Dr. Ambareen Khan | University Sains Malaysia (USM) | Malaysia
Dr. Ambareen Khan is an accomplished researcher in aerospace engineering and artificial intelligence, currently serving as a Lecturer in Artificial Intelligence at the Centre for Instructional Technology & Multimedia (PTPM), Universiti Sains Malaysia (USM). Her interdisciplinary research integrates computational fluid dynamics (CFD), machine learning, and experimental aerodynamics, with a focus on supersonic flow control, ANN modeling, and data-driven simulations.
Author Profile
Education
Dr. Ambareen Khan earned her Ph.D. in Aerospace Engineering from Universiti Sains Malaysia, where her thesis investigated passive flow control using rib geometries in sonic and supersonic flow conditions. She holds a Master of Science (Research) in Aerospace Engineering from USM and a second Master’s degree in International Business from the University of Nottingham, Malaysia. She completed her undergraduate studies in Computer Science Engineering under Visvesvaraya Technological University.
Professional Experience
Dr. Ambareen Khan currently lectures and supervises research projects in artificial intelligence applications in engineering. She previously completed a postdoctoral fellowship at USM’s School of Management, contributing to machine learning models for traffic behavior analysis in industrial zones. As a Graduate Research Assistant from 2020 to 2023, she conducted advanced simulations and wind tunnel experiments related to supersonic aerodynamics and base pressure control mechanisms.
Her industry-relevant skill set spans both engineering and AI, enabling her to work across disciplines such as CFD modeling, deep learning for flow prediction, and hybrid simulation methods.
Research Skills
Dr. Ambareen Khan expertise includes computational fluid dynamics (CFD), wind tunnel testing, supersonic jet analysis, and base pressure optimization. Her AI proficiency includes artificial neural networks (ANN), deep learning (CNN, SLNN), and data modeling using Python, TensorFlow, Keras, and C++. Her interdisciplinary capabilities are further supported by project experience in business analytics and systems modeling.
Selected Publications
Ambareen Khan, A., Rajendran, P., Khan, S.A., et al. (2025). Experimental and Numerical Investigation of Suddenly Expanded Flow at Sonic Mach Number. Scientific Reports.
Jamadar, I.S., Kumar, K., Ambareen Khan, A., et al. (2025). Quantum Pressure and Memory Effects in Cancer Modeling: A Fractional Calculus Neural Network Approach. Results in Engineering.
Ambareen Khan, A., Aabid, A., Akhtar, M.N., et al. (2025). Supersonic Flow Control with Quarter Rib in a Duct: An Extensive CFD Study. International Journal of Thermofluids.
Ambareen Khan, A., Rajendran, P., Sidhu, J.S.S., et al. (2023). CNN Modeling and Response Surface Analysis of Compressible Flow at Sonic and Supersonic Mach Numbers. Alexandria Engineering Journal.
Ambareen Khan, A., Mazlan, N.M., Ismail, M.A. (2022). Velocity Distribution and Base Pressure Analysis of Under Expanded Nozzle Flow at Mach 1.0. JARFMTS. (Scopus)
Ambareen Khan, A., Ismail, M.A., Mazlan, N.M. (2020). Numerical Simulation of Suddenly Expanded Flow from Converging Nozzle at Sonic Mach Number. Springer Proceedings, AeroMech 2019.
Conclusion
Dr. Ambareen Khan is a multidisciplinary researcher at the intersection of aerospace engineering and artificial intelligence. Her expertise in CFD, machine learning, and high-speed flow control has resulted in high-impact publications and real-world research applications. Through her innovative approach and academic leadership, Dr. Khan continues to make significant contributions to future aerospace technologies and intelligent systems.