Dieuwertje Alblas - MIA
Riccardo Bardin - MACS
Vincent Bosboom - MACS
Nicoló Botteghi - MIA
Xiaoyu Cheng - MACS
Lars Corbijn van Willenswaard - MACS
Sven Dummer - MIA
Sagy Ephrati - MMS
Arnout Franken - MMS
Elena Giamatteo - MACS
Abdul Halim - MACS
Lucas Jansen Klomp - MIA
Manu Kalia - MIA
Muhammad Hamza Khalid - MACS
Nishant Kumar - MACS
Kaifang Liu - MACS
Xiangyi Meng - MACS
Nida Mir - MIA / MDI-TNW
Kevin Redosado - MMS
Len Spek - MIA
Julian Suk - MIA
Alexander Wierzba - MAST
Fengna Yan - MACS
Weihao Yan - MIA
source: http://www.malinc.se/math/trigonometry/geocentrismen.php - Heeringa - MIA

Scientific Machine Learning (SciML)


Scientific Machine Learning (SciML) is an emerging area in computational science that investigates the synergistic integration of scientific computing and machine learning, with the goal of combining the strengths and compensating the weaknesses of both. In particular, SciML aims to (i) use numerical models for the improvement of established machine learning techniques, (ii) use data-driven machine learning techniques to assist numerical simulations, and (iii) create new efficient, reliable, and robust methodologies by employing aspects from both approaches. The SciML research in the MIA group focuses on:


People working on this subject within SACS are:

Staff:

PhD