Xiangliang Zhang, KAUST associate professor of computer science and principal investigator of the Machine Intelligence & Knowledge Engineering Lab, joined the Computational Bioscience Research Center (CBRC) on July 1, 2018. In CBRC, Xiangliang will work on the problems of modeling biological networks using machine learning models.
Women in Data Science (WiDS) is like the Global Women's March for analytics; it's a phenomenon too big for just one city. WiDS is the largest data science conference on Earth—taking place in over 50 countries, it has attained more than 100,000 attendees and is tagged as a global movement.
The annual conference aims to inspire and educate data scientists worldwide—regardless of gender—and support women in the field. This year's WiDS conference was held at Stanford University with more than 100 regional institutions all over the world participating, including KAUST.
Mapping genetic influences on connections between neural networks could lead to a better understanding of brain organization and behavior.
The recent KAUST Research Conference: Computational and Statistical Interface to Big Data brought together leading computer science researchers and statistical experts to discuss the current state and future of data science. Held on campus from March 19 to 21, the conference covered such data science topics as succinct data representation and storage; big data visualization; parallel and distributed algorithms for inference and optimization; and analysis of large graphs and networks.
Color changes in the northern Red Sea indicate rising sea temperatures could significantly impact tropical marine ecosystems.
A new malaria metabolic model may uncover better ways to treat a highly deadly disease.
KAUST second year Ph.D. student Yuxiao Li has been selected to receive a Student Paper Award from the American Statistical Association (ASA) for his paper entitled "Efficient Estimation of Non-stationary Spatial Covariance Functions with Application to High-resolution Climate Model Emulation."
KAUST second year Ph.D. student Yuxiao Li has been selected to receive a Student Paper Award from the American Statistical Association (ASA) for his paper entitled "Efficient Estimation of Non-stationary Spatial Covariance Functions with Application to High-resolution Climate Model Emulation."
A risk-based optimization scheme boosts confidence and profitability for future mixed-technology power plants.
KAUST Ph.D. alumna Sabrina Vettori and Ph.D. student Yuxiao Li have been selected by the Eastern North American Region (ENAR) of the International Biometric Society to receive a Distinguished Student Paper Award at the 2018 ENAR Spring Meeting.
KAUST Ph.D. student Yuxiao Li has been selected by the Eastern North American Region (ENAR) of the International Biometric Society to receive a Distinguished Student Paper Award at the 2018 ENAR Spring Meeting.
Faster computations will allow researchers to see the finer details of brain activity in functional brain imaging.
Married couple Wanfang Chen and Yuxiao Li came to KAUST in August 2016 to pursue their Ph.D. studies in the field of statistics. Both students are based in the University's Computer, Electrical and Mathematical Science & Engineering division—Chen under the supervision of Distinguished Professor Marc Genton and Li under the supervision of Professor Ying Sun.
More accurate statistical modeling of extreme weather will improve forecasting and disaster mitigation.
A technique that uses the power of computing could solve statistical problems cheaper and faster than current methods.