Computational Science Research Center
Date of the Event: September 12, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Damian Rouson, Lawrence Berkeley National Laboratory ABSTRACT: The vast majority of parallel programs running on high-performance computing (HPC) platforms leverage parallel programming models often referred to as “MPI+X”, where MPI is the Message-Passing Interface and X typically stands for OpenMP, OpenACC, or CUDA. Over the course of the […]
Date of the Event: September 5, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Scott Mitchell, Sandia National Laboratory, Center for Computing Research ABSTRACT: I’ll describe my family’s colorful journey leading me to Sandia Labs, and what it’s like to work there and with the international research community. I’ll highlight some key technical concepts from triangulations and meshing, and how my work […]
Date of the Event: August 29, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Miguel Dumett, San Diego State University, Computational Science Research Center ABSTRACT: Mimetic differences is a numerical method for constructing schemes that can solve partial differential equations. The method is derived from a high-order approximation of the integration by parts and uses a staggered grid. It offers uniform accuracy over […]
Date of the Event: May 2, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Linda Petzold, UC Santa Barbara, Mechanical Engineering and Computer Science ABSTRACT: Neural networks have the ability to serve as universal function approximators, but they are not interpretable and do not generalize well outside of their training region. Both of these issues are problematic when trying to apply standard neural […]
Date of the Event: April 25, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Nathan Urban, Brookhaven National Laboratory ABSTRACT: As carbon dioxide emissions to the atmosphere continue from fossil fuel consumption, the Earth’s climate will change considerably over the course of this century due to the resulting greenhouse effect. Societies and ecosystems will feel these global changes in the form of extreme […]
Date of the Event: April 18, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Steve Shkoller, University of California, Davis ABSTRACT: We present a novel Computational Shock Development (CSD) algorithm for the 1D Euler equations, based on an Arbitrary Lagrangian-Eulerian mesh-movement scheme, that is designed to capture the fine cusp structures which emerge when sound waves first steepen to form a gradient […]
Date of the Event: April 11, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Poki Chen,National Taiwan University of Science and Technology, Dept. of Electronic and Computer Engineering ABSTRACT: The fine-tuning process of analog integrated circuit design is both time-consuming and labor-intensive. To assist analog IC designers who are new to software development and eager to enhance design efficiency, a simple auto-optimization […]
Date of the Event: March 28, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Michele Bacciocchi, DESID Department, University of San Marino, Republic of San Marino ABSTRACT: The main aim of this research is the development of a finite element code based on the strain gradient theory able to deal with thin laminated plates in the framework provided by Kirchhoff hypotheses. Therefore, […]
Date of the Event: March 14, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Feng Liu, University of California, Irvine, Department of Mechanical and Aerospace Engineering ABSTRACT: Simulation of three-dimensional unsteady reactive flows pose major challenges to computational methods for engineering applications. In this talk, I will present an efficient, accurate, and robust Computational Fluid Dynamics software package for various multi-disciplinary engineering […]
Date of the Event: March 7, 2025
TIME: 3:30 PM LOCATION: GMCS 314 SPEAKER: Siyuan Xing, California Polytechnic State University, San Luis Obispo ABSTRACT: In this talk, we introduce the Combinatorial Operation Neural Network (CombOpNet), a compact neural architecture designed to overcome the curse of dimensionality in Sparse Identification of Nonlinear Dynamics. Within CombOpNet, nonlinear terms in dynamical equations are represented by […]