Description
The panel discussion is organized as an activity of the Central European Chapter of Women in HPC, committed to raising awareness of the unique challenges women face in high-performance computing (HPC) and advocating for inclusive policies and practices within organizations. By promoting these values, they aim to create a more welcoming environment for everyone in HPC.
We will host users and researchers who work with HPC in their fields. They will share their experiences, perspectives, and advice on how to establish a more inclusive environment for women and achieve greater balance in this area.
Claudia Blaas-Schenner studied Technical Physics at TU Wien, where she also earned her PhD and completed her postdoc. She started with supercomputer calculations in 1990 and has since delved deeper into the field. Today, Claudia Blaas-Schenner is one of the world's most recognised HPC experts. In 2015, she founded the training programme at Austria’s supercomputer, the VSC, and has been its director ever since. She is one of the top experts in MPI and chair of the EuroMPI/Australia 2024 conference.
Alja Prah is part of the supercomputing team at Jožef Stefan Institute, involved with supporting most Slovenian supercomputers. At the same time she is continuing to pursue her research (from which she obtained a PhD in Pharmacy in 2021) as part of the Theory Department at the National Institute of Chemistry.
Ivona Vasileska has a PhD in nuclear engineering and has been a researcher and teaching assistant at the Faculty of Mechanical Engineering, University of Ljubljana, Slovenia. Her research focuses on plasma physics, nuclear fusion, and high-performance computing (HPC). In recent years, she has expanded her work to parallel computing for machine learning. Vasileska has contributed to over 12 European projects in fusion and HPC and has authored more than 30 journal and conference papers in high-impact publications in fusion, and HPC.
Iva Černoša is a PhD student of bioinformatics at University of Ljubljana. She uses supercomputers as part of her research for analysis of big genomic files and to train models for prediction of gene expression in plants.
