Guided Affinity GroupS (GAGS) are designed to help students get more out of SIAM CSE conference sessions. Led by CSE volunteer community members, learning groups explore conference topics from an entry level perspective by meeting prior to the conference session, attending the conference session together, and then meeting afterwards. BE attendees will meet with affinity group leads virtually prior to the conference and then meet daily with leads. Attendees will provide a 5-10 minute presentation on what was discovered and learned from the experience at the BE Wrap up session. All conference attendees are invited to attend the morning affinity group stand-ups and participate in expanding the educational experience of our BE attendees. Students who wish to attend the GAGS must pre-register by sending an email to info@shinstitute.org.
GAGS Standups
The first thing every morning at SIAM CSE21 the affinity groups will gather to discuss three questions:
What did we learn yesterday?
What are we planning on learning today?
What do we need to do today to get the final presentation complete?
GAGS Deliverable
Each group will present for a maximum of 10 minutes during the BE Wrap Up Session. Best practices in presentations say that no more than 5 slides should be used. Students will be required to create and deliver this presentation. In the slides we’d like the group to talk about:
What was their affinity group?
What were the pedagogical goals of the team?
Who was involved? (Leader, team, others?)
What did they learned?
What was the most effective ways to learn?
Particular talks/researchers they felt helped them?
What’s next?
Here is a list of the planned Guided Affinity Groups:
- Meshes and Particles and GPUs Oh My!, Ann Almgren, Berkeley LabAbstract: Computational science seems to get more and more complicated every year — we talk about multiphysics, multiscale, multirate, multicore and more. We talk about… Read more: Meshes and Particles and GPUs Oh My!, Ann Almgren, Berkeley Lab
- Quantum algorithms for scientific computing, Giacomo Nannicini, IBM T.J. Watson research centerAbstract: Quantum computing has been studied for almost 40 years, but only recently hardware capable of running simple quantum algorithms has become available. Because quantum… Read more: Quantum algorithms for scientific computing, Giacomo Nannicini, IBM T.J. Watson research center
- Ice sheet modeling, Daniel Martin, Lawrence Berkeley National LaboratoryAbstract: Modeling the dynamics of ice sheets like those found in Antarctica and Greenland has become an exciting research topic. Once thought to be stable… Read more: Ice sheet modeling, Daniel Martin, Lawrence Berkeley National Laboratory
- Inverse Problems and Applications, Malena Espanol and Mirjeta Pasha, Arizona State UniversityAbstract: In many physical systems, the internal structure of a material can only be observed by analyzing measurements obtained on the exterior of it. For… Read more: Inverse Problems and Applications, Malena Espanol and Mirjeta Pasha, Arizona State University
- Software Productivity and Sustainability for Science and Engineering, Anshu Dubey, Argonne National LaboratoryAbstract: Computing has become a critical component of science and engineering. Software is the key crosscutting technology that enables advances in mathematics, computer science, and… Read more: Software Productivity and Sustainability for Science and Engineering, Anshu Dubey, Argonne National Laboratory
- CSE Applications, Stephen Wood, National Aeronautics and Space AdministrationAbstract: From a certain point of view, scientists and engineers are customers in need of new digital tools to forge the technologies of tomorrow. Teams… Read more: CSE Applications, Stephen Wood, National Aeronautics and Space Administration
- Open Science Practices, Kyle Niemeyer, Oregon State UniversityAbstract: Open-science practices are important to ensure the results of research, and in particular publicly funded research, are accessible to all, to make findings reproducible… Read more: Open Science Practices, Kyle Niemeyer, Oregon State University
- Learning and Algorithms on Graph-Structured Data, Aydin Buluc, Berkeley LabAbstract: Graphs provide a rich abstraction for modeling interactions in science and society. Graph algorithms have been instrumental in solving some of the hardest combinatorial… Read more: Learning and Algorithms on Graph-Structured Data, Aydin Buluc, Berkeley Lab
- Going Deep with AI and Machine Learning for Science and Engineering, Alina Lazar, Youngstown State UniversityAbstract: Currently, there are 2.5 quintillion bytes of electronic data created every day and this pace is not going to decrease in the future. Scientific… Read more: Going Deep with AI and Machine Learning for Science and Engineering, Alina Lazar, Youngstown State University
- Impacting Science and Engineering Applications with Computational Science, Andrew Salinger, Sandia National LabsAbstract: A Computational Scientist comes armed with expertise in algorithms, fluency in software, and intuition for physical processes of scientific/engineering systems. There are tremendous opportunities… Read more: Impacting Science and Engineering Applications with Computational Science, Andrew Salinger, Sandia National Labs