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Lecturer
Prof. Cynthia Rudin, Duke University (USA),
Prof. Emma Strubell, Carnegie Mellon University (USA),
Prof. Golnoosh Farnadi, McGill University & Mila (Canada),
Prof. Amir Baratir Farimani, Carnegie Mellon University (USA),
Prof. Matthieu Cord, Sorbonne Université (France), Scientific Director of Valeo AI,
Content and organization
This year, the Deep Learning School will address the hot topics of the moment in Deep Learning, of course, but also NLP and the SciML revolution.
Speakers will address these issues and the concerns they may generate (personal data management and retention, environmental impact, explicability/interpretability, health/biology, etc.) from a responsible, human-centric and ethical angle.
- Frugal AI and NLP: Reducing the environmental footprint of large language models: challenges and solutions, with Professor Emma Strubell, who leads the Structure in(g) LAnguage LAB (SLAB) in the Language Technologies Institute at Carnegie Mellon University.
- Responsible AI and Equity: Algorithmic Fairness: A Pathway to Developing Responsible AI Systems with Professor Golnoosh Farnadi, who is a co-director of McGill’s Collaborative for AI & Society (McCAIS), and the founder and principal investigator of the EQUAL lab (EQuity & EQuality Using AI and Learning algorithms) at Mila/McGill University.
- Interpretable AI: Simpler Machine Learning Models for a Complicated World with Professor Cynthia Rudin, who directs the Interpretable Machine Learning Lab at Duke University.
- AI & Physics/Numerical Simulation: Robust Representation Learning with Transformers and LLMs for Engineering Problems with Professor Amir Barati Farimani, who heads the Mechanical and Artificial Intelligence Laboratory (MAIL) at Carnegie Mellon University.
- Foundation Models and Generative AI in Vision: From Transformers to Foundation models for Multimedia, and Generative AI with Matthieu Cord, full professor at Sorbonne Université, member of the ISIR laboratory, holder of the VISA-DEEP AI Chair and Scientific Director of Valeo AI.
Level
Whether you are a researcher, an engineer, an expert in deep learning, or simply eager to learn more about these crucial methods at the core of modern AI, this program is designed for you!
Course Duration
2:45-hour classes and 3:00-hour labs each day
Course Type
Seasonal School
Participation terms
Fees for one person exclusively reserved for students and staff from AIDA, Université Côte d'Azur, and 3IA Côte d'Azur consortium (Centrale Méditerranée, CNRS, Ecole de l'Air et de l'Espace, EURECOM, Inria, Inserm, SKEMA). Registration required on AIDA and on the event website : https://my.weezevent.com/deep-learning-school-2024-aida.
Language
English
Modality (online/in person):
In person
Notes
Participants will have the opportunity to attend the program on the Campus SophiaTech, located in Sophia Antipolis, France. This work has benefited from state aid managed by ANR under France 2030 for the EFELIA Côte d'Azur project, reference ANR 22 CMAS 0004.
