The session starts with a short presentation (3 min) of the Industrial Research School in Complex Systems (INRESCOS) followed by 4 student presentations on the topic of artificial intelligence. QA after the presentations (approx. 10 min)
Anomaly Detection in High Energy Physics at CERN by Maria Elena Perruzza
The focal point of the project will be to develop a Particle Identification algorithm using End-to-End technologies and Graph Convolutional Neural Networks.
Utilizing Big data within early phase of the New Product Development Process (NPD) by Ali Haytham
Use of feedback data in terms of failure data in the early phase product development process to enhance data-driven decision-making.
Adaptive Operation of Hydropower Units for Increased Integration of Renewable Resources (AdaptHydro) by Kaled Aleikish
Investigating whether data-driven modeling solutions, such as machine learning, can be used for automatic tuning of PSS (power system stabilizer) during the operation of the hydropower plant.
Anomaly Detection, Prognostics, and Diagnostics - Machine Learning for Large Complex Systems at the Hadron Calorimeter of the CMS Experiment by Mulugeta W. Asres
Use of deep learning advancements to monitor complex systems.
The session is in English.
Professor Kristin Falk and Project manager Monica Fagerli are responsible for this event.
