Krishna is a PhD student in Department of Electrical and Computer Engineering
at Iowa State University. He is working under the supervision of
Professor Arun Somani in Dependable Computing and Networking Laboratory.
He graduated with a Bachelor's degree in Electronics and Communication Engineering
from University College of Engineering, Osmania University, Hyderabad,
India in Summer 2017.
Krishna’s research interests are Machine Learning and Parallel Computer Architecture/Computing.
He primarily works at the intersection of Systems and Deep Learning
which includes designing compressed Neural Network algorithms for efficient
execution on hardware accelerators (TPU like) and general purpose processing devices
(CPU, GPU). He also explores different problems (fault tolerance, memory accesses)
related to DNN hardware. He previously interned at AMD’s MIGraphX
(Deep Learning Graph Optimization team).
Manu is a PhD student in the Computational Media department at
the University of California at Santa Cruz. He is also a part of
the Creative Coding Lab supervised by Professor Angus Forbes.
He received a master of science in computer science from the University
of Illinois at Chicago, where he was a part of the Electronic
Visualization Lab. He has a bachelor in computer science
from the Cochin University of Science and Technology.
Manu's research focuses on real-time graphics and machine learning.
Recent advances have inspired Manu to explore neural network-assisted techniques for ray tracing and global illumination.
In his research, Manu aims to solve various rendering
problems with deep learning solutions optimized for high performance.
Qi is a PhD student in the Visualization and Interface Design Innovation lab
at the University of California Davis, supervised by Professor Kwan Liu Ma.
Prior to this, he received a Master of Science in Computing from the University
of Utah, and a Bachelor of Science in Physics from the Hong Kong
University of Science and Technology.
Qi’s research focuses on real-time graphics through ray tracing, parallel
scientific visualization systems and programmable visualization interfaces.
In the past, his work has contributed to several production visualization
software such as OSPRay, VisIt, VL3. Through his research,
Qi aims to build high performance and fidelity ray tracing system
for scientists with user-friendly interfaces.
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