Zaid Sawlan

Student

PhD Student​​​​

Research Interests

  • ​Model calibration and Bayesian model comparison for fatigue data.
  • Bayesian inference in linear parabolic PDEs with noisy boundary conditions.
  • History matching using ensemble Kalman filters.

Selected Publications

  • ​Fabrizio Ruggeri, Zaid Sawlan, Marco Scavino, Raul Tempone, A hierarchical Bayesian setting for an inverse problem in linear parabolic PDEs with noisy boundary conditions, submitted, 2015​​
  • I. Babuska, Z. Sawlan, M. Scavino, B. Szabo, R. Tempone, Bayesian inference and model comparison for metallic fatigue data,  Accepted for publication in Computer Methods in Applied Mechanics and Engineering, Feb. 2016

Education

  • 2006-2010 Bachelor of Science, Mathematics, King Saud University, Saudi Arabia.
  • 2010-2012 Master of Science, Applied Mathematics, King Abdullah University of Science & Technology, Saudi Arabia.

Professional Profile

  • Teaching Assistant at KAUST (Stochastic Methods in Engineering).
  • Research Intern at ARAMCO (summer 2014).

Awards

  • 2008-2010 KAUST Discovery Scholarship, King Saud University, Saudi Arabia.
  • 2010- KAUST Fellowship, King Abdullah University of Science & Technology, Saudi Arabia.

KAUST Affiliations