Dr. Mohamed Mabrok – Academic Profile
Dr. Mohamed Mabrok

Dr. Mohamed Mabrok

Associate Professor of Applied Mathematics

Dynamical systems and control AI & Machine learning AI in Healthcare

Academic Journey

2013
Ph.D. Completion

Ph.D. in Applied Mathematics

University of New South Wales, Australian Defence Force Academy, Canberra, Australia

2008
M.Sc. Degree

M.Sc. in Applied Mathematics/ Quantum Physics

Suez Canal University, Egypt

2004
B.Sc. Degree

B.Sc. in Applied Mathematics

Suez Canal University, Egypt

Dr. Mohamed Mabrok – Academic Profile

Professional Experience

2022 – Present
Current Position

Associate Professor of Applied Mathematics

Department of Mathematics, Statistics and Physics, College of Arts and Sciences, Qatar University

2021 – 2022
Promotion

Associate Professor

Department of Mathematics and Physics, Australian University, Kuwait

2017 – 2021
Academic Appointment

Assistant Professor of Applied Mathematics

Department of Mathematics and Physics, Australian University, Kuwait

2015 – 2017
Postdoctoral Research

Postdoctoral Fellow

Professor Jeff Shamma’s Group, King Abdullah University of Science and Technology (KAUST)

2013 – 2015
Postdoctoral Research

Post-doctoral Fellow

UNSW Canberra, Quantum Control

Research Focus

Dr. Mabrok’s research focuses on developing intelligent systems at the intersection of artificial intelligence and control theory, with applications in healthcare diagnostics and industrial automation. He is particularly interested in creating transparent, robust AI solutions that can be effectively deployed in real-world settings.

AI & Control Theory

Integrating machine learning with control systems for intelligent automation

Healthcare Diagnostics

Developing AI solutions for medical applications and diagnostics

Industrial Automation

Applying intelligent systems to optimize industrial processes

© 2023 Dr. Mohamed Mabrok. Academic Profile.

Dr. Mohamed Mabrok – Academic Profile

Research Focus

Dr. Mabrok’s research focuses on developing intelligent systems at the intersection of artificial intelligence and control theory, with applications in healthcare diagnostics and industrial automation. He is particularly interested in creating transparent, robust AI solutions that can be effectively deployed in real-world settings.

AI & Control Theory

Integrating machine learning with control systems for intelligent automation

Healthcare Diagnostics

Developing AI solutions for medical applications and diagnostics

Industrial Automation

Applying intelligent systems to optimize industrial processes