MAY 19-23, 2025
ML4SCIENCE & ENGINEERING SUMMER SCHOOL
MAY 19-23, 2025
ML4SCIENCE & ENGINEERING SUMMER SCHOOL
The Inductiva Machine Learning for Science & Engineering Summer School is designed for researchers, engineers, and professionals eager to explore the latest advancements in Artificial Intelligence (AI) and Machine Learning (ML) applied to science and engineering.
The Program
This program offers a deep dive into state-of-the-art ML techniques and their transformative impact across various scientific fields. While Computational Fluid Dynamics (CFD) will be a key focus, broader applications in engineering and scientific computing will also be explored.
Participants will engage with experts, explore real-world use cases, and gain hands-on experience in AI-driven simulations. This initiative is proudly supported by AptWind, an EU-funded project under the Marie Skłodowska-Curie Actions (MSCA) within Horizon Europe. AptWind aims to train a new generation of innovative, industry-oriented researchers capable of addressing current and future challenges in atmospheric flow physics and turbulence for wind energy applications.
This collaboration enriches the summer school's offerings, providing participants with insights into cutting-edge research and applications in wind energy. Join us to expand your expertise, collaborate with peers, and leverage ML to drive innovation in science and engineering
Meet Industry Leaders
Keynote Speakers
Lab Assistants
Organizers
Funding
Organized by Inductiva in collaboration with FEUP
Agenda
May 19th-23rd, 2025 (5 days)
FEUP The Engineering Faculty of the University of Porto.
Why Attend the Inductiva ML Summer School?
This invitation-only summer school is a unique opportunity to deepen your expertise in Artificial Intelligence and Machine Learning and explore their real-world applications in science and engineering. Over five immersive days, attendees will:
Learn from leading experts about the latest advancements in ML for Computational Fluid Dynamics (CFD), physics-based simulations, and broader scientific applications.
Work on real-world challenges, apply AI-driven simulations, and enhance your technical skills through practical sessions.
Connect with a diverse group of researchers, engineers, and professionals, fostering interdisciplinary collaboration and knowledge exchange.
Benefit from contributions by AptWind, an EU-funded project advancing research in atmospheric flow physics and wind energy applications.
Discover how AI accelerates scientific discovery, optimizes simulations, and enhances computational research across multiple disciplines.
What to Expect from the Summer School
The event will offer world-class speakers, engaging workshops, and interactive sessions to provide advanced AI and ML research insights. Attendees will gain exposure to emerging technologies and innovations that are transforming industries.
Programme highlights include:
- A week of on-site sessions at FEUP, Porto.
- Networking opportunities with experts in the field.
- Opportunities to collaborate with peers and contribute to exciting AI projects.
Open Sessions
May 21, 2025
14:00 - 15:00pm
Piotr Mirowski:
Neural Compression of Atmospheric States
May 22, 2025
10:00 - 11:00am
Ricardo Vinuesa:
ML and CFD
May 22, 2025
11:30am - 12:30pm
Jousef Murad:
AI Agents in Engineering
May 22, 2025
14:00 - 15:00pm
Guilherme Beleza:
(TBC)
May 22, 2025
15:15 - 16:15pm
Hans Bihs:
(TBC)
May 23, 2025
10:00 - 11:00am
Jonathan Godwin:
Learning to Simulate Complex Physics
May 23, 2025
11:00am - 12:00pm
Hugo Penedones:
Will there be more Nobels for AI?
The room where the sessions will take place and the streaming link will be available shortly.
Logistics and Accommodation
Participants are responsible for arranging their own travel and accommodation. For convenience, we recommend staying near FEUP (Faculty of Engineering, University of Porto) to ensure easy access to the event venue.
Questions?
If you have any questions about the event or the invitation process, please contact Clara Gonçalves or Filipa Almeida through the email MLSummerschool@inductiva.ai