The IN-DEEP consortium gathered for the Scientific Review meeting held on January 28, 2025 to discuss key advancements in the project.
Day 1 - Welcome & Scientific presentations.
Day 2 - Scientific presentations.
Day 3 - Deep PDE solvers implementation (technical course).
Day 4 - Research methodology and tools (transversal skills course).
Day 5 - Communication, dissemination, and transfer of knowledge.
Day 1 - Welcome & Scientific presentations.
Day 2 - Scientific presentations.
Day 3 - Physics-aware & mathematics-infused DL for PDEs (technical course).
Day 4 - Communication and public speaking (transversal skills course).
Day 5 - Communication, dissemination, and transfer of knowledge.
Day 1 - Welcome & Scientific presentations.
Day 2 - Scientific presentations.
Day 3 - Mathematical modeling and benchmark problems in health applications (technical course).
Day 4 -Introduction to research funding. Research Programmes (transversal skills course).
Day 5 - Communication, dissemination, and transfer of knowledge.
Day 1 - Welcome & Scientific presentations.
Day 2 - Scientific presentations.
Day 3 - AI tools for green energy technologies (technical course).
Day 4 - My Ph.D., what next? (transversal skills course).
Day 5 - Communication, dissemination, and transfer of knowledge.
Topics: Supervised vs. unsupervised learning in deep PDE solvers. Synthetic datasets in inverse problems. Challenges in experimental datasets for industrial inverse problems.
Practical training: Data sampling in TensorFlow for a simple PDE model.
Courses: Research articles. Effective grant proposals. Writing about sciences for a general audience.
Practical training: Improve your own work-in-progress paper. Grant proposal case study: HORIZON-MSCA-2022-DN-01-01. Turn your research paper and findings into a blog post.
Topics: Explainable AI: concepts and taxonomies. Explainability in deep neural networks. Application to geophysics, healthcare, and urban traffic forecasting.
Topics: Sources of financing. EU funds and regulations on intellectual property for entrepreneurs. Strategic innovation. Prospect theory. Customer value proposition. Inspirational success stories (and the lessons learned).
Practical tutorial: Assess the industry trends in AI. Identify an opportunity for creating a tech business. Draft a start-up business plan.