modeling

Houcem Ben Salem

Intern (former), Information Science Lab
Research Intern at KAUST(King Abdullah University of Science and Technology) .

Machine Learning Models for Context Aware Recommendation Systems

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B3 L5 R5209

The goal of this thesis is to pave the way towards the next generation of recommendation systems tackling such real-world challenges to improve the user experience while giving good recommendations.

Eliminating Waiting Time Inequities for Deceased Donor Kidney Transplantation in the USA

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B9 L2 H1 R2322

This research formally models, analyzes and maximizes equity of transplant waiting times and probabilities using queuing theory and network flows, based on Rawls' theory of justice. The presented formal models address inequities resulting from blood type incompatibilities, which are interrelated to ethnic differences in patient and donor rates.

KAUST Ph.D. student Jinhui Xiong wins best paper award

1 min read ·
KAUST computer science Ph.D. student Jinhui Xiong recently won the best paper award at the 24th International Symposium on Vision, Modeling, and Visualization. The symposium took place from September 30 to October 2, 2019, at the University of Rostock, Germany, and provided the opportunity for researchers to discuss a wide range of topics in computer science, including computer graphics, vision, visualization and visual analytics.

Training an AI eye on the Moon

1 min read ·
Machine learning accelerates the search for promising Moon sites for energy and mineral resources.

Viruses as communication molecules

1 min read ·
Electrical and computer engineers take on complex modeling questions that can further our understanding of virus spread in small spaces.

Wildfire simulation heats up

1 min read ·
Computational models capture the capricious behavior of forest fires.

Watching viscous flow, but faster

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A state-of-the-art method for modeling the behavior of liquids described by the Computational Sciences Group represents a breakthrough in computational speed for viscous liquids.

A model for millions of locations

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CEMSE statisticians developed a framework which enables modeling of a range of meteorological and environmental datasets from up to 2 million locations globally.

Ivan Viola

Professor, Computer Science
Professor Viola’s expertise lies in scientific visualization and visual computing. His research focuses on multiscale visualization and modeling of complex biological systems, ranging from cellular organisms to atomistic-level details.