Profiles

Andrea Rocha is a research specialist in statistics at KAUST, working with the Stochastic Processes and Mathematical Statistics group. Before joining KAUST, she was an associate professor in the Department of Scientific Computing at the Federal University of Paraíba (UFPB), Brazil, where she also held various academic and coordination roles over nearly 15 years.

Her academic background includes a Ph.D. in Computational Mathematics, an M.Sc. in Statistics, and a B.Sc. in Statistics, all from the Federal University of Pernambuco (UFPE). Her doctoral and master’s work was supervised by Professor Andrei Toom.

Andrea’s research bridges theory and application in computational statistics, with a focus on probabilistic modeling, regression analysis, and stochastic processes. She has authored several publications in international journals and co-authored academic books on probability and random processes.

Andrea’s research lies at the intersection of computational mathematics, statistical inference, and applied probability. Her main areas of interest include:

• Statistical modeling of complex data using Bayesian methods
• Machine learning techniques for regression and classification
• Probabilistic simulation and stochastic processes
• Diagnostic and influence analysis in regression models
• Dispersion models and beta regression

She has contributed to the theory and application of statistical methods through both individual research and collaborations.

Her research interests include computer vision and deep learning, with a focus on video understanding and efficient models.

Damilya Saduakhas is a PhD candidate in Statistics at King Abdullah University of Science and Technology (KAUST) in the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) division, working under the supervision of Professor David Bolin. She received her B.S. degree in Mathematics from Nazarbayev University, Kazakhstan, in 2020 and her M.S. degree in Statistics from KAUST in 2022. Her work on log-Gaussian Cox processes on metric graphs received the Best Paper Award at Spatial Statistics 2025 and the Best Poster Award at ISBA World Meeting 2024. During her time at KAUST, she served as president of the ASA Student Chapter and as Academic and Research Counselor on the Graduate Student Council.

Damilya's research focuses on spatial statistical methods based on stochastic partial differential equations, with applications to environmental and urban data.