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<> statistics (45)
Juan Jose Galeano Arenas

Juan José Galeano Arenas

Ph.D. Student, Statistics
Juan José Galeano Arenas is a MS/PhD student at the King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Håvard Rue in his research group.

Vecchia Approximations of Gaussian Processes on GPUs for Scalable Spatial Modeling and Computer Model Emulation

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B5 L5 R5209

This thesis advances the computational efficiency of Vecchia approximation methods for Gaussian Processes (GPs), emphasizing GPU-based implementations for large-scale geospatial analysis and computer emulation. Traditional GPs require expensive covariance matrix inversions, which this work overcomes using scalable Vecchia-based approximations without sacrificing accuracy.

Collective Estimation of Multiple Bivariate Density Functions with Application to Angular-sampling-based Protein Structure Prediction

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B1

In this talk we develop a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs. Each log density function in the collection is modeled as a linear combination of a common set of basis functions. The shared basis functions are modeled as bivariate splines on triangulations and are estimated using data. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles.

Disease Risk Estimation by Combining Case-Control Data with Aggregated Information on the Population at Risk

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B1 L4 R4102

We propose a novel statistical framework by supplementing case–control data with summary statistics on the population at risk for a subset of risk factors. Our approach is to first form two unbiased estimating equations, one based on the case–control data and the other on both the case data and the summary statistics, and then optimally combine them to derive another estimating equation to be used for the estimation.

Brain waves in boxes

1 min read ·
A statistical method helps to identify abnormal signals in electroencephalograms and locate their source in the brain.

2015 Workshop on Computational Space-Time Statistics

1 min read ·
Organizers : Prof. Marc G. Genton , Chair of Spatio-Temporal Statistics and Data Science Group Prof. Raphael Huser, Chair of Extreme Statistics Group​ Prof. Ying Sun​, Chair of Environmental Statistics Group Confirmed speakers: Prof. Sudipto Banerjee, University of California Los Angeles, USA Prof. Souhaib Ben Taieb, Monash University, Australia Prof. Stefano Castruccio, Newcastle University, UK Prof. Miguel de Carvalho, Pontificia Universidad Catolica de Chile,​ Chile Prof. Clément Dombry, University of Franche-Comté , France Prof. Xuming He, University of Michigan, USA Prof. Hsin-Cheng Huang

A clearer view of rainfall patterns

1 min read ·
Improved random modeling allows scientists to generate realistic patterns of high-frequency rainfall.

2016 Workshop Statistics for High-Dimensional & Complex Data

1 min read ·
Workshop on Statistics for High-Dimensional and Complex Data, Nov. 6-9, 2016​ Organizers : Prof. Marc G. Genton, Chair of Spatio-Temporal Statistics and Data Science Group Prof. Raphael Huser, Chair of Extreme Statistics Group​ Prof. Ying Sun​, Chair of Environmental Statistics Group Confirmed speakers: Prof. David Bolin, Chalmers University of Technology, Sweden Prof. Probal Chaudhuri, Indian Statistical Institute, India Prof. Dan Cooley, Colorado State University, USA​ Prof. Subhajit Dutta, IIT Kanpur, India Prof. Amanda Hering, Baylor University, USA Dr. Anna Kiriliouk, Université

Getting the jump on industrial failures

1 min read ·
A statistics-driven method for the early detection of emerging problems in industrial processes could improve industrial safety, reliability and productivity.

Keeping antennas at peak performance

1 min read ·
Sensitive detection of partial faults in antenna systems could prevent performance degradation in wireless networks.

A safe sweep of weather data

1 min read ·
A statistical technique for automatically cleaning erroneous data from weather-balloon observations will improve the accuracy of weather forecasting.

Smart healthcare uses stats to spot a stumble

1 min read ·
Statistical monitoring technology can detect serious falls and immediately warn healthcare providers.

Professor Sun receives the Environment Early Investigator Award 2017

1 min read ·
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).

Assistant Professor Ying Sun wins American Statistical Association award

1 min read ·
​​​​Ying Sun, KAUST assistant professor of applied ​mathematics and computational science​, won the 2017 Section on Statistics and the Environment (ENVR) Early Investigator Award from the American Statistical Association (ASA). Sun received her award at the 2017 Joint Statistical Meetings (JSM), held from July 29 to August 3 in Baltimore, Maryland, U.S. Sun's award recognizes her important contributions to the field of environmental statistics that help to address major problems like climate change and environmental pollution. At KAUST, Sun leads the Environmental Statistics Group in the

Dataset size counts for better predictions

1 min read ·
A statistical technique for modeling large datasets improves interpretation of climate and environmental data.

2017 Workshop Modern Statistics for Complex Data Structures

1 min read ·
2017 Workshop Modern Statistics for Complex Data Structures

One bad apple can spoil a robot swarm

1 min read ·
Coordinated robot swarms can achieve amazing feats, but even a single faulty unit can have serious consequences.

Ph.D. Student Gaurav Agarwal received an Honorable Mention from ENVR Student Paper Competition

1 min read ·
Ph.D. student Gaurav Agarwal received an Honorable Mention from ENVR student paper competition for his paper entitled "Quantile function modeling with application to salinity tolerance analysis in plant data."

Revealing hidden relationships in data

1 min read ·
A method to visualize hidden statistical structure helps make sense of environmental data.

Making data more accessible

1 min read ·
Ying Sun is a multi-award-winning statistician who is inspired by the value of statistics in solving real-world problems.

Ph.D. Student Yuxiao Li won the ENAR Distinguished Student Paper Award

1 min read ·
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.

Second year Ph.D. student to receive top statistics award

1 min read ·
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."

Ph.D. Student Yuxiao Li won the ENVR student paper award

1 min read ·
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."

New stats apps show a virtual reality

1 min read ·
Harnessing the power of virtual reality will help to visualize data and improve statistical models.

Postdoc Carolina Euan received Sylvia Esterby Presentation Award from TIES

1 min read ·
Carolina Euán, a postdoctoral fellow in KAUST Associate Professor Ying Sun's Environmental Statistics research group, recently received the Sylvia Esterby Presentation Award from the International Environmentrics Society (TIES) at the 28th Annual TIES Conference 2018 held from July 16 to 21, 2018, in Guanajuato, Mexico. Euán won the award for her talk entitled "Bernoulli Vector Autoregressive Model with Applications to Spatio-temporal Drought Events in Mexico."

