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MS1. High-dimensional Bayesian networks

MS2. Functional Data Analysis (I)

MS3. Spatio-temporal Data Science

MS4. Interpretability and explainability of algorithms

MS5. High-dimensional variable selection

MS6. Fair learning

MS7. Optimal transport for data science

MS8. Adversarial Machine Learning

MS9. Probabilistic Learning

MS10. New Approaches in Combinatorial Optimization

MS11. Mathematical Optimization Methods for Decision Making

MS12. Decision aid and data science models for disaster management

MS13. Mathematical support to resource and process management in health services

MS14. Mathematical Optimization for Data-Driven Decision-Making

MS15. Mathematical Optimization, Classification and Regression

MS16. Data Science Applications

MS17. Non-linear approximation, vision and images

MS18. Neural networks for Mathematicians

MS19. Machine learning techniques in control theory and inverse problems

MS20. Solving inverse problems using data-driven models

MS21. New perspectives in Computational Mathematics (I)

MS22. New perspectives in Computational Mathematics (II)

MS23. Statistical analysis of complex data (I)

MS24. Statistical analysis of complex data (II)

MS25. Digital Twins

MS26. New Perspectives in Data Science

MS27. Mathematical Optimization in Industry

MS28. ML and NLP models: from notebook to production deployment

MS29. Functional Data Analysis (II)

MS30. Data Science in Action


Important Dates

Grant application:
September 20th 2021
Notification of acceptance on grants:
October 1st 2021
Early registration until:
October 1st 2021