I am currently a software engineer at Google. Before this, I was a software engineer at C3.ai, which is software company that provides an artificial intelligence and machine learning platform for enterprises. I was a software engineer at the Intel Corporation working for the technology and manufacturing group at Hillsboro, OR. I was a postdoctoral researcher in the Scientific Computing and Imaging (SCI) institute in the University of Utah. I graduated with a Ph.D. at The Pennsylvania State University in the Department of Computer Science and Engineering in August, 2012. I completed my undergraduation in mechanical engineering at the Indian Institute of Technology Madras (IIT Madras) in Chennai, India in July 2007.

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Shankar Prasad Sastry

Overview of my Research Area

Simulation science is usually driven by the solution to partial differential equations (PDEs) using the finite element (FE) method. A computational pipeline that facilitates computer-aided engineering (CAE) typically involves following stages: geometric modeling, mesh generation, numerical simulation, error analysis, mesh adaptation, and visualization. My research has focused on numeric and geometric aspects of scientific and high performance computing in most of the stages of the pipeline (see the figure below). As the first step in CAE, geometric models are obtained from specialized software, image data, or other sources. These models are discretized to construct surface and volume meshes to solve discretized forms of PDEs. High-quality meshes are necessary for the stability and efficiency of an FE solver and the accuracy of the associated PDE solution. In order to obtain high-quality meshes, the quality of its elements is optimized using numerical techniques. Analysis of error in numerical simulations and the subsequent adaptation of meshes (refinement, warping, optimization, etc.) yield accurate solutions that may be visualized to aid engineering design.

The Pipeline

My research has focused on numeric and geometric aspects 
of scientific and high performance computing in most of the stages of the

My Projects

Specifically, I have worked on geometric modeling and visualization of geological structures with applications to oil exploration, meshing techniques (generation, optimization, and adaptation) with applications to patient-specific treatment, numerical analysis to determine error bounds in the FE method, and data reordering techniques to improve cache utilization. As parts of the projects above, I have also worked on numerical optimization and graph theoretic approaches to improve the performance of preconditioned linear solvers. Browse this website for more information about my projects and links to my research papers.