Clustering helps unlock secrets of the human brain

1 min read ·
The latest statistical methods from research on complex high-dimensional environmental data also yield powerful tools for interpreting brain activity.

Taking aim at outliers

1 min read ·
Automatic detection of uncharacteristic data sequences could change the way data is processed and analyzed.

Honing in on hotspots in spatial data

1 min read ·
More accurate detection of hotspot clusters provides new insights into the behavior of air pollution.

3 Faculty Positions in Statistics 2020 at KAUST

1 min read ·
The 3 faculty positions are in the Statistics Program (http://stat.kaust.edu.sa) within the Computer, Electrical, and Mathematical Sciences and Engineering Division. Currently, the Statistics Program has 7 core faculty and 10 affiliated faculty. We are primarily interested in applicants with strong background in one of the following areas: (1) Statistical Data Science and AI, including network data analysis and high-dimensional statistics (https://apply.interfolio.com/69165); (2) Statistical Climatology, with expertise in statistical analysis of climate model output data, in particular regional climate models, and in physical systems (https://apply.interfolio.com/69167); (3) Statistics for Public Health, including smart health data analysis, personalized medicine, and disease mapping (https://apply.interfolio.com/69168).

2019 Statistics and Data Science Workshop

1 min read ·
From November 18 to 20 the KAUST CEMSE Division has hosted the 2019 Statistics and Data Science Workshop. The workshop, organized by Workshop Chair Professor Ying Sun from the KAUST Environmental Statistics Group, featured 17 keynote talks from eminent data science researchers from Asia, Europe, North America and on-campus. Talks included: personalized recommendation by learning from heterogeneous graph data; dynamic spatial panel models; networks, common shocks, and sequential exogeneity; unbiased Markov chain Monte Carlo, plus many more.

Testing barley's salt tolerance is a numbers game

1 min read ·
Factors influencing the tolerance of barley to saline soils have been uncovered using an advanced robust statistical technique.

Pop stats for big geodata

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A universal high-performance computing interface allows popular statistical tools to run efficiently on large geospatial datasets.

KAUST Environmental Statistics group publishes book exploring multivariate statistical analysis

1 min read ·
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.

Today we celebrate World Statistics Day!

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Let’s discover the world of the statisticians at KAUST and be ready to be amazed by their cutting-edge research!

Deep learning in the emergency department

1 min read ·
Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments.

KAUST STAT students come together for second ASA chapter meeting

1 min read ·
Members of the KAUST American Statistical Association (ASA) student chapter recently came together for the group’s second online meeting held on Tuesday, November 10, 2020. The meeting served as an orientation exercise for new KAUST Statistics (STAT) Program students while also highlighting the shared experience of STAT Ph.D. candidates: Jian Cao, Wanfang Chen, Yuxiao Li, and Gaurav Agarwal.

Modeling rainfall drop by drop

1 min read ·
A high-frequency model developed using data from new high-precision rain gauges gives fresh insight into the dynamics of rain and runoff events.

Mixing precision for model acceleration

1 min read ·
A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.

Trio of tuning tools for modeling large spatial datasets

1 min read ·
Statistical tools help fine-tune the parameters and approximations of models used to make sense of large spatial datasets.

Deeper defense against cyber attacks

1 min read ·
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.

Can machine learning help predict disease spread?

1 min read ·
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.

Yuxiao Li

Ph.D., Statistics
Yuxiao Li obtained his Ph.D. degree in Statistics from King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Ying Sun in the Environmental Statistics group. Education and Early Career: Yuxiao obtained his Bachelor of Science degree in Mathematics in 2013 from Beijing Institute of Technology, Beijing, China. In 2015, he graduated with his Master of Science degree in Statistics from the University of California at Irvine, USA. Then, he joined the Ph.D. program in Statistics at KAUST. Research Interest: His research interests lie in the fields such as

Qilong Pan

Ph.D. Student, Statistics
Qilong Pan's research focuses on developing scalable statistical methods, with a particular emphasis on Gaussian Processes and GPU acceleration.

Jose Hermenegildo Ramirez Gonzalez

Postdoctoral Research Fellow, Statistics

Fouzi Harrou

Senior Research Scientist, Statistics
Harrou’s research focuses on statistical decision theory and its applications, multivariate statistical process monitoring, anomaly detection and diagnosis.
<> Environmental Statistics (28)

Professor Ying Sun elected as a Fellow of the American Statistical Association

3 min read ·
Ying Sun joins the elite ranks of ASA Fellows in 2025 for her contributions to spatial statistics, mentoring and global outreach.

Workshop on Computational Space-Time Statistics

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B1 L4 R4102

Workshop on Computational Space-Time Statistics

Uncertainty Quantification of Tsunami Models

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B1

In this talk, we first show various strategies for the efficient emulation of simulators having uncertain inputs, with applications to tsunami wave modelling. A fast surrogate of the simulator's time series of outputs is provided by the outer product emulator.

Workshop on Statistical Process Monitoring and Risk Assessment for Engineering and Spatial Environmental Applications

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B1 L4 R4102

LIST OF SPEAKERS KAUST Environmental Statistics Group, CEMSE Division - Ying Sun (ying.sun@kaust.edu.sa), PI - Fouzi Harrou (fouzi.harrou@kaust.edu.sa), Postdoc - Huang Huang (huang.huang@kaust.edu.sa), PhD Student - Tianbo Chen (tianbo.chen@kaust.edu.sa), PhD Student - Rui Meng (rui.meng@kaust.edu.sa), Master Student - Sulaiman Binkhamis (sulaiman.binkhamis@kaust.edu.sa), Master Student Hydrology and Land Observation Group, BESE Division - Gaohong Yin (gaohong.yin@kaust.edu.sa), Master Student Collaborators - NorEddine Ghaffour (noreddine.ghaffour@kaust.edu.sa), co-I, WDRC - Matthew McCabe

Heteroscedastic BART Using Multiplicative Regression Trees

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B1 L4 R4102

Bayesian additive regression trees (BART) has become increasingly popular as a flexible and scalable non-parametric model useful in many modern applied statistics regression problems. It brings many advantages to the practitioner dealing with large and complex non-linear response surfaces, such as a matrix-free formulation and the lack of a requirement to specify a regression basis a priori.

Computational Methods for Large Spatio-temporal Datasets and Functional Data Ranking

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B1 L4 R4102

In this thesis defense, I will talk about two topics—computational methods for large spatial datasets and functional data ranking. Both are tackling the challenges of big and high-dimensional data.

