
About the PhD School
As part of the CWI Research Semester on Learning Enhanced Optimization, we are excited to host an International PhD School during the first week of September. The PhD School explores recent theoretical developments at the intersection of Machine Learning and Optimization.
As computation increasingly moves into real-time, data-driven, and uncertain settings, classic algorithmic paradigms are being reimagined through the lenses of learning theory, incentive design, and machine-learned predictions. The PhD School delves into the theoretical and algorithmic foundations of integrating such novel techniques into algorithm design.
This three-day event, running from Tuesday to Thursday, is tailored for PhD students interested in the growing intersection of Machine Learning and Optimization. The school combines lectures with collaborative group works.
The school will feature lectures from three renowned researchers:
- Michal Feldman (Tel Aviv University, Israel)
- Anupam Gupta (New York University, USA)
- Ola Svensson (EPFL, Switzerland)
Who should attend?
The school is aimed at PhD students in theoretical computer science, algorithms, machine learning, operations research and related areas. Please note that there will be a strong focus on theoretical and algorithmic foundations. Advanced Master’s students and early-career researchers/postdocs with a strong theoretical background are also warmly encouraged to participate.