This event is a part of the "Strategies for Working Remotely" panel series, produced by the IDEAS Productivity Project. This online panel session addresses challenges in working remotely, with emphasis on issues faced by collaborating teams in computational research.
|Panel Title||Year in Review: What Have We Learned So Far?|
|Date and Time||Thursday 2020-12-17 3:00pm-4:00pm EST|
|Panelists||Lori Diachin (Exascale Computing Project and Lawrence Livermore National Laboratory), Thomas Evans (Oak Ridge National Laboratory), and Elaine Raybourn (Sandia National Laboratories)|
|Moderators||Ashley Barker (Oak Ridge National Laboratory)|
|Series Information and Archives||
Panels are free and open to the public. Advance registration is required through the Event website. Archives (recording, slides) will be posted at the same link soon after the event.
Earlier this year many workers abruptly transitioned from a primarily on-site to a primarily remote work experience due to a global pandemic. As we bring 2020 to a close, what have we learned so far, and what do we have yet to learn about working remotely, and working effectively in hybrid configurations? In this fireside chat, we look at key highlights from each of the Strategies for Working Remotely panel discussions in the series and dig deeper. What has worked, why, and where can we improve? What do we have yet to learn, or unlearn? “Ask me anything” questions can be submitted by the audience in advance to email@example.com.
Lori Diachin joined the Exascale Computing Project as the Deputy Director, Lori had been serving as the Deputy Associate Director for Science and Technology in the Computation Directorate at Lawrence Livermore National Laboratory (LLNL) since 2017. The Computation Directorate has approximately 1000 staff serving the needs of the laboratory in areas ranging from high performance computing, computing sciences for the missions of LLNL, and information technology for business and workforce enablement. As Computation DAD for S&T, Lori serves as a senior-level advisor to the Computation Associate Director (AD) and to division leaders and institute directors on strategies to develop and sustain critical computer and computational capabilities. She is also the Program director for the HPC4Manufacturing and HPC4Materials programs in the DOE EERE and FE program offices. She has been involved with DOE’s SciDAC program since its inception and currently serves as the FASTMath institute director; leading a team of over 50 researchers from 10 different organizations. Lori served for 6 years as the Director for the Center for Applied Scientific Computing (CASC) and 2 years as the Acting Information Technology Department head. CASC houses approximately 125 applied mathematicians, computer scientists, and data scientists who conduct world class, collaborative scientific research and development on problems critical to national security. The Center’s core competencies include high performance computing, computational physics, numerical mathematics, computer science, and data science. Lori has over 20 years experience in applied mathematics research where her areas of expertise include mesh quality improvement, mesh component software, numerical methods, and parallel computing. Before joining LLNL, Lori was a computer scientist at Argonne National Laboratory and a Member of the Technical Staff at Sandia National Laboratories. Lori received her Bachelors degree in Mathematics from Edinboro University of Pennsylvania in 1988 and her Ph.D. in Applied Mathematics from University of Virginia in 1992.
Tom Evans specializes in the development, implementation, and application of computational radiation transport as applied in the areas of Nuclear Engineering, radiation detection, astrophysics, high energy density physics, and medical applications. His interests include stochastic and deterministic transport methods on massively parallel platforms, nonlinear and time-dependent transport methods, coupled physics including radiation-hydrodynamics and core-reactor physics, acceleration and preconditioning techniques, optimization and performance analysis, and large-scale scientific software design for parallel codes. He leads work at ORNL on energy applications in ECP. He is working remotely during a pandemic in a house with a high school senior, college senior, and fellow scientist/manager/wife Kate.
Elaine Raybourn is a social scientist in the Statistics and Human Systems Group (Applied Cognitive Science) at Sandia National Laboratories. Her research focuses on virtual teams, software developer productivity, scientific visualization, and transmedia learning. She has worked remotely for a combined total of 14 years while at Sandia National Laboratories: from the UK as a guest researcher at British Telecom; Germany (Fraunhofer FIT) and France (INRIA) as a Fellow of the European Research Consortium in Informatics and Mathematics (ERCIM), and most recently from Orlando, Florida as Sandia’s Institutional PI for the IDEAS-ECP productivity project. She leads PSIP and the panel series Strategies for Working Remotely.
Ashley Barker is the Group Leader for the User Assistance and Outreach (UAO) team at the Oak Ridge Leadership Computing Facility (OLCF) located at Oak Ridge National Lab (ORNL). UAO is responsible for facilitating access to OLCF resources, providing training, documentation, and technical support to users, collecting and reporting on user facility data, and acquainting the public with the work conducted at the OLCF through scientific highlights. The OLCF supports more than 1,200 users and 250 projects annually from a wide spectrum of science domains. Ashley served as the National Climate Research Center (NCRC) Project Director from 2014-2016. The NCRC project represents a partnership between NOAA and DOE and through this partnership, the NCRC team has delivered multiple computer systems to NOAA, allowing the agency to advance its climate modeling and improve our understanding of climate variability and change. Ashley is also currently involved in the Exascale Computing Project (ECP) as the Control Account Manager (CAM) for training and productivity.