Professor Sun receives the Environment Early Investigator Award 2017

1 min read ·
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).

Ph.D. Student Gaurav Agarwal received an Honorable Mention from ENVR Student Paper Competition

1 min read ·
Ph.D. student Gaurav Agarwal received an Honorable Mention from ENVR student paper competition for his paper entitled "Quantile function modeling with application to salinity tolerance analysis in plant data."

Students shine on the statistics stage

1 min read ·
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.

Second year Ph.D. student to receive top statistics award

1 min read ·
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."

Taking aim at outliers

1 min read ·
Automatic detection of uncharacteristic data sequences could change the way data is processed and analyzed.

Statistics plot pollution to inform policy

1 min read ·
The spatial variation in different air pollution components helps identify possible targets for pollution control.

Honing in on hotspots in spatial data

1 min read ·
More accurate detection of hotspot clusters provides new insights into the behavior of air pollution.

KAUST Ph.D. student receives environmetrics best poster award

1 min read ·
Ghulam Qadir, a third-year Ph.D. student in KAUST Associate Professor Ying Sun's Environmental Statistics research group, recently received a best poster award from the Italian Environmetrics Society (GRASPA) and the International Environmetrics Society (TIES) at the GRASPA 2019 conference held from July 15 to 16 in Pescara, Italy.

CEMSE Division student spotlight: Gaurav Agarwal

1 min read ·
Gaurav Agarwal firmly believes in the age-old adage that patience is a virtue. Without patience, life’s challenges cannot be overcome, and a steadfast belief in perseverance has served the statistics Ph.D. student well throughout his academic career.

Meet KAUST prospective student: Cristian Felipe Jiménez Varón

1 min read ·
Cristian Felipe Jiménez Varón is an applied mathematics graduate who will join KAUST from the Universidad Nacional de Colombia Sede Manizales (UNAL), Colombia. He also holds dual bachelor's degrees in industrial engineering and chemical engineering fromUNAL .

Modeling rainfall drop by drop

1 min read ·
A high-frequency model developed using data from new high-precision rain gauges gives fresh insight into the dynamics of rain and runoff events.

Trio of tuning tools for modeling large spatial datasets

1 min read ·
Statistical tools help fine-tune the parameters and approximations of models used to make sense of large spatial datasets.

Yuxiao Li

Ph.D., Statistics
Yuxiao Li obtained his Ph.D. degree in Statistics from King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Ying Sun in the Environmental Statistics group. Education and Early Career: Yuxiao obtained his Bachelor of Science degree in Mathematics in 2013 from Beijing Institute of Technology, Beijing, China. In 2015, he graduated with his Master of Science degree in Statistics from the University of California at Irvine, USA. Then, he joined the Ph.D. program in Statistics at KAUST. Research Interest: His research interests lie in the fields such as

Wu Wang

Postdoctoral Research Fellow, Statistics
Wu Wang is a postdoctoral fellow at King Abdullah University of Science and Technology (KAUST) working with Professor Ying Sun in the environmental statistics research group. Education Wu Wang received his Ph.D. degree in June 2017 from Fudan University, China. He joined KAUST in September 2017 Wu Wang received his Bachelor's degree in 2008 from East China Normal University Research Interest Wu Wang' s research interests lie in spatial varying coefficients regression with application in particulate matter modeling. He is also interested in functional data analysis, especially functional linear

Junho Lee

Postdoctoral Research Fellow, Statistics
Short Bio about yourself Junho Lee received both undergraduate and Master degrees in Statistics from Yonsei University, Seoul, Korea. After his Master degree and before beginning his Ph.D. study, Junho Lee had worked at Korea Credit Bureau as a researcher to develop the Credit Scoring system for Bank, Credit Card and Insurance industries in Korea. Before joining KAUST in August 2017, Junho Lee received his Ph.D. in Statistics from University of Wisconsin-Madison, USA. Here, at KAUST, Junho Lee is working at Environmental Statistics Group with Prof. Ying Sun. Education and Early Career Ph.D. in

Jose Hermenegildo Ramirez Gonzalez

Postdoctoral Research Fellow, Statistics

Huang Huang

Ph.D., Statistics
Career 2022-, Quantitative Researcher & Developer, Abu Dhabi Investment Authority (ADIA), UAE. 2019-2021, Research Scientist, King Abdullah University of Science and Technology (KAUST), Saudi Arabia. Research statistical modeling of multivariate spatio-temporal data with large size Apply machine learning models to environmental data with comparisons to spatio-temporal statistical models Lead reading groups on spatial machine learning Collaborate with computer scientists in developing high-performance packages for large geostatistical inference Mentor students on their internship on research

Ghulam A. Qadir

Ph.D. Student, Statistics
Ghulam Qadir is a Ph.D. student in the Environmental Statistics group under the supervision of Prof. Ying Sun at the King Abdullah University of Science and Technology (KAUST). He believes that KAUST creates a perfect research-friendly environment where students are provided with excellent resources which allow them to turn their research creativity into valuable discoveries as well as make them ready for their future endeavors. Education and Early Career M.Sc. Statistics, Hindu College, University of Delhi, 2016 B.Sc. (Hons.) Statistics, Hindu College, University of Delhi, 2014 Research

Gaurav Agarwal

Ph.D., Statistics
Gaurav Agarwal obtained his Ph.D. degree in Statistics from King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Ying Sun in the Environmental Statistics group. His research focused on developing statistical models for dealing with the issues concerning the environment. Bringing data to life, with statistics and programming excites him. Besides research, he likes to dance and work out. Research Interest Gaurav's research interests included Multivariate quantiles, Non-parametric statistics, Functional data analysis, and Spatial Statistics. Awards and

Fouzi Harrou

Senior Research Scientist, Statistics
Harrou’s research focuses on statistical decision theory and its applications, multivariate statistical process monitoring, anomaly detection and diagnosis.

Cristian Felipe Jiménez Varón

Ph.D. Student, Statistics
Cristian Felipe Jiménez Varón is a Ph.D. candidate in the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Cristian obtained a master's degree in applied mathematics from the Universidad Nacional de Colombia Sede Manizales (UNAL), Colombia. He also holds dual bachelor's degrees in industrial engineering and chemical engineering from UNAL. Research Interests Cristian's research interests include the analysis of large volumes of data, statistical modeling and environmental statistics.

