Anass ElYaagoubi
- Postdoctoral Research Fellow, Statistics
- Ph.D., Statistics
I am a statistician, data scientist, and AI researcher working at the intersection of machine learning, topological data analysis, and complex scientific systems. At King Abdullah University of Science and Technology, I develop new statistical frameworks to uncover hidden structures in brain signals, networks, and high-dimensional biomedical data, while also building AI-powered education technology to make advanced learning more accessible at scale. My work combines mathematics, engineering, and scientific curiosity with a strong focus on real-world impact, from neuroscience research to the future of intelligent education.
Biography
Anass ElYaagoubi is a statistician, data scientist, and researcher currently based at King Abdullah University of Science and Technology. He earned his Ph.D. in Statistics from KAUST under the supervision of Hernando Ombao, focusing on topological and statistical analysis of brain time-series data. His academic work spans machine learning, topological data analysis, neuroscience, and high-dimensional statistical modeling, with publications in journals and conferences across statistics, AI, and computational neuroscience.
Before joining KAUST, he studied information systems engineering and data science in France at National Institute of Applied Sciences of Rouen and University of Rouen Normandy. Over the years, he has worked on projects involving biomedical signal analysis, natural language processing, search systems, and AI-enabled educational platforms. He has also taught statistics, machine learning, and programming to large academic and industry audiences, including collaborations with Saudi institutions and industry partners.
His broader vision is to bridge rigorous mathematical research with impactful technological tools that can improve scientific discovery, learning, and human understanding.
Research Interests
- Topological Data Analysis
- Time-Series Analysis and Dynamical Systems
- Computational Neuroscience and Brain Connectivity
- High-Dimensional Statistics and Network Science
- Biomedical Signal Processing (EEG, LFP, ECG, Hi-C)
- Large Language Models and AI for Education
- Scientific AI and Interdisciplinary Data Science
About
Anass ElYaagoubi is a postdoctoral researcher in statistics and data science at King Abdullah University of Science and Technology, specializing in statistical modeling, machine learning, time-series analysis, and topological data analysis. His research focuses on developing mathematical and computational methods for understanding complex biological and networked systems, particularly brain connectivity and neural dynamics. Alongside academia, he is also building AI-driven educational technologies that combine adaptive learning, large language models, and scalable software systems to democratize high-quality education.
Qualifications
Education
- Doctor of Philosophy (Ph.D.)
- Statistics, King Abdullah University of Science and Technology, Saudi Arabia, 2024
- Master of Engineering (M.Eng.)
- Computer Science, National Institute of Applied Sciences of Rouen, France, 2019
- Master of Science (M.S.)
- Data Science, University of Rouen Normandie, France, 2019
- English
- Full professional proficiency
- Arabic
- Native or bilingual proficiency
- French
- Native or bilingual proficiency
- Spanish
- Professional working proficiency
Languages
Quote
Curiosity, creativity, and rigorous thinking are powerful tools for uncovering hidden patterns in nature, solving meaningful real-world problems, and advancing our understanding of intelligence and complex systems.
Selected Publications
- El-Yaagoubi, A. B., Chung, M. K., & Ombao, H. (2024). Topological Analysis of Seizure-Induced Changes in Brain Hierarchy Through Effective Connectivity. ArXiv Preprint ArXiv:2407.13514.
- El-Yaagoubi, A. B., Chung, M. K., & Ombao, H. (2023). Topological data analysis for multivariate time series data. MDPI.
