Dr. Muhammet Emre Sanci | Robotics | Innovative Research Award
Dr. Muhammet Emre Sanci | Robotics | Istanbul Technical University at Turkey
Robotics expertise forms the foundation of the academic and research journey of Dr. Muhammet Emre Sanci, whose professional path seamlessly blends advanced theoretical knowledge with applied innovation in intelligent systems, nonlinear control, autonomous technologies, and UAV swarm intelligence. Dr. Muhammet Emre Sanci completed his PhD in Mechatronics Engineering at Istanbul Technical University, funded by the Ministry of Education Turkiye, where his thesis focused on adaptive inverse optimal controller design for nonlinear non-affine systems using machine learning methods. He also earned an MSc (Hons) in Electrical and Electronics Engineering at Pamukkale University, focusing on model-based control and autonomy in magnetic levitation systems, and previously completed a BE (Hons, 1st) in Electrical and Electronics Engineering at Anadolu University, where he compared fuzzy PID and PI controllers for DC microgrid energy systems. Adding multidisciplinary strength to his robotics vision, he studied Physics at Vilnius University through Erasmus+ mobility and completed BSc (Hons, 1st) in Physics at Abant Izzet Baysal University. Professionally, Dr. Muhammet Emre Sanci served as a Postdoctoral Fellow at the University of Idaho, advancing research in autonomous robotics, adaptive optimal control, multi-drone swarming systems, and agricultural automation. His work included adaptive disturbance rejection-based fuzzy PID control for UAV swarms, deep learning-based greenhouse automation, irrigation distribution modeling under heterogeneous soil conditions, and drone-based pest management systems, while providing data-driven modeling, algorithm development, and comprehensive documentation for large-scale research initiatives. Earlier, he served at Istanbul Technical University as Teaching & Research Assistant in Control and Automation Engineering, contributing to intelligent control, UAV-based autonomous mine sweeping, multi-agent local path planning, velocity obstacle avoidance, and neural network plus SVR-based nonlinear non-affine system identification strategies. His earlier experience at Pamukkale University integrated Robotics with materials and machining optimization, focusing on magnetic levitation system modeling and composite machining surface roughness prediction. He has extensive teaching expertise across multiple modules including Control Systems, Mechatronics, Real-Time Embedded Systems, Linear Algebra, Probability Theory, Microcontroller Systems, State-Space Methods, Intelligent Systems, Deep Learning, Hardware-in-the-Loop, Electronic Instrumentation, MATLAB Programming, and more, supporting robotics education at undergraduate and postgraduate levels. His research interests remain deeply rooted in Robotics, nonlinear intelligent control, adaptive UAV swarming, multi-agent autonomy, artificial neural networks for system identification, optimal control theory, and real-time embedded computation. His core research skills include nonlinear model design, optimal robotics controller development, multi-UAV coordination, intelligent system modeling, path-planning algorithms, machine learning implementation, and multi-environment dynamic optimization. His innovation has been supported by major competitive grants from national and international science foundations, including drone-based sensing system development for infrastructure inspection and UAV optimization technology for autonomous missions. His excellence is reflected through distinguished graduation achievements, academic honors, international research scholarships, and best presentation recognitions. In conclusion, Dr. Muhammet Emre Sanci stands as a robotics-focused scholar whose interdisciplinary expertise, highly adaptive control systems research, and forward-thinking approach to autonomous UAV swarming technologies significantly advance the global state-of-the-art in intelligent engineering systems, making him an invaluable contributor to emerging frontiers in Robotics.
Featured Publications
Sanci, M. E., Halis, S., & Kaplan, Y. (2017). Optimization of machining parameters to minimize surface roughness in the turning of carbon-filled and glass fiber-filled polytetrafluoroethylene. 2017, 6 citations.
Sanci, M. E., & Günel, G. Ö. (2024). Neural network based adaptive inverse optimal control for non-affine nonlinear systems. 2024, 5 citations.
Sanci, M. E., Uçak, K., & Günel, G. Ö. (2023). A novel adaptive LSSVR based inverse optimal controller with integrator for nonlinear non-affine systems. 2023, 5 citations.
Candan, F., Sanci, M. E., & Li, L. (2024). Vision-based relative navigation and drone swarming control for inspection in GPS-denied environment. 2024, 1 citation.
Sanci, M. E., Halis, S., & Kaplan, Y. (2016). Study on surface roughness of carbon and glass fiber filled polytetrafluoroethylene in turning process. 2016, 1 citation.