Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.
AaronLefohn

Aaron Lefohn


Director of Graphics Research, NVIDIA
PhD, Computer Science
Thesis title: Interactive Computation and Visualization of Level-Set Surfaces: A Streaming Narrow-Band Algorithm
Advisor: Ross Whitaker

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Aaron Lefohn, SCI alumnus, recently joined NVIDIA as the Director of Real-Time Graphics Research. Aaron Lefohn received his PhD from the University of California, Davis in 2006, studying under John Owens. During his PhD program, he was employed as a researcher and graphics software engineer at Pixar Animation Studios, where he worked on a variety of R&D projects focused on interactive rendering tools for artists. He obtained his MS degree from the University of Utah, studying computer graphics and scientific visualization under Ross Whitaker at the SCI Institute. His research focused on creating the first interactive 3D level-set solver for segmentation of MRI volumetric data sets. He was challenged with figuring out how to solve dynamic, sparse PDEs in parallel on the GPU and directly volume rendering those sparse representations.

In 2006, Aaron joined Neoptica, a startup company creating new graphics programming models on heterogeneous CPU+GPU computer systems such as PlayStation3. When Intel acquired Neoptica in 2007, he led Intel's engagement in OpenCL, working closely with Apple and Khronos to define version 1.0. He then returned to rendering research, leading a small research team focused on new shadow rendering algorithms for the Larrabee graphics processor. In November 2010, he became the research lead for the Advanced Rendering Technology team, a research group focused on new real-time rendering algorithms, power-efficient rendering, and CPU-GPU programming systems for visual computing.

The first product announcement based on the research from Aaron's Intel team was at the Game Developer Conference in March 2013. The announcement was that Intel's latest GPU (Haswell) adds new capabilities that make it possible to deliver practical solutions to several long-standing problems in real-time graphics: order-independent transparency, volumetric shadows, and anti-aliasing of fine detail such as foliage and hair:

Lefohn tumorClip
From Aaron's master's thesis: Interactive level-set segmentation of a brain tumor from a 256 × 256 × 198 MRI with volume rendering to give context to the segmented surface. A clipping plane shows the user the source data, the volume rendering, and the segmentation simultaneously. The segmentation and volume rendering parameters are set by the user probing data values on the clipping plane.
Lefohn greenhouse Lefohn hair Lefohn tree
From "Adaptive Transparency," voted second best paper at High Performance Graphics 2011. This paper introduced a new algorithm for solving order-independent transparency in real-time rendering. The technique was impractical at the time the paper was published, requiring unbounded memory. However, the research led to a new hardware feature in Intel's latest GPU that enables a practical, fixed-memory implementation of the algorithm. The 2013 GRID2 car racing game from CodeMasters used a derivative of the algorithm to render anti-aliased foliage and self-shadowing smoke.