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Sultan Albarakati

Instructional Assistant Professor 
Director, KAUST Academy

Computer, Electrical and Mathematical Science and Engineering Division


Education Profile

  • PhD. Applied Mathematics, July 2020, King Abdullah University of Science and Technology
  • Master's degree, Applied Mathematics, June 2014, King Abdullah University of Science and Technology
  • Bachelor's of Science, Mathematics, June 2004, Umm Al-Qura University

Research Interests

Professor Sultan Albarakati is the Director of KAUST Academy, and the mission of the Academy is to provide continuous learning initiatives to support development in Saudi Arabia. KAUST Academy provides training courses targeted at undergraduate students and early career professionals to enhance their academic and professional training with short, condensed courses in the areas of artificial intelligence, machine learning and data science. The courses on offer are micro-credential courses, diplomas, and part-time master's degree courses.

The Academy is focusing on creating partnerships with universities and organizations in the Kingdom and contributing to the growth of National Talent Development in line with Vision 2030. These collaborations will cover joint curriculum development and teaching, guest lectures, short student exchange visits, joint workshops and conferences, and collaborations to conduct national events like PyCon and AICon.

Currently there are top young leaders in the Kingdom who are KAUST graduates. We need to build on this success and increase our footprint and reach a larger population of students and trainees in the Kingdom. KAUST academy was created with this as the primary goal.

Selected Publications

  • Albarakati S., Lima R.M., Theußl T., Hoteit I., Knio O.M. Multi-objective risk-aware path planning in uncertain transient currents: an ensemble-based stochastic optimization approach 2020-07-06 Journal of Oceanic Engineering
  • Albarakati, S., Lima, R. M., Theußl, T., Hoteit, I., & Knio, O. M. Optimal 3D time-energy trajectory planning for AUVs using ocean general circulation models. 2020-07-06 Journal of Oceanic Engineering
  • Albarakati, Sultan, Advisors: Knio, Omar; Shamma, Jeff S. Trajectory Planning for Autonomous Underwater Vehicles: A Stochastic Optimization Approach (2020-08-30) [KAUST Dissertation]