Carolina D. Euan Campos

Postdoctoral Research Fellow, Statistics
Dr. Carolina Euan is a postdoctoral fellow at the Environmental Statistics Research Group at King Abdullah University of Science and Technology (KAUST). Education and Early Career Carolina Euan received her Ph.D. degree in Probability and Statistics from the Center for Research in Mathematics (CIMAT), Mexico, in 2016. She joined KAUST as a Postdoctoral Research Fellow in October 2016. Research Interest High dimensional Time Series, Spatio-Temporal Models, Non-Stationary Processes, Complex Data Visualization, Computational Statistics. Awards and Distinctions Sylvia Esterby Presentation Award
<> machine learning (25)

Zakaria El Kassimi

KAUST offers a unique environment where applied mathematics and data science meet real-world impact, with exceptional resources and a supportive community for ambitious research.

Jonathan Klein

Research Scientist, Computer Science
My fields of research interests include computational simulation, plant simulation and modeling, synthetic training data, machine learning architectures, none-line-of-sight imaging, and computational photography.

Yibin Wang

Keep Moving forward

Andrea Vanessa Rocha

Research Specialist, Statistics

Vecchia Approximations of Gaussian Processes on GPUs for Scalable Spatial Modeling and Computer Model Emulation

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B9 L2 R2325

This seminar introduces GPU-accelerated Vecchia approximations to overcome Gaussian Process computational limits, enabling scalable applications for large geospatial datasets and high-dimensional computer model emulations.
Chengjie zhao

Chengjie Zhao

Visiting Researcher, Information Science Lab
Visiting Student, King Abdullah University of Science and Technology

Mohamed Ads

Visiting Student, King Abdullah University of Science and Technology

Hayssam Dahrouj

Senior Research Scientist at KAUST (King Abdullah University of Science and Technology)

Karen Sanchez

Postdoctoral Research Fellow
Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Hani A. Al Majed

M.S. Student
Electrical and Computer Engineering Master's student at KAUST under the supervision of Professor Bernard Ghanem, with expertise in machine learning workflow automation, physics-informed neural operators, and AI for Science, particularly in chemistry applications. Passionate about leveraging AI to solve complex scientific problems.

Ahmad Sait

M.S. Student, Computer Science
Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.

Saleh AlJazzar

Research Fellow at King Abdullah University of Science and Technology (KAUST) .

Muhammad Esmat

Visiting student at, King Abdullah University of Science and Technology (KAUST).

Yasser Jaber

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Ahsan Mehmood

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

Abdulkarem Badiea Alshaibani

Visiting Student at the Information Science Lab at the King Abdullah University of Science and Technology (KAUST).

Meet KAUST prospective student: Pratik Nag

1 min read ·
Pratik Nag will join KAUST this fall as a Ph.D. candidate and member of the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Pratik holds a master's degree in statistical quality control and operation research, and a bachelor's degree in statistics, from the Indian Statistical Institute and the University of Calcutta, India.

KAUST Environmental Statistics group publishes book exploring multivariate statistical analysis

1 min read ·
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.

Deep learning in the emergency department

1 min read ·
Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments.

Deeper defense against cyber attacks

1 min read ·
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.

Can machine learning help predict disease spread?

1 min read ·
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.
Sameh Abdulah

Sameh Abdulah

Sameh Abdulah > Appointments, Roles and Affiliations, Hierarchical Computations on Manycore Architectures
Dr. Sameh Abdulah specializes in HPC, scalable algorithms, and climate modeling, with innovations receiving the ACM Gordon Bell Prize for Climate Modelling.

Pratik Nag

Ph.D. Student, Statistics
Pratik Nag is a Ph.D. candidate at the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Pratik obtained a master's degree in statistical quality control and operation research from the Indian Statistical Institute, India. Research Interests Pratik's research interests focus on machine learning, artificial intelligence and statistical techniques to solve problems related to spatio-temporal processes. Education Profile Master's degree in Statistical Quality Control and operation research, Indian Statistical Institute, India

Fouzi Harrou

Senior Research Scientist, Statistics
Harrou’s research focuses on statistical decision theory and its applications, multivariate statistical process monitoring, anomaly detection and diagnosis.
<> Deep learning (14)

Zakaria El Kassimi

KAUST offers a unique environment where applied mathematics and data science meet real-world impact, with exceptional resources and a supportive community for ambitious research.

Adonai Vera

Machine Learning Engineer with 6+ years of experience specializing in computer vision, deep learning, and robotics. Led AI solutions for retail analytics, UAV systems, and edge devices. Author, educator, and TensorFlow Google Developer Expert.

Juan Pablo Muñoz Díaz

Karen Sanchez

Postdoctoral Research Fellow
Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Mhd. Emad Alolaby

Sixiu Liu

Ph.D. degree in Earth science and engineering with the King Abdullah University of Science and Technology (KAUST)

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab
Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)
<> spatio-temporal statistics (13)

Vecchia Approximations of Gaussian Processes on GPUs for Scalable Spatial Modeling and Computer Model Emulation

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B5 L5 R5209

This thesis advances the computational efficiency of Vecchia approximation methods for Gaussian Processes (GPs), emphasizing GPU-based implementations for large-scale geospatial analysis and computer emulation. Traditional GPs require expensive covariance matrix inversions, which this work overcomes using scalable Vecchia-based approximations without sacrificing accuracy.

Haziq Jamil

Research Specialist, Statistics
Haziq Jamil is a Research Specialist at the King Abdullah University of Science and Technology. His research focuses on statistical theory, methods and computation, with a special inclination towards social science applications.

Professor Ying Sun elected as a Fellow of the American Statistical Association

3 min read ·
Ying Sun joins the elite ranks of ASA Fellows in 2025 for her contributions to spatial statistics, mentoring and global outreach.

CEMSE Welcomes new Professor: Dr. Ying Sun

1 min read ·
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.

2015 Workshop on Computational Space-Time Statistics

1 min read ·
Organizers : Prof. Marc G. Genton , Chair of Spatio-Temporal Statistics and Data Science Group Prof. Raphael Huser, Chair of Extreme Statistics Group​ Prof. Ying Sun​, Chair of Environmental Statistics Group Confirmed speakers: Prof. Sudipto Banerjee, University of California Los Angeles, USA Prof. Souhaib Ben Taieb, Monash University, Australia Prof. Stefano Castruccio, Newcastle University, UK Prof. Miguel de Carvalho, Pontificia Universidad Catolica de Chile,​ Chile Prof. Clément Dombry, University of Franche-Comté , France Prof. Xuming He, University of Michigan, USA Prof. Hsin-Cheng Huang

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

1 min read ·
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).

