About Jian Cao Jian Cao Ph.D., Statistics data science spatio-temporal statistics statistics Jian Cao obtained his Ph.D. degree in Statistics from King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Marc Genton at the "spatio-temporal statistics and data science" research group. His research focused on Monte Carlo simulation, hierarchical matrices, tile-low-rank matrices, and solving high dimensional multivariate normal or Student-t probabilities. Education and Early Career Ph.D. degree from King Abdullah University of Science and Technology Master from Shanghai Jiaotong University Bachelor from University of Science and Technology of China Articles Related News April 2023 KAUST STAT Program graduates secure faculty positions at prominent U.S. universities 7 min read · Wed, Apr 19 2023 News KAUST graduates are characterized by the rigor of their Ph.D. programs, the long hours spent in the lab and classroom, juggling professional and personal commitments, achieving a work-life balance and, more recently, the ability to adapt to a global pandemic. April 2021 Introducing "THE FANTASTATISTICS 4" 1 min read · Thu, Apr 15 2021 News Introducing KAUST’s very own "THE FANTASTATISTICS 4." Gaurav Agarwal, Jian Cao, Wanfang Chen, and Yuxiao Li are four Ph.D. alumni from the Statistics program at KAUST. The four students obtained their Ph.D.s last year under the supervision of Professor Ying Sun, Agarwal and Li, and Distinguished Professor Marc Genton, Cao and Chen, respectively. January 2021 CEMSE Student Research Excellence Awards and Student Academic Accomplishment Awards winners announced 2 min read · Tue, Jan 5 2021 News Spotlight student research excellence awards The annual CEMSE Student Research Excellence Awards and Student Academic Accomplishment Awards celebrate the talent and achievements of the Division's students. Awarded around the KAUST Commencement ceremony, the awards are presented in recognition of the academic accomplishments and research impact created by our leading students in the fields of Applied Mathematics and Computer Science (AMCS), Computer Science (CS), Electrical and Computer Engineering (ECE), and Statistics (STAT). December 2020 KAUST STAT students come together for second ASA chapter meeting 2 min read · Thu, Dec 3 2020 News statistics data science Members of the KAUST American Statistical Association (ASA) student chapter recently came together for the group’s second online meeting held on Tuesday, November 10, 2020. The meeting served as an orientation exercise for new KAUST Statistics (STAT) Program students while also highlighting the shared experience of STAT Ph.D. candidates: Jian Cao, Wanfang Chen, Yuxiao Li, and Gaurav Agarwal. April 2019 KAUST Ph.D. student wins best paper award from American Statistical Association 1 min read · Thu, Apr 25 2019 Awards News Spotlight Statistical computing High Performance Computing 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. October 2018 Reining in computational complexity 1 min read · Tue, Oct 2 2018 News statistics extreme weather A more efficient approach to modeling spatial data involving thousands of variables keeps computation time in check.
KAUST STAT Program graduates secure faculty positions at prominent U.S. universities 7 min read · Wed, Apr 19 2023 News KAUST graduates are characterized by the rigor of their Ph.D. programs, the long hours spent in the lab and classroom, juggling professional and personal commitments, achieving a work-life balance and, more recently, the ability to adapt to a global pandemic.
Introducing "THE FANTASTATISTICS 4" 1 min read · Thu, Apr 15 2021 News Introducing KAUST’s very own "THE FANTASTATISTICS 4." Gaurav Agarwal, Jian Cao, Wanfang Chen, and Yuxiao Li are four Ph.D. alumni from the Statistics program at KAUST. The four students obtained their Ph.D.s last year under the supervision of Professor Ying Sun, Agarwal and Li, and Distinguished Professor Marc Genton, Cao and Chen, respectively.
CEMSE Student Research Excellence Awards and Student Academic Accomplishment Awards winners announced 2 min read · Tue, Jan 5 2021 News Spotlight student research excellence awards The annual CEMSE Student Research Excellence Awards and Student Academic Accomplishment Awards celebrate the talent and achievements of the Division's students. Awarded around the KAUST Commencement ceremony, the awards are presented in recognition of the academic accomplishments and research impact created by our leading students in the fields of Applied Mathematics and Computer Science (AMCS), Computer Science (CS), Electrical and Computer Engineering (ECE), and Statistics (STAT).
KAUST STAT students come together for second ASA chapter meeting 2 min read · Thu, Dec 3 2020 News statistics data science Members of the KAUST American Statistical Association (ASA) student chapter recently came together for the group’s second online meeting held on Tuesday, November 10, 2020. The meeting served as an orientation exercise for new KAUST Statistics (STAT) Program students while also highlighting the shared experience of STAT Ph.D. candidates: Jian Cao, Wanfang Chen, Yuxiao Li, and Gaurav Agarwal.
KAUST Ph.D. student wins best paper award from American Statistical Association 1 min read · Thu, Apr 25 2019 Awards News Spotlight Statistical computing High Performance Computing 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.
Reining in computational complexity 1 min read · Tue, Oct 2 2018 News statistics extreme weather A more efficient approach to modeling spatial data involving thousands of variables keeps computation time in check.
Engage ORCID ShareClipboard Related Sites Statistics (STAT) Spatio-Temporal Statistics and Data Science (STSDS) Related Content Articles 6 Events 1 Related Links View publication list on KAUST Repository Also view list of Publications on ORCID
