Register now After registration you will be able to apply for this opportunity online.
This opportunity is not published. No applications will be accepted.
Artificial Intelligence for Engineering Applications (TU Delft Summer School)
APPLICATION CLOSED - 26 – 30 August 2024 - This summer school focuses on harvesting the power of AI to extract actionable information from raw data. The course integrates AI principles with engineering applications, offering students the opportunity to learn advanced computational techniques and apply them to complex engineering challenges. This synergy of AI and engineering is designed to empower students with the skills to innovate and optimize in the field of engineering and beyond.
Data-driven decision-making is becoming a crucial skill in dealing with engineering systems that generate vast amounts of data from the automation system. Data science is improving our understanding of complex phenomena even faster than physical models have done in the past. Engineering Systems are composed of many complex elements, and their mutual interaction is not trivial to evaluate and predict by adopting the conventional first principles physics-based models.
This course will exploit advanced statistical techniques to build models directly based on the large amount of historical data collected by the recently advanced automation systems without prior knowledge of the underlying physical system. The course will focus on Artificial Intelligence (AI), Machine Learning (ML), and Data-driven models (DDMs) for engineering applications, including linear and non- linear models, shallow and deep models, and the best practices for model selection and error estimation. Numerical examples and real-life problems will be proposed and analysed, from bearings fault prediction, to fuel consumption optimisation. All course material will be freely available in PDF format for a complete understanding of the related subjects as well as for future consultation. During the afternoon session, hands-on workshops will be delivered with numerical examples focused on various aspects of AI, ML, and DDMs.
The course is designed for students interested in data analysis with an engineering background, numerical skills, and a rudimentary understanding of statistics. This course covers methodologies necessary for inferring useful information and identifying underlying patterns from raw, incomplete, noisy, and corrupted data that is present in real-life engineering applications. This is achieved by introducing concepts and methods used to model a wide range of systems based on available data.
**Learning Objectives** On completion of the course the student is expected to be able to achieve the fol- lowing Learning Objectives (LO):
- LO 1: Describe several models for supervised and unsupervised inference from data. Critically evaluate statistical analysis. Critically assess the fit of statistical models. - LO 2: Assess the strengths and weaknesses of each of these models and inter- pret the mathematical equations from linear algebra, statistics, and probability theory used in the learning models. - LO 3: Implement efficient learning algorithms in the MATLAB language, applied to engineering problems. - LO 4: Design test procedures to evaluate the model hyperparameters (model selection) and its error (error estimation). Develop an appropriate exper- imental research design for an engineering case study considering practical limitations.
For the detailed porgramme please see https://idealeague.org/artificial-intelligence-for-engineering-applications-2024/
For the detailed porgramme please see https://idealeague.org/artificial-intelligence-for-engineering-applications-2024/
Participation Details
TU Delft, the Netherlands
TU Delft, the Netherlands
Not specified
There are no registration and accommodation fees. Students from IDEA League member universities selected to participate in a summer school only have to pay for their own travel costs where applicable.
There are no registration and accommodation fees. Students from IDEA League member universities selected to participate in a summer school only have to pay for their own travel costs where applicable.
How to apply
Application is open to Master and PhD Students of the member universities of the IDEA League Alliance http://idealeague.org :
- Chalmers University of Technology
- ETH Zürich
- Politecnico di Milano
- RWTH Aachen
- TU Delft
Application is open to Master and PhD Students of the member universities of the IDEA League Alliance http://idealeague.org :
- Chalmers University of Technology - ETH Zürich - Politecnico di Milano - RWTH Aachen - TU Delft
In order to apply you need to **login to SiROP with your university account**. When your email belongs to a partner university the affiliation is created automatically.
After successful affiliation you can return to this event and you will find a **button "Apply" right at the top**.
If you need to affiliate manually please see: http://bit.ly/sirop-affiliate
In order to apply you need to **login to SiROP with your university account**. When your email belongs to a partner university the affiliation is created automatically.
After successful affiliation you can return to this event and you will find a **button "Apply" right at the top**.
If you need to affiliate manually please see: http://bit.ly/sirop-affiliate
The following documents will be requested from you as attachments you will have to upload with your application:
- Curriculum vitae & publications list
- Letter of motivation
- Letter of recommendation (optional)
- Supervisor approval (for PhD students from Chalmers)
The following documents will be requested from you as attachments you will have to upload with your application:
- Curriculum vitae & publications list - Letter of motivation - Letter of recommendation (optional) - Supervisor approval (for PhD students from Chalmers)
For more information please read the FAQ:
https://idealeague.org/students/summerschools/
If you have any further questions regarding the application process, please contact the organizer office@idealeague.org.
For more information please read the FAQ:
https://idealeague.org/students/summerschools/
If you have any further questions regarding the application process, please contact the organizer office@idealeague.org.
The IDEA League offers the students of the network (Chalmers, ETH Zurich, Politecnico di Milano, RWTH Aachen, TU Delft) the unique opportunity to develop new insights into current research, and to enhance their skills and academic excellence.
