Profiles

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.

Eman Kabbas is a Saudi researcher specializing in Bayesian statistics and modeling. She earned her Bachelor’s degree in Mathematics from Imam Abdulrahman bin Faisal University, then continued her studies in the United States through the King Abdullah Scholarship Program, obtaining a Master’s degree in Applied Mathematics from the University of North Carolina. Supported by scholarships from KAUST and the Royal Commission of Jubail and Yanbu, Eman is currently a PhD student in Applied Mathematics and Computational Science (AMCS) at King Abdullah University of Science and Technology (KAUST), supervised by Professor Håvard Rue. Beyond her research, Eman is a Mathematics and Statistics faculty member at Jubail Industrial College under the Royal Commission of Jubail and Yanbu, and co-founder of Sorat Alardh, a startup advancing environmental monitoring and climate analytics. She envisions combining theory and real-world application by transforming scientific research into practical tools that enhance environmental resilience and data-driven innovation in Saudi Arabia. Eman enjoys reading, learning new languages, playing the piano, and exploring strategic games like chess.

Eman Kabbas's research interests focus on developing and applying spline models in non-parametric regression. She addresses the limitations of splines in prediction tasks with insufficient data by proposing a spline model suitable for both regular and irregular observations, leverages Bayesian techniques to ensure efficient modeling and reliable predictions.