MBZUAI Machine Learning Winter School 2026: Representation Learning & GenAI

About the Winter School

The MBZUAI Machine Learning Winter School: Representation Learning & GenAI is an intensive 5-day program that brings together world-leading researchers to explore the cutting-edge developments in modern machine learning and generative artificial intelligence. This comprehensive program combines keynote presentations, technical lectures, and hands-on practical sessions, offering participants direct access to the latest research and methodologies from pioneers who are shaping the future of AI.

The winter school focuses on the revolutionary advances in deep learning that have enabled powerful generative capabilities across multiple domains. From large language models to diffusion models for images and videos, these breakthrough techniques are transforming how we approach AI research and applications.

Target Audience

This winter school is designed for:

Graduate students (PhD and Master's) in machine learning, computer science, AI, or related fields
Exceptional undergraduate students with strong mathematical and programming backgrounds
Early-career researchers and industry practitioners seeking to advance their expertise in representation learning and generative AI
Academic researchers looking to explore new directions or transition into generative AI research

Prerequisites

Strong mathematical foundation: Linear algebra, calculus, probability theory, and statistics
Proficiency in Python programming (required) with experience in ML libraries (NumPy, PyTorch/TensorFlow)
Basic understanding of machine learning concepts: Neural networks, optimization, and deep learning fundamentals
Recommended: Prior coursework or research experience in machine learning or computer vision/NLP

🎯 Apply Now! 🚀

Ready to join the future of AI? Apply for the MBZUAI ML Winter School 2026!

📝 Apply Now 📝

📋 Application Requirements:

📄 Up-to-date CV: Please ensure your CV is current and comprehensive
📅 Availability confirmation: Ensure you will be available for the entire duration of the school (February 9-13, 2026)
💌 Letter of motivation: Explain why we should pick you over others. Pro tip: Make it personal and authentic - we can spot an LLM-generated letter from miles away! 😉
📜 Letter of recommendation (recommended): From an instructor, supervisor, or manager who can speak to your abilities and potential

⚠️ Important: Please review all requirements carefully before submitting your application. Incomplete applications may not be considered.

⏰ Application Deadline: October 10th, 2025

📅 Timeline: You'll hear back from us by November.

Confirmed speakers and lecturers

The school brings together world-leading researchers and practitioners from academia and industry to share cutting-edge insights in representation learning and generative AI.

Michael Bronstein Professor, Imperial College London

Arthur Gretton Professor, University College London

Salman Khan Associate Professor, MBZUAI

Alexander Korotin Assistant Professor, Skoltech

Ivan Laptev Professor, INRIA - MBZUAI

Eric Moulines Professor, École Polytechnique - MBZUAI

Yuandong Tian Research Scientist Director, Meta GenAI

Kun Zhang Professor, Carnegie Mellon University - MBZUAI

More lecturers to be announced soon Stay tuned for additional speakers

School Program

The winter school features a comprehensive 5-day program combining theoretical foundations with practical applications. The schedule includes:

Technical lectures covering cutting-edge developments in modern machine learning
Hands-on practical sessions
Collaborative coding sessions and project work
Panel discussions on the future of AI research and applications
Networking opportunities with industry practitioners and academic researchers

Participants will gain direct access to the latest research methodologies and have opportunities to engage with pioneers who are shaping the future of AI. A detailed program will be available closer to the winter school date.

MBZUAI Machine Learning Winter School 2026

Representation Learning & GenAI