computational methods

Spatial Dataflow is all you need!

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B9 L2 R2325

Jian Weng's research, inspired by spatial dataflow, proposes a unified hardware design and implementation framework that leverages a familiar software programming paradigm, enabling concise and efficient designs while significantly reducing code complexity and achieving near-handcrafted performance, with future applications in ML inference systems targeting memory bandwidth limitations.

Peter Schmid

​Professor Schmid's research interests are in theoretical and computational fluid dynamics, with emphasis on hydrodynamic stability theory, flow control, model reduction and system identification. He is also interested in computational techniques for flow optimization and quantitative flow analysis.

CEMSE Welcomes new Professor: Dr. Ying Sun

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Ying Sun is an Assistant Professor of Statistics in the Division of Computer, Electrical and Mathematical Sciences and Engineering (CEMSE). She joined KAUST after one-year service as an assistant professor in the Department of Statistics at the Ohio State University.

Student life: studying and working at the Computational Bioscience Research Center (KAUST)

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For Ph.D. students Arturo Magana Mora, Haitham Ashoor and Olaa Motwalli, April 2017 was a particularly nerve-wracking month. After years of hard work and sleepless nights, they finally defended their thesis, bringing them one step closer to graduation.

The awesome scope of big data

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Sifting through huge amounts of data may bring a better understanding of whale shark social structures, protein targets for drug therapies and disease-causing genes.

Professor Sun receives the Environment Early Investigator Award 2017 for her outstanding contribution in environmental statistics

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Ying Sun, Professor of Statistics in the Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE) of the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, has been awarded the 2017 Early Investigator Award by the American Statistical Association’s Section on Statistics and the Environment (ENVR).

Sarah Alghamdi defends her master's thesis

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Sarah Alghamdi successfully defended her master's thesis on April 10, 2018. Her project, entitled "Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Ageing and Longevity in Inbred Mouse Strains", was well-received by a panel of professors that included Professor Vladimir Bajic, Associate Professor Xin Gao and Assistant Professor Robert Hoehndorf.

Arwa Bin Raies defends her thesis proposal

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Arwa Bin Raies, a Ph.D. candidate under the supervision of Professor Vladimir Bajic, defended her thesis proposal on May 14, 2018.

Using Statistical Models to Solve Environmental Problems

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Joining the faculty of King Abdullah University of Science and Technology (KAUST) six years ago gave statistics Professor Ying Sun a unique career opportunity: the chance to build and lead her own research group solving real-world problems.

SRSI student success story at Ibdaa 2022

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Faisal Fadi Hasan Almulla, who worked last year under the mentorship of Dr. Fouzi Harrou and Professor Ying Sun as part of the annual KAUST Saudi Research Science Institute (SRSI) summer program, won two awards at the National Olympiad for Scientific Creativity — Ibdaa 2022.

Rawan Olayan

Rawan Olayan obtained both, her MS Degree and PhD Degree from Computer Science at KAUST in 2013 and 2018 respectively. Her master thesis and PhD thesis supervisor was Vladimir Bajic. Under the supervision of her advisor Professor Vladimir Bajic, she completed her thesis on developing novel computational methods to predict drug-target interactions and their functional effects using data integration, graph mining and machine learning approaches. Currently, Rawan is working as a postdoctoral associate in the Carter Lab at the Jackson Laboratory for Genomic Medicine in Farmington, Connecticut. In

Olaa A. Motwalli

Research Interests Olaa Motwalli is a Ph.D. student in Computational Science and a member of the Computational Bioscience Research Center (CBRC) at KAUST. She obtained her Bachelor's degree in Computer Science at King Abdul Aziz University in Jeddah and obtained her Master's degree in Computer and Software Engineering at Widener University in the USA. Her research interests are mainly the development and computational support for the design of sustainable biofuel production via microbial cell factories through machine learning, graph mining, and algorithm development, genome-scale metabolic

Haitham M. Ashoor

Research Interests Haitham Ashoor is a Ph.D. candidate in the Computer Science program at King Abdullah University of Science and Technology (KAUST). He is working under the supervision of Prof. Vladimir Bajic. He has obtained his BSc degree in Computer Engineering from the University of Jordan, Amman Jordan in 2008. He joined KAUST as an MSc student in 2009. In 2011, He finished his master studies under the supervision of Prof. Vladimir Bajic. His main research interests are developing computational methods for next-generation sequencing data analysis and applications of machine learning in