentic AI, RAG, data pipelines) with forward-looking research areas (alignment/safety, interpretability, verification & reasoning).

Our objectives are to deliver a rigorous curriculum, an excellent experience for participants, and measurable impact on research. The program will combine lectures, tutorials, invited talks, and hands-on labs. In addition to reinforcement learning theory, LLM alignment/safety, RAG & agents, and time series analysis, the program will include systems and efficiency for LLMs, post-training and preference optimization, synthetic data practices, evaluation, mechanistic interpretability, and reasoning.

Venue: Columbia University Morningside Campus