Profiles

Administrative Staff

Guangyu Liu

Dr. Guangyu Liu is the assistant dean of CEMSE at KAUST, supporting the Division’s strategic priorities, interdisciplinary research and external engagement.
Education
Doctor of Philosophy (Ph.D.)
Electrical Engineering, Lehigh University, United States, 2013
Bachelor of Science (B.S.)
Electronic Science and Technology, Huazhong University of Science and Technology, China, 2008

Martins Bruvelis

Martins is a Tier 3 IT Specialist with a background in quantum engineering and data science. He leverages analytical, multidisciplinary, and data-driven approaches to drive innovation and efficiency within the IT infrastructure. He excels at full-stack development, identifying complex problems' root causes and developing impactful long-term solutions within a broad area of competence.

Former Members

Andrea Vanessa Rocha

Biography

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.

Research Interests

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.