Using Statistical Models to Solve Environmental Problems

1 min read ·
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.

Meet KAUST Prospective Student: Amin Wu

1 min read ·
Amin Wu is a 24-year-old graduate who will join KAUST from the Communication University of China. Wu will join the University in the fall of 2020 as an M.S./Ph.D. candidate in the KAUST Environmental Statistics Research Group under the supervision of Professor Ying Sun. Wu wants to be a teacher or researcher and use her expertise and knowledge to make the world a better place.

Meet KAUST new student: Qilong Pan

1 min read ·
Qilong Pan is a statistics graduate who joined KAUST in June 2021 from the Wuhan University of Technology, China. Pan is a M.S./Ph.D. student and member of the Environmental Statistics research group under the supervision of Professor Ying Sun.

Ying Sun

Professor, Statistics
Professor Ying Sun leads a research group focusing on environmental statistics. She is at the forefront of developing advanced models and methodologies in the fields of spatio-temporal statistics, functional data analysis and process monitoring.

Qilong Pan

Ph.D. Student, Statistics
Qilong Pan's research focuses on developing scalable statistical methods, with a particular emphasis on Gaussian Processes and GPU acceleration.

Jose Hermenegildo Ramirez Gonzalez

Postdoctoral Research Fellow, Statistics

Fouzi Harrou

Senior Research Scientist, Statistics
Harrou’s research focuses on statistical decision theory and its applications, multivariate statistical process monitoring, anomaly detection and diagnosis.
<> artificial intelligence (11)
Salem Alsaqaf

Salem Al-saqaf

Salem Al-Saqaf is an Electrical and Computer Engineer specializing in semiconductors, electronics and AI. He combines strong academic training with practical industry experience in AI-driven solutions, data science, and system optimization. His work spans applied research and real-world innovation, aiming to advance intelligent systems, enhance semiconductor applications, and develop technologies that bridge academic discovery with industrial impact.
Najmeddine Dhieb

Najmeddine Dhieb

Mohamed Ads

Visiting Student, King Abdullah University of Science and Technology

Yasmeen Alsaedy

M.S. Student, Computer Science
She is an AI researcher specializing in generative AI and deep learning. With a strong academic foundation and hands-on experience in machine learning, data science and artificial intelligence, she is passionate about advancing AI applications in real-world scenarios. She has contributed to cutting-edge projects, published research, and collaborated on innovative solutions that bridge the gap between AI theory and practice. Her expertise includes designing and implementing advanced data models, AI-driven visual/text computing, and deep learning architectures.

Yasser Jaber

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab
Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)

Meet KAUST prospective student: Pratik Nag

1 min read ·
Pratik Nag will join KAUST this fall as a Ph.D. candidate and member of the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Pratik holds a master's degree in statistical quality control and operation research, and a bachelor's degree in statistics, from the Indian Statistical Institute and the University of Calcutta, India.

Deep learning in the emergency department

1 min read ·
Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments.

Ángel López Oriona

Postdoctoral Research Fellow, Statistics
Dr. López Oriona received his bachelor’s degree in Mathematics and his master’s degree in Statistics both from the University of Santiago de Compostela (Spain), his master’s degree in Big Data Analytics from the European University of Madrid (Spain), and his PhD in Statistics from the University of A Coruña (Spain). He was a Visiting Researcher at the Sapienza University of Rome (Italy), the University of Sydney (Australia), the Helmut Schmidt University of Hamburg (Germany), and Lancaster University (United Kingdom). Since September 2023, he is a Postdoctoral Fellow in the Environmental

Pratik Nag

Ph.D. Student, Statistics
Pratik Nag is a Ph.D. candidate at the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Pratik obtained a master's degree in statistical quality control and operation research from the Indian Statistical Institute, India. Research Interests Pratik's research interests focus on machine learning, artificial intelligence and statistical techniques to solve problems related to spatio-temporal processes. Education Profile Master's degree in Statistical Quality Control and operation research, Indian Statistical Institute, India
<> cybersecurity (9) <> computational statistics (8)

Andrea Vanessa Rocha

Research Specialist, Statistics

Professor Ying Sun elected as a Fellow of the American Statistical Association

3 min read ·
Ying Sun joins the elite ranks of ASA Fellows in 2025 for her contributions to spatial statistics, mentoring and global outreach.

Computational Methods for Large Spatio-temporal Datasets and Functional Data Ranking

-

B1 L4 R4102

In this thesis defense, I will talk about two topics—computational methods for large spatial datasets and functional data ranking. Both are tackling the challenges of big and high-dimensional data.

Ángel López Oriona

Postdoctoral Research Fellow, Statistics
Dr. López Oriona received his bachelor’s degree in Mathematics and his master’s degree in Statistics both from the University of Santiago de Compostela (Spain), his master’s degree in Big Data Analytics from the European University of Madrid (Spain), and his PhD in Statistics from the University of A Coruña (Spain). He was a Visiting Researcher at the Sapienza University of Rome (Italy), the University of Sydney (Australia), the Helmut Schmidt University of Hamburg (Germany), and Lancaster University (United Kingdom). Since September 2023, he is a Postdoctoral Fellow in the Environmental

Ying Sun

Professor, Statistics
Professor Ying Sun leads a research group focusing on environmental statistics. She is at the forefront of developing advanced models and methodologies in the fields of spatio-temporal statistics, functional data analysis and process monitoring.

