algorithm

Unveiling the potential of energy/entropy stable numerical methods for hyperbolic/mixed hyperbolic-parabolic PDEs

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B9 L2 H1

Abstract The demand for increasingly multidisciplinary reliable simulations, for both analysis and design optimization purposes, requires transformational advances in individual components of future PDEs solvers. At the algorithmic level, hardware compatibility and efficiency are of paramount importance in determining viability on future hardware. However, equally important (if not more so) is provable algorithmic robustness which becomes progressively more challenging to achieve as problem size and physics complexity increase. We show that rigorously designed adaptive semi- and fully-discrete

In collaboration with QCRI, InfoCloud published a paper "Lightning fast and space efficient inequality joins" in VLDB 2015.

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In collaboration with QCRI, InfoCloud published a paper "Lightning fast and space-efficient inequality joins" in VLDB 2015.

Amin Allam (CEMSE PhD) wins the second prize in the DREAM Challenge 1B

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Amin Allam (CEMSE PhD student in the InfoCloud group) supervised by Prof Panos Kalnis has won the second prize in the AstraZeneca-Sanger Drug Combination Prediction DREAM Challenge 1B. Amin Allam utilized Bayesian inference to achieve the 2nd place.

Helping computers to see who we really are

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Algorithms that train computers to automatically detect human activity in videos can improve online searches and real-world surveillance systems.

New Data Mining approach makes recurring patterns easier to be spotted

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The ultimate answer is ScaleMine, cost-effective and agile scalable parallel frequent subgraph mining in a single large graph. Panagiotis Kalnis, Professor of Computer Science (CS), and the team from the KAUST Extreme Computing Research Center (ECRC), under the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division signed this novel approach.

Blind matchmaking for more efficient wireless networks

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Autonomously pairing network users could expand the capability of the next generation of wireless networks

Our work on mining growth phenotype data accepted by Bioinformatics

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​​Congratulates Majed and Hiro on their work on developing a novel constant-column biclustering algorithm for mining co-fit genes from genome-scale growth phenotype data which was accepted by Bioinformatics.

SFB Group graduated its third PhD student - Dr. Ibrahim Alabdulmohsin!

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Congratulates the SFB group on graduating its third Ph.D. student, Dr. Ibrahim Alabdulmohsin.

Algorithm scours datasets to diagnose medical mysteries

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A new tool uses genetic and clinical information to find the root cause of unexplained illnesses.

Dominik L. Michels receives the first Procter & Gamble Faculty Award

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Dominik L. Michels, Computer Science and Mathematics faculty in the Computer, Electrical and Mathematical Science and Engineering Division (CEMSE) and head of the Computational Sciences Group within the Visual Computing Center (VCC), recently received the first Procter & Gamble (P&G) Faculty Award.

Robots learn by checking in on team members

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Innovative drone designs and software enables a team of drones to work together in a coordinated approach.

Beyond self-driving simulations: teaching machines to learn

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Teaching has the power to test the limits of one's knowledge. Teaching algorithms to learn using machine learning is making it possible for cars to do away with human drivers in the near future, but this has also opened up new questions about the limits of our knowledge of the brain and learning. Bernard Ghanem, KAUST associate professor of electrical engineering from the University's Visual Computing Center and principal investigator of the Image and Video Understanding Lab, applies machine learning techniques to computer vision for automated navigation (for example, self-driving cars and

A race against time

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The theme of the University's 2019 Winter Enrichment Program (WEP) was "time." It represented an opportune moment for KAUST to welcome members of the McLaren Group to campus to discuss the recently signed extreme performance research partnership between KAUST and McLaren.

Querying big data just got universal

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A universal query engine for big data that works across computing platforms could accelerate analytics research.

Changing how we predict coral bleaching

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A remote sensing algorithm offers better predictions of Red Sea coral bleaching and can be fine tuned for use in other tropical marine ecosystems.

Teamwork pays off at startup Insyab

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Insyab, a technology startup specializing in smart solutions allowing robots and drones to collaborate on the execution of common tasks, resulted from three years of its founders' dedicated research at KAUST.

An algorithm for success: KAUST-designed differential equation-solving algorithm included in Maple 2020

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A KAUST-designed symbolic algorithm to solve nonlinear ordinary differential equations (ODEs) has been selected for inclusion in the current version of the computer algebra system (CAS) Maple 2020. The global symbolic and numeric computing software system—developed by the Canadian company Waterloo Maple (Maplesoft)—is widely used by scientists, engineers, and researchers to analyze, visualize, and solve mathematical problems.

Training an AI eye on the Moon

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Machine learning accelerates the search for promising Moon sites for energy and mineral resources.

Zhize Li

Research Scientist, Computer Science
Zhize Li is a Research Scientist working with Professor Peter Richtarik in his research group at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Zhize Li received his Ph.D. in Computer Science from the Institute for Interdisciplinary Information Sciences of Tsinghua University in 2019 under the supervision of Prof. Jian Li. On the career side, before joining KAUST, he was a visiting scholar at the Computer Science Department of Duke University (Hosted by Prof. Rong Ge) and a visiting scholar at the Industrial and

Xun Qian

Xun Qian is a Postdoctoral Research Fellow at the Visual Computing Center (VCC), King Abdullah University of Science and Technology (KAUST), working with Professor Peter Richtárik in his research group. Education and Early Career Dr. Qian obtained his B.Sc. degree in Mathematics from Huazhong University of Science and Technology, China, in 2013. In 2017, he has obtained a Ph.D. degree in Mathematics from Hong Kong Baptist University (HKBU), Hong Kong. Research Interest Xun Qian is interested in stochastic methods and algorithms, machine learning and interior-point methods. Selected

Sian-Jheng Lin

Postdoctoral Research Fellow (former), Electrical and Computer Engineering
Postdoctoral Research Fellow, Electrical and Computer Engineering , King Abdullah University of Science and Technology. Project Researcher, University of Science and Technology of China (USTC), PRC.

Hammad Naveed

Postdoctoral Research Fellow, Structural and Functional Bioinformatics
Hammad Naveed worked as a Postdoctoral research fellow at Prof. Xin Gao's Structural and Functional Bioinformatics Group (SFB) at King Abdullah University of Science and Technology (KAUST) during 2013-2015. Hammad is an Associate Professor in the Computer Science Department at the National University of Computer & Emerging Sciences, Pakistan. Previously he was a Research Assistant Professor at the Toyota Technological Institute at Chicago, University of Chicago 2014-2017. Hammad Naveed received his Ph.D. in Bioinformatics from the University of Illinois at Chicago in 2012. He spent the
gustavo soares valentim

Gustavo Soares Valentim

Dissemination Development of a Modular Open Source Power Electronics Didactic Platform L. Koleff et al. 2019 IEEE 15th Brazilian Power Electronics Conference and 5th IEEE Southern Power Electronics Conference (COBEP/SPEC), 2019