SungYe Kim is a research scientist investigating machine learning and deep learning approaches for real-time rendering as part of the Graphics Research team at Intel. Since she joined Intel in 2012, she has worked on various engineering and research projects in graphics performance analysis and optimization, virtual reality, machine learning, and deep learning, including deep-learning-based super sampling and upscaling. She has a PhD in computer engineering from Purdue University and master's degree in computer science and engineering from Chung-Ang University. Before her studies at Purdue, she worked in graphics research and development at the Electronics and Telecommunications Research Institute in South Korea.
Publications
Temporally Stable Conservative Morphological Anti-Aliasing (TSCMAA)
Realizing Real-Time Deep Learning-Based Super-Resolution Applications on Integrated GPUs
clCaffe: OpenCL™ Standard Accelerated for Caffe* for Convolutional Neural Networks
Read more articles published by SungYe at Google* Scholar.
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