Pratik Nag

Ph.D. Student, Statistics
Pratik Nag is a Ph.D. candidate at the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Pratik obtained a master's degree in statistical quality control and operation research from the Indian Statistical Institute, India. Research Interests Pratik's research interests focus on machine learning, artificial intelligence and statistical techniques to solve problems related to spatio-temporal processes. Education Profile Master's degree in Statistical Quality Control and operation research, Indian Statistical Institute, India

Jose Hermenegildo Ramirez Gonzalez

Postdoctoral Research Fellow, Statistics

Carolina D. Euan Campos

Postdoctoral Research Fellow, Statistics
Dr. Carolina Euan is a postdoctoral fellow at the Environmental Statistics Research Group at King Abdullah University of Science and Technology (KAUST). Education and Early Career Carolina Euan received her Ph.D. degree in Probability and Statistics from the Center for Research in Mathematics (CIMAT), Mexico, in 2016. She joined KAUST as a Postdoctoral Research Fellow in October 2016. Research Interest High dimensional Time Series, Spatio-Temporal Models, Non-Stationary Processes, Complex Data Visualization, Computational Statistics. Awards and Distinctions Sylvia Esterby Presentation Award
<> Signal processing (8)

Serine Medjber

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri

Mohammed Amine Labbas

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri
Chengjie zhao

Chengjie Zhao

Visiting Researcher, Information Science Lab
Visiting Student, King Abdullah University of Science and Technology
Almutasem Bellah Enad

Almutasem Bellah Enad

Visiting Researcher (former), Information Science Lab
Visiting Student, King Abdullah University of Science and Technology, Present M.Eng in Electrical and Computer Engineering, American University of Beirut, Lebanon
Ahmad Dkhan

Ahmad Dkhan

Visiting Scholar (former), Information Science Lab
Visiting Student, King Abdullah University of Science and Technology Present -Master's in Electrical and Computer Engineering, American University of Beirut, Lebanon

Saleh AlJazzar

Research Fellow at King Abdullah University of Science and Technology (KAUST) .

Alaa Alameer Ahmad

Research visit to communication theory lab in computer, electrical and mathematical sciences and engineering. KAUST (King Abdullah University of Science and Technology) ,Worked with research groups supervised by Prof. Mohamed-Slim Alouini and Prof. Tareq AL-Naffouri.

Abdullatif Al-Rabah

MS Degree, Computer, Electrical and Mathematical Sciences and Engineering at King Abdullah University of Science and Technology (KAUST).
<> applied mathematics (7)

Juan Pablo Muñoz Díaz

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.

A clearer view of rainfall patterns

1 min read ·
Improved random modeling allows scientists to generate realistic patterns of high-frequency rainfall.

Getting the jump on industrial failures

1 min read ·
A statistics-driven method for the early detection of emerging problems in industrial processes could improve industrial safety, reliability and productivity.

Keeping antennas at peak performance

1 min read ·
Sensitive detection of partial faults in antenna systems could prevent performance degradation in wireless networks.

A safe sweep of weather data

1 min read ·
A statistical technique for automatically cleaning erroneous data from weather-balloon observations will improve the accuracy of weather forecasting.

Getting a visual on complex data

1 min read ·
A new method for visually presenting complex data distributions provides a much-needed tool for management, analysis and interpretation.
<> Computer Vision (7)

Adonai Vera

Machine Learning Engineer with 6+ years of experience specializing in computer vision, deep learning, and robotics. Led AI solutions for retail analytics, UAV systems, and edge devices. Author, educator, and TensorFlow Google Developer Expert.

Abdelrahman Eldesokey

Postdoctoral Research Fellow
Abdelrahman Eldesokey is a Postdoctoral Fellow at KAUST, working on Generative AI and Computer Vision. His research focuses on diffusion models, multimodal large language models, and vision foundation models, aiming to make generative systems more controllable, interpretable, and reliable.
Najmeddine Dhieb

Najmeddine Dhieb

Karen Sanchez

Postdoctoral Research Fellow
Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Aznaur Aliev

M.S. Student

Hani A. Al Majed

M.S. Student
Electrical and Computer Engineering Master's student at KAUST under the supervision of Professor Bernard Ghanem, with expertise in machine learning workflow automation, physics-informed neural operators, and AI for Science, particularly in chemistry applications. Passionate about leveraging AI to solve complex scientific problems.

Ahmad Sait

M.S. Student, Computer Science
Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.
<> IoT (7)
Salem Alsaqaf

Salem Al-saqaf

Salem Al-Saqaf is an Electrical and Computer Engineer specializing in semiconductors, electronics and AI. He combines strong academic training with practical industry experience in AI-driven solutions, data science, and system optimization. His work spans applied research and real-world innovation, aiming to advance intelligent systems, enhance semiconductor applications, and develop technologies that bridge academic discovery with industrial impact.

Serine Medjber

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri

Mohammed Amine Labbas

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri
Ruochen Zhu

Ruochen Zhu

Mohamed Ads

Visiting Student, King Abdullah University of Science and Technology
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Ahsan Mehmood

Intern (former), Information Science Lab
Visiting student at King Abdullah University of Science and Technology (KAUST).
<> spatial statistics (6)

Kriging Asymptotics

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B1 L4 R4102

Spatial analyses often focus on spatial smoothing using the geostatistical technique known as kriging. Theoretical results regarding large sample convergence rates of kriging predictors remain elusive. By casting kriging as a variational problem, we develop an equivalent kernel approximation technique that can also lead to computational feasibility for large data problems.

A Distributed Implementation of the Multi-resolution Approximation for Very Large Spatial Data

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B1 L4 R4102

With data of rapidly increasing sizes in the environmental and geosciences such as satellite observations and high-resolution climate model runs, the spatial statistics community has recently focused on methods that are applicable to very large data. One such state-of-the-art method is the multi-resolution approximation (MRA), which was specifically developed with high performance computer architecture in mind.

Workshop on Statistical Process Monitoring and Risk Assessment for Engineering and Spatial Environmental Applications

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B1 L4 R4102

LIST OF SPEAKERS KAUST Environmental Statistics Group, CEMSE Division - Ying Sun (ying.sun@kaust.edu.sa), PI - Fouzi Harrou (fouzi.harrou@kaust.edu.sa), Postdoc - Huang Huang (huang.huang@kaust.edu.sa), PhD Student - Tianbo Chen (tianbo.chen@kaust.edu.sa), PhD Student - Rui Meng (rui.meng@kaust.edu.sa), Master Student - Sulaiman Binkhamis (sulaiman.binkhamis@kaust.edu.sa), Master Student Hydrology and Land Observation Group, BESE Division - Gaohong Yin (gaohong.yin@kaust.edu.sa), Master Student Collaborators - NorEddine Ghaffour (noreddine.ghaffour@kaust.edu.sa), co-I, WDRC - Matthew McCabe

Students shine on the statistics stage

1 min read ·
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.

CEMSE Division student spotlight: Gaurav Agarwal

1 min read ·
Gaurav Agarwal firmly believes in the age-old adage that patience is a virtue. Without patience, life’s challenges cannot be overcome, and a steadfast belief in perseverance has served the statistics Ph.D. student well throughout his academic career.

Gaurav Agarwal

Ph.D., Statistics
Gaurav Agarwal obtained his Ph.D. degree in Statistics from King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Ying Sun in the Environmental Statistics group. His research focused on developing statistical models for dealing with the issues concerning the environment. Bringing data to life, with statistics and programming excites him. Besides research, he likes to dance and work out. Research Interest Gaurav's research interests included Multivariate quantiles, Non-parametric statistics, Functional data analysis, and Spatial Statistics. Awards and
<> Cyber Security (5) <> ISAC (5)
kaust-cemse-ece-ccsl-changhao-he

Changhao He

kaust-cemse-ece-ccsl-yousef-awad

Yousef Awad

kaust-cemse-ece-ccsl-bumin-kagan-yildirim

Bumin Kagan Yildirim

Bang Huang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Bang Huang works as a postdoctoral fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Bang Huang received the M.S. degree (with honors) in electrical engineering and Ph.D degree in information and communication engineering from the School of Information and Communication Engineering (SICE), University of Electronic Science and Technology of China (UESTC), Chengdu, China, in

Xiaowei Pang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Xiaowei Pang is currently a Postdoctoral Research Fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Xiaowei Pang received her B.S. degree in Telecommunication Engineering from Northwestern Polytechnical University, Xi'an, China, in 2018, and her Ph.D. degree in Information and Communication Engineering from Dalian University of Technology, Dalian, China, in 2024. From 2021 to 2022
<> award (4)

Ying Sun wins Young Researcher Award

1 min read ·
KAUST Assistant Professor of Statistics Ying Sun won the 2016 Abdel El-Shaarawi Young Researcher (AEYR) Award from the International Environmetrics Society (TIES) in June. The society was founded by El-Shaarawi, an Egyptian-born and Canadian-trained statistician, and the award was established by the board of TIES in 2002 to honor young statisticians who have made excellent contributions to the development of statistical and/or quantitative methods for environmental science research. Sun received the award on July 18 at the 26th Annual Conference of the International Environmetrics Society in

Professor Sun receives the Environment Early Investigator Award 2017

1 min read ·
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).

Assistant Professor Ying Sun wins American Statistical Association award

1 min read ·
​​​​Ying Sun, KAUST assistant professor of applied ​mathematics and computational science​, won the 2017 Section on Statistics and the Environment (ENVR) Early Investigator Award from the American Statistical Association (ASA). Sun received her award at the 2017 Joint Statistical Meetings (JSM), held from July 29 to August 3 in Baltimore, Maryland, U.S. Sun's award recognizes her important contributions to the field of environmental statistics that help to address major problems like climate change and environmental pollution. At KAUST, Sun leads the Environmental Statistics Group in the

Postdoc Carolina Euan received Sylvia Esterby Presentation Award from TIES

1 min read ·
Carolina Euán, a postdoctoral fellow in KAUST Associate Professor Ying Sun's Environmental Statistics research group, recently received the Sylvia Esterby Presentation Award from the International Environmentrics Society (TIES) at the 28th Annual TIES Conference 2018 held from July 16 to 21, 2018, in Guanajuato, Mexico. Euán won the award for her talk entitled "Bernoulli Vector Autoregressive Model with Applications to Spatio-temporal Drought Events in Mexico."
<> computational methods (4)

CEMSE Welcomes new Professor: Dr. Ying Sun

1 min read ·
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.

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

1 min read ·
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).

Using Statistical Models to Solve Environmental Problems

1 min read ·
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

1 min read ·
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.
<> environmental applications (4)

CEMSE Welcomes new Professor: Dr. Ying Sun

1 min read ·
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.

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

1 min read ·
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).

SRSI student success story at Ibdaa 2022

1 min read ·
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.

Ying Sun

Professor, Statistics
Professor Ying Sun leads a research group focusing on environmental statistics. She is at the forefront of developing advanced models and methodologies in the fields of spatio-temporal statistics, functional data analysis and process monitoring.
<> healthcare (4) <> HPC (4)

Vecchia Approximations of Gaussian Processes on GPUs for Scalable Spatial Modeling and Computer Model Emulation

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B5 L5 R5209

This thesis advances the computational efficiency of Vecchia approximation methods for Gaussian Processes (GPs), emphasizing GPU-based implementations for large-scale geospatial analysis and computer emulation. Traditional GPs require expensive covariance matrix inversions, which this work overcomes using scalable Vecchia-based approximations without sacrificing accuracy.

Amal Alghamdi

Saverio Pasqualoni

M.S. Student, Computer Science
Saverio is a Master’s student pursuing graduate studies (M.S. and Ph.D.) in Computer Science at KAUST, working in the SANDS research group on high-performance computing and collective communications, with research interests that bridge systems-level computer science and large-scale simulation through a strong mathematical foundation.
ACM Gordon Bell Prize for Climate Modelling

KAUST wins the “Nobel” of high-performance computing for climate modeling

1 min read ·
KAUST has been awarded the “Nobel" prize of high-performance computing—the ACM Gordon Bell Prize for Climate Modelling—in partnership with the NSF National Center for Atmospheric Research, U.S. and other partner institutions.
<> integrated photonics (4)

Nikita Kondratyev

Mikhail Mishevskii

Mikhail received the B.S. degree in applied mathematics and physics from Novosibirsk State, Novosibirsk, Russia and received a master's degree with honors from the Skolkovo Institute of Science and Technology (Skoltech). His research interests include: nonlinear optics, integrated photonics, ultrafast lasers, frequency comb generation. During his time at Skoltech participated in the Skoltech Translational Research and Innovation Program industrial project to create a pulsed submicron laser for pumping a single-photon quantum light source. Mikhail awarded with Scholarship of the President of

Aleksandr Movsisian

Aleksandr received his bachelor’s degree in 2023 in Physics from Moscow State University (MSU, ranked first in Russia) and completed a master’s degree in Physics with honors at the same institution. He has over two years of research experience in quantum optics, optomechanics, and quantum measurement theory as part of the LIGO group at MSU. His work has focused on squeezed states of light, measurement topologies, and methods to overcome the Standard Quantum Limit, resulting in two first-author publications in JOSA B and Optics Letters. Aleksandr also gained hands-on experimental experience at

Aram Mkrtchyan

Postdoctoral Research Fellow, Electrical and Computer Engineering
<> uncertainty quantification (4)

Amal Alghamdi

ACM Gordon Bell Prize for Climate Modelling

KAUST wins the “Nobel” of high-performance computing for climate modeling

1 min read ·
KAUST has been awarded the “Nobel" prize of high-performance computing—the ACM Gordon Bell Prize for Climate Modelling—in partnership with the NSF National Center for Atmospheric Research, U.S. and other partner institutions.

