IAȘI AI

Scientific Machine Learning (SciML) represents a blend of scientific computing and machine learning methodologies.

Traditionally, scientific computing relies on mechanistic modeling (ie., differential equations), with a focus on domain models based on physical laws and scientific knowledge. However, while mechanistic models of lots of scientific phenomena are routinely available, our computational capabilities are unable to keep up with the increasingly demanding requirements of realistic simulation.

On the other hand, machine learning focuses on developing non-mechanistic data-driven models which require minimal knowledge and prior assumptions, are often faster to evaluate, but rely on "big-data" and lots of parameters. Merging the two disciplines together offers the opportunity for mechanistic and non-mechanistic models and methodologies to complement each other in order to improve accuracy, interpretability and plausibility of the models while simultaneosly reducing data requirements and accelerating model training. This talk will give an overview of current challenges in SciML and discuss application areas of interest.

Our speaker for this meetup, Bogdan Burlacu, is a senior researcher at the University of Applied Sciences Upper Austria where he develops algorithms and methodologies for interpretable physical modeling using symbolic regression. He has a bachelors degree in systems and computer engineering from the "Gheorge Asachi" Technical University of Iasi, Romania and a PhD in Software Engineering from the Johannes Kepler University of Linz, Austria. His main research interests are machine learning, symbolic regression, physical-based modeling and high performance computing.

Meet the speaker

Bogdan Burlacu Senior Researcher

Bogdan Burlacu is a senior researcher at the University of Applied Sciences Upper Austria where he develops algorithms and methodologies for interpretable physical modeling using symbolic regression. He has a bachelors degree in systems and computer engineering from the "Gheorge Asachi" Technical University of Iasi, Romania and a PhD in Software Engineering from the Johannes Kepler University of Linz, Austria. His main research interests are machine learning, symbolic regression, physical-based modeling and high performance computing.