About Fouzi Harrou Fouzi Harrou Senior Research Scientist, Statistics spatio-temporal statistics Environmental Statistics statistics machine learning Harrou’s research focuses on statistical decision theory and its applications, multivariate statistical process monitoring, anomaly detection and diagnosis. Articles Related News April 2022 Can machine learning help predict disease spread? 1 min read · Sun, Apr 17 2022 News human health machine learning statistics Machine learning techniques can provide accurate forecasting of the spread of viruses during pandemics. Under the supervision of Ying Sun and Fouzi Harrou, Yasminah Alali developed an approach that removes human bias and assumptions, predicting pandemic evolution more accurately. March 2022 SRSI student success story at Ibdaa 2022 2 min read · Sun, Mar 20 2022 Awards News environmental applications data analysis computational methods 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. November 2021 Deeper defense against cyber attacks 1 min read · Sun, Nov 28 2021 News cybersecurity machine learning Deep learning statistics To address the growing threat of cyberattacks on industrial control systems, a KAUST team including Fouzi Harrou, Wu Wang and led by Ying Sun has developed an improved method for detecting malicious intrusions. August 2021 Dr. Harrou receives two IEEE ECBIOS 2021 best paper awards 2 min read · Tue, Aug 10 2021 News renewable energy systems Deep learning Dr. Fouzi Harrou, a research scientist in the KAUST Environmental Statistics (ES) group, recently received two IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability 2021 (IEEE ECBIOS 2021) best paper awards. November 2020 Deep learning in the emergency department 1 min read · Sun, Nov 22 2020 News machine learning artificial intelligence statistics human health Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments. October 2020 KAUST Environmental Statistics group publishes book exploring multivariate statistical analysis 2 min read · Tue, Oct 20 2020 News Deep learning statistics machine learning The KAUST Environmental Statistic (ES) research group has recently published a book titled "Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches." The book is the outcome of the Core Research Grant (GRG) project led by KAUST Professor Ying Sun, Associate Professor of Statistics. January 2017 Keeping antennas at peak performance 1 min read · Sat, Jan 28 2017 News applied mathematics statistics Sensitive detection of partial faults in antenna systems could prevent performance degradation in wireless networks.
Can machine learning help predict disease spread? 1 min read · Sun, Apr 17 2022 News human health machine learning statistics Machine learning techniques can provide accurate forecasting of the spread of viruses during pandemics. Under the supervision of Ying Sun and Fouzi Harrou, Yasminah Alali developed an approach that removes human bias and assumptions, predicting pandemic evolution more accurately.
SRSI student success story at Ibdaa 2022 2 min read · Sun, Mar 20 2022 Awards News environmental applications data analysis computational methods 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.
Deeper defense against cyber attacks 1 min read · Sun, Nov 28 2021 News cybersecurity machine learning Deep learning statistics To address the growing threat of cyberattacks on industrial control systems, a KAUST team including Fouzi Harrou, Wu Wang and led by Ying Sun has developed an improved method for detecting malicious intrusions.
Dr. Harrou receives two IEEE ECBIOS 2021 best paper awards 2 min read · Tue, Aug 10 2021 News renewable energy systems Deep learning Dr. Fouzi Harrou, a research scientist in the KAUST Environmental Statistics (ES) group, recently received two IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability 2021 (IEEE ECBIOS 2021) best paper awards.
Deep learning in the emergency department 1 min read · Sun, Nov 22 2020 News machine learning artificial intelligence statistics human health Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments.
KAUST Environmental Statistics group publishes book exploring multivariate statistical analysis 2 min read · Tue, Oct 20 2020 News Deep learning statistics machine learning The KAUST Environmental Statistic (ES) research group has recently published a book titled "Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches." The book is the outcome of the Core Research Grant (GRG) project led by KAUST Professor Ying Sun, Associate Professor of Statistics.
Keeping antennas at peak performance 1 min read · Sat, Jan 28 2017 News applied mathematics statistics Sensitive detection of partial faults in antenna systems could prevent performance degradation in wireless networks.
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