Uncertainty Quantification of Tsunami Models

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B1

In this talk, we first show various strategies for the efficient emulation of simulators having uncertain inputs, with applications to tsunami wave modelling. A fast surrogate of the simulator's time series of outputs is provided by the outer product emulator.

Pratik Nag

Ph.D. Student, Statistics
Pratik Nag is a Ph.D. candidate at the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Pratik obtained a master's degree in statistical quality control and operation research from the Indian Statistical Institute, India. Research Interests Pratik's research interests focus on machine learning, artificial intelligence and statistical techniques to solve problems related to spatio-temporal processes. Education Profile Master's degree in Statistical Quality Control and operation research, Indian Statistical Institute, India
<> AI (3) <> bioscience (3) <> data (3) <> data analysis (3) <> data science (3)

2018 Workshop on Statistics and Data Science

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Auditorium 0215 between Buildings 4 & 5

The Statistics Program at KAUST is proud to host the 2018 Workshop on Statistics and Data Science. This workshop gathers the leading experts on statistical data science to discuss the current needs, challenges and opportunities of modeling massive and high dimensional data, predicting complex biological and physical processes. The workshop will run from November 12-14. Talks and posters presentations will take place in Auditorium 0215 (between Buildings 4 & 5). View Workshop's Agenda.

2019 Statistics and Data Science Workshop

1 min read ·
From November 18 to 20 the KAUST CEMSE Division has hosted the 2019 Statistics and Data Science Workshop. The workshop, organized by Workshop Chair Professor Ying Sun from the KAUST Environmental Statistics Group, featured 17 keynote talks from eminent data science researchers from Asia, Europe, North America and on-campus. Talks included: personalized recommendation by learning from heterogeneous graph data; dynamic spatial panel models; networks, common shocks, and sequential exogeneity; unbiased Markov chain Monte Carlo, plus many more.

KAUST STAT students come together for second ASA chapter meeting

1 min read ·
Members of the KAUST American Statistical Association (ASA) student chapter recently came together for the group’s second online meeting held on Tuesday, November 10, 2020. The meeting served as an orientation exercise for new KAUST Statistics (STAT) Program students while also highlighting the shared experience of STAT Ph.D. candidates: Jian Cao, Wanfang Chen, Yuxiao Li, and Gaurav Agarwal.
<> embedded systems (3) <> extreme computing (3) <> haps (3)

Bang Huang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Bang Huang works as a postdoctoral fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Bang Huang received the M.S. degree (with honors) in electrical engineering and Ph.D degree in information and communication engineering from the School of Information and Communication Engineering (SICE), University of Electronic Science and Technology of China (UESTC), Chengdu, China, in

Xiaowei Pang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Xiaowei Pang is currently a Postdoctoral Research Fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Xiaowei Pang received her B.S. degree in Telecommunication Engineering from Northwestern Polytechnical University, Xi'an, China, in 2018, and her Ph.D. degree in Information and Communication Engineering from Dalian University of Technology, Dalian, China, in 2024. From 2021 to 2022
H

Hussein Al-Shatri

I chose KAUST because of its reputation for excellence in research and its recent emphasis on applied research. With my extensive background in both academic research and industrial development, I am excited to contribute my experience and ambition. My goal is to foster new ideas and develop innovative prototypes in the field of wireless communications, which will undoubtedly enhance people's lives.
<> LiDAR (3) <> MATLAB (3) <> Nonlinear Optics (3) <> optimization (3) <> Photonics and optoelectronics (3) <> Python (3) <> Reinforcement Learning (3) <> Statistical Modeling (3) <> Statistics of extremes (3) <> student award (3) <> Advanced Perception (2) <> AI4Science (2) <> Automous Vehicles (2) <> Bayesian computational statistics (2) <> big data (2) <> biomedical devices (2) <> brain science (2) <> climate science (2) <> communication (2) <> computational simulations (2) <> Dynamical Systems (2) <> forecasting (2)

Statistical Analysis of Multi-day Solar Irradiance using a Threshold Time Series model

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B9 H2 R2325

Abstract The analysis of solar irradiance has important applications in predicting solar energy production from solar power plants. Although the sun provides every day more energy than we need, the variability caused by environmental conditions affects electricity production. Most of the existing statistical models to forecast solar irradiance are linear and highly depend on normality assumptions. However, solar irradiance shows strong non-linearity and is only measured during the day time. Thus, we propose a new multi-day threshold autoregressive (TAR) model to quantify the variability of the

Cristian Felipe Jiménez Varón

Ph.D. Student, Statistics
Cristian Felipe Jiménez Varón is a Ph.D. candidate in the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Cristian obtained a master's degree in applied mathematics from the Universidad Nacional de Colombia Sede Manizales (UNAL), Colombia. He also holds dual bachelor's degrees in industrial engineering and chemical engineering from UNAL. Research Interests Cristian's research interests include the analysis of large volumes of data, statistical modeling and environmental statistics.
<> FPGA (2) <> Generative AI and LLMs (2) <> GPU Computing (2) <> human health (2) <> Large Language Models (2) <> LLM (2) <> Localization (2) <> machine learning for wireless communication (2) <> modeling (2) <> multimodal sensing (2) <> nanomaterials (2) <> Network Design (2) <> Non-Terrestrial Networks (2) <> nonparametric statistics (2) <> optical computing (2) <> photonic integrated circuits (2) <> Programming language (2) <> quantum communication (2) <> remote sensing (2) <> sensors (2) <> student focus (2) <> ultrafast fiber lasers (2) <> weather (2) <> wireless communication (2) <> Wireless Communications (2) <> 2D materials (1) <> 5G and beyond (1) <> 5G networks (1) <> 6G (1) <> 6G On-chip reconfigurable intelligent surface (1) <> 6G On-chip reconfigurable transmitarray and phased array (1) <> 6g wireless systems (1) <> Action Recognition (1) <> Action understanding (1) <> adaptive control (1) <> Adaptive Optics (1) <> Aerial Robotics (1) <> aerospace design (1) <> Affective AI (1) <> AI for healthcare (1) <> ambit fields (1) <> Arabic NLP (1) <> artificial intelligence for wireless communication (1) <> automotive security (1) <> Bayesian Statistics (1) <> beamforming (1) <> bifurcation theory (1) <> biological processes (1)