This event is organized by Prof. Xin Gao, Prof. Panagiotis Kalnis and Prof. Marc Genton (CEMSE) with financial support from the KAUST Office of Sponsored Research (OSR) and additional support provided by the KAUST Industry Collaboration Program (KICP), Industry Partnerships office.
Link to Website: KAUST Research Conference: Computational and Statistic Interface to Big Data
We are now in the fourth paradigm of science: Data Science. The massive amount of structured and unstructured data has posed new challenges and opportunities to the fields of computer science and statistics. Traditional computational and statistical methods for data storage, curation, sharing, querying, updating, visualization, analysis, and privacy have been shown to fail in the big data scenario due to the unprecedented volume, velocity, variety, veracity and value of the big data.
This conference will bring together a number of prominent researchers in Computer Science and Statistics with common interests and active research in big data, as well as the researchers at KAUST who regularly generate or face big data, such as those in bioscience and red sea research. The goal is to exchange ideas and to share their latest research findings in new challenges, methodologies and applications in the context of big data, to promote the big data research at KAUST, to educate KAUST students and postdocs to be the next-generation data scientists, and to encourage active interactions and collaborations amongst participants and KAUST at-large.
- Tony Cai, Professor, University of Pennsylvania, USA.
- Jianqing Fan, Professor, Princeton University, USA.
- Christian Jensen, Professor, Aalborg University, Denmark.
- Hernando Ombao, Professor, KAUST, Saudi Arabia
- Andrey Rzhetsky, Professor, University of Chicago, USA
- Matt Wand, Distinguished Professor, University of Technology Sydney, Australia.
- Wei Zhao, Professor, VPR, American University of Sharjah, UAE
The event is open to the KAUST community.