The 2021 Platform for Advanced Scientific Computing (PASC) Conference, co-sponsored by the Association for Computing Machinery (ACM) and the Swiss National Supercomputing Centre (CSCS), will be held on July 5-8, 2021, at the University of Geneva in Geneva, Switzerland. The PASC Conference series is an international and interdisciplinary platform for the exchange of knowledge in scientific computing and computational science with a strong focus on methods, tools, algorithms, application challenges, and novel techniques and usage of high performance computing (HPC). BIDS Faculty Affiliate Rachel Slaybaugh will co-chair this year's engineering section.
— Submissions due December 13, 2020
— Expression of Interest (EOI) due November 22, 2020
— Full submissions (if invited after EOI notification): due January 17, 2021
- Chemistry and Materials
- Life Sciences (incl. but not limited to biophysics, genomics, bioinformatics, systems biology, neuroscience and computational biology, …)
- Physics (incl. but not limited to astrophysics, cosmology, plasma modelling, QCD, …)
- Climate and Weather
- Solid Earth Dynamics
- Engineering (incl. but not limited to CFD, computational mechanics, computational engineering materials, turbulent flow, …)
- Computer Science and Applied Mathematics
- Emerging Application Domains (incl. but not limited to social sciences, finance, …)
Rachel Slaybaugh is an Assistant Professor of Nuclear Engineering at the University of California, Berkeley. Slaybaugh researches computational methods applied to nuclear reactors, nuclear non-proliferation and security, and shielding. She recently served as a Program Director at the Advanced Research Projects Agency-Energy (ARPA-E) and has served on the Nuclear Energy Advisory Committee (NEAC). She is the founding Board Chair for Good Energy Collective, and a Senior Fellow at the Breakthrough Institute. Prof. Slaybaugh is developing programs to train and inspire the next generation to innovate in clean energy, including the Nuclear Innovation Bootcamp, and also focuses on improving transparency and reproducibility in computational science and scientific publication.