Ahmed Aboudonia
Ahmed Aboudonia is a robotics and control researcher whose work focuses on the intersection of control theory, mathematical optimisation, and machine learning. His research goal is to design adaptive, learning-enabled, and data-driven control frameworks for uncertain and complex systems, with practical impact on autonomous systems, sustainable energy systems, and trustworthy societal systems.
Since February 2025, he has been a Postdoctoral Researcher at theUniversity of Illinois Urbana-Champaign(UIUC) in the United States, where he develops adaptive learning-based and data-driven control methods for robotic platforms. His technical expertise includes control theory, mathematical optimisation, machine learning, data science, Python, MATLAB, and applied robotics.
Before joining UIUC, Ahmed spent nearly seven years at ETH Zürich (2018–2025) as a Scientific Assistant. During this period, he led major research projects in adaptive control and data-driven control systems. He collaborated with Swiss Federal Railways (SBB) to design control architectures for railway rolling stock and with Swiss Research Laboratories (Empa) to develop data-driven algorithms for building energy management. This technology was later adopted by Viboo and has demonstrated up to 40% energy savings in European buildings. His work at ETH also covered microgrids, energy systems, and machine learning-based optimisation.
Earlier in his career, Ahmed was a Research Assistant at Sapienza University of Rome, working on humanoid robot gait generation and obstacle avoidance using model predictive control and mathematical optimisation. At The German University in Cairo, he proposed robust control algorithms for unmanned aerial vehicles. He also conducted research at the German Aerospace Center (DLR) on disturbance estimation for helicopters and completed machine learning research at TU Darmstadt on human activity recognition. He gained early industry exposure through an internship atSiemens.
Ahmed holds a PhD in Automatic Control from ETH Zürich (2018–2023), a Master’s degree in Control Engineering from Sapienza University of Rome, and both a Master’s and Bachelor’s degree in Mechatronics Engineering from The German University in Cairo. He has authored more than 15 peer-reviewed publications in IEEE, Elsevier, Springer, and PMLR, covering predictive control, machine learning for control, building energy optimisation, UAV control, and humanoid robotics.
His academic excellence has been recognised through multiple scholarships and awards, including DAAD Scholarship, Sapienza Excellence Awards, and several GUC fellowships and honours.
