Freda Shi, PhD candidate
Toyota Technological Institute at Chicago
Ananya Kumar, PhD candidate
Department of Computer Science, Stanford University
Stephanie Wang, PhD candidate
University of California, Berkeley
Scaling applications with distributed execution has become the norm. With the rise of big data and machine learning, more and more developers must build applications that involve complex and data-intensive distributed processing.
Xuejun Du, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jian Zhao
Saikat Dutta, PhD candidate
Department of Computer Science, University of Illinois Urbana-Champaign
Abhibhav Garg, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Rafael Oliveira
Yongqiang (Victor) Tian, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Chengnian Sun
David Radke, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Kate Larson, Tim Brecht
Shlomi Steinberg, PhD candidate
University of California, Santa Barbara
Rendering and path-tracing techniques power most of the complex computer-generated content we see in films and movies, visualizations and even video games. However, these techniques are strictly confined to ray optics, while many applications often require simulating the interference and diffraction phenomena, that arise from the wave nature of light.
Aarti Malhotra, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jesse Hoey