University of Idaho – Department of Soil and Water Systems | United States
Dr. Muhammet Emre Sanci is a research scientist and postdoctoral fellow specializing in Artificial Intelligence, Machine Learning, Robotics, UAV-based remote sensing, precision agriculture, and hydrological–environmental modeling, currently affiliated with the University of Idaho, Department of Soil and Water Systems. He earned his Ph.D. in Mechatronics Engineering from Istanbul Technical University, where his doctoral research focused on adaptive inverse optimal controller design for non-affine nonlinear systems using machine learning techniques, supported by the Turkish Ministry of National Education. He holds distinction-level master’s and bachelor’s degrees in Electrical–Electronics Engineering, along with an honors degree in Physics, enriched by international academic experience at Vilnius University through the Erasmus+ program. His research career is driven by the integration of AI-driven modeling, nonlinear control algorithms, and intelligent systems to solve practical environmental and agricultural challenges. At the University of Idaho, he has contributed to cutting-edge research in adaptive irrigation, UAV swarming control, subsurface defect detection in civil infrastructure, greenhouse climate control, and drone-based pest management, while also mentoring graduate students, developing models, preparing proposals, and ensuring high-quality documentation of scientific outcomes. His technological contributions include the development of advanced intelligent controllers—such as ELM-MPC, UKF-MRAC, and NARMA-L2—designed to enable high-efficiency autonomous control in greenhouse systems and water management applications. His interdisciplinary efforts span the United States, Turkey, and Europe, focusing on environment-aware robotics, precision agriculture systems, and climate-resilient technologies. He has authored peer-reviewed journal articles, developed simulation frameworks, and participated in several funded projects, including major U.S. National Science Foundