KAUST Ph.D. student wins best paper award from American Statistical Association
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KAUST Ph.D. student Jian Cao was recently selected as a best paper award winner by the American Statistical Association for his paper entitled 'Computing High-Dimensional Normal and Student-t Probabilities with Tile-Low-Rank Quasi-Monte Carlo and Block Reordering.' Photo by Meres J. Weche.
-By David Murphy, KAUST News
KAUST Ph.D. statistics student Jian Cao was recently selected as a best paper award winner by the American Statistical Association (ASA) for his paper entitled "Computing High-Dimensional Normal and Student-t Probabilities with Tile-Low-Rank Quasi-Monte Carlo and Block Reordering." Cao's paper was chosen in an ASA student paper competition under the section on Statistical Computing.
Cao is a member of Distinguished Professor Marc Genton's Spatio-Temporal Statistics & Data Science research group. He will be officially recognized for his award by the ASA later this year at the association's 2019 Joint Statistical Meetings (JSM) in Denver, Colorado, U.S., from July 27 to August 1.
Tapping into other branches of high performance computing
"[My winning paper] is one self-contained project of my research on estimating high-dimensional multivariate normal and Student-t probabilities, which is one concrete branch of the extensive high performance computing field," Cao stated. "In this topic, I have developed relevant skills for easier tapping into other branches of high performance computing."
Of his award win, he noted, "It is definitely a great honor, especially being the first time I received a recognition of this type. This will encourage me to continue working hard, and in the meantime, it will be a great opportunity to sharpen my presentation skills."
The simple or the impossible
Since joining KAUST in late 2016 from Shanghai Jiao Tong University in China, Cao has pursued a research focus within Genton's group centered on solving statistical problems associated with high-dimensional data using scientific computing methods.
"[At KAUST,] my academic interests are about algebra and high performance computing," he said. "I like digging into algorithms to reduce task complexity."
With his research, Cao sees no limitations in regards to exciting developments or discoveries moving forward.
"Another project that I have in mind is studying one matrix compression scheme and its applications, for which we certainly have exciting expectations," he added. "However, I will try to flatten my heartbeat in case it boils down to something simple—or something simply impossible."