Profiles

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.

• 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

Anna Talgat is currently a Ph.D. candidate in Applied Mathematics and Computational Sciences at KAUST. She earned her B.S. in Mathematics from Fatih University, Istanbul, with high honors and a full scholarship. Anna continued her studies at KAUST, completing her M.S., focusing on stochastic geometry-based analysis of LEO satellite communication systems. Her early career includes an internship at Cambridge University’s DAMTP and teaching mathematics at Galaxy International School in Kazakhstan. Additionally, she was a Graduate Teaching Assistant at KAUST, supporting academic development and enhancing teaching methodologies.

Anna Talgat's research interests primarily focus on stochastic geometry and its applications in communication systems. Specifically, her work includes the stochastic geometry-based analysis of LEO satellite communication systems, performance analysis and optimization of wireless communications, and enhancing the efficiency and reliability of these networks. Her research aims to advance the understanding and development of satellite communication networks, which are critical for various applications, including IoT (Internet of Things) and secure data transmission in space communications.

Diego Augusto Silva is a Ph.D. candidate at the Communications and Computing Systems Laboratory (CCSL) within the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. His research focuses on event-based vision, object recognition, deep learning, and neuromorphic computing.

He received his Bachelor’s degree in Electrical Engineering from the Federal University of São João del-Rei (UFSJ), Brazil, in 2018, and his M.Sc. degree in Electronic Engineering and Computing from the Technological Institute of Aeronautics (ITA), Brazil, in 2020, with a specialization in Electronic Devices and Systems.

Diego’s technical expertise spans both theoretical and practical aspects, with significant experience in FPGA prototyping and asynchronous logic design. His innovative work has been recognized through two hackathon awards in his research areas, highlighting his ability to translate advanced neuromorphic computing and event-based vision concepts into real-world solutions.

Diego's research interests include the digital logic design of algorithms and event-based cameras.