Large-scale Data Analysis
Methods and workflows for complex datasets that exceed the practical limits of conventional analysis.
RESEARCH · BIG DATA · VISUAL ANALYTICS
Research driven by Large Complex Data.
My research and collaborations focus on methods and systems that make large, heterogeneous, and multidimensional datasets easier to compute, analyze, and understand.
KAUST brings together world-class researchers tackling important national and global challenges across diverse scientific disciplines. Their work generates massive volumes of complex scientific data that demand advanced computing, AI, and big-data analytics to turn raw data into meaningful scientific knowledge. Over the past decade, I have had the privilege of collaborating with these researchers to develop HPC, GPU computing, AI, big-data analytics, and visualization solutions that help them analyze, interpret, and extract actionable insight from large and complex datasets—supporting research that addresses real scientific and societal challenges.
Through these collaborations, I support research and industry across energy, climate, marine science, geoscience, food safety, and digital technologies, combining HPC, GPU computing, AI, and big-data analytics to transform complex data into actionable insight. Together, this work strengthens Saudi Arabia's digital research ecosystem and helps organizations tackle increasingly complex scientific and industrial challenges through advanced data analysis and computing.
RESEARCH THEMES
From scalable data systems to visual reasoning.
My work spans visual analytics, scientific visualization, spatio-temporal analysis, high-dimensional data, Big Data systems and data-intensive scientific workflows.
Visual Analytics
Interactive analytical approaches that combine computational methods with human visual reasoning.
Scientific Visualization
Visualization of simulations, measurements and multidimensional scientific phenomena.
Data-intensive Computing
HPC, GPU and scalable workflows that move analysis closer to the scale of modern research.
Data Science
Data-driven methods that turn complex research data into interpretable evidence, models and actionable insight.
Immersive Analytics
AR/VR services that turn complex scientific data into immersive, interactive experiences—from virtual exploration and 3D visualization to collaborative analysis and research showcases.
SAMPLE PROJECTS
Across disciplines. Across sectors.
Below are selected recent projects spanning environmental science, energy, climate, marine systems, geoscience, public health, and data-intensive visual analytics.
Energy
Climate & Weather
Marine Science
Geoscience
Digital Technologies
Data & AI
An interactive web-based framework for scenario-driven dust storm simulation and mitigation analysis
A unified web environment that connects interactive terrain editing, HPC-based dust-storm simulation, and comparative visualization, enabling researchers to test mitigation scenarios and examine their effects across the Arabian Peninsula.
View Publication →ColorPCA: Scalable Colored Dimensionality Reduction for Unlabeled High-dimensional Data
A scalable approach that integrates dimensionality reduction with color encoding to reveal hidden patterns in unlabeled high-dimensional data, implemented in a web-based visual analytics system and evaluated across benchmark and climate datasets.
View Publication →Visualization Environment for Analyzing Extreme Rainfall Events: A Case Study
An interactive environment for examining high-resolution weather simulations and the evolution of extreme precipitation, demonstrated through the November 2022 Jeddah rainfall event and its atmospheric dynamics.
View Publication →A Visual Analytics Framework for Renewable Energy Profiling and Resource Planning
An interactive decision-support environment for exploring long-term solar and wind resources, spatial variability, temporal profiles, and potential renewable-energy installation scenarios.
View Publication →Visualization and visual analytics approaches for image and video datasets: A survey
A broad survey of visualization research at the intersection of computer vision and visual analytics, organizing techniques, tasks, datasets, tools, and application areas while identifying gaps and opportunities for collaboration.
View Publication →A visual analytics based decision making environment for COVID-19 modeling and visualization
A linked visual analytics environment for exploring epidemic simulations, applying intervention measures, and examining their potential effects on disease spread and resource requirements across space and time.
View Publication →RedSeaAtlas: A Visual Analytics Tool for Spatio-temporal Multivariate Data of the Red Sea
A visual analytics system developed with ocean and atmospheric scientists to explore diverse multivariate Red Sea datasets through coordinated maps, charts, selections, and domain-specific analytical views.
View Publication →The State of the Art in Visual Analysis Approaches for Ocean and Atmospheric Datasets
An extensive survey of visual analysis for ocean and atmospheric science, covering task requirements, interaction, visualization, machine learning, uncertainty, data scale, and the use of HPC for complex scientific analysis.
View Publication →A therapy-driven gamification framework for hand rehabilitation
An adaptive e-health framework that turns prescribed hand-therapy movements into personalized serious games, using 3D navigation, patient and therapy models, and motion tracking to make rehabilitation more engaging and measurable.
View Publication →RESEARCH RECORD
A sustained publication and collaboration record.
Selected metrics from the current academic profile.
30+
Peer-reviewed publications
1200+
Citations
2026
Latest publication year
5
Patents
RESEARCH IN CONTEXT
Research is strongest when computation, domain knowledge and visual reasoning meet.
The KVL environment is designed around that intersection: domain scientists, large datasets, high-performance computing and interactive visualization.
See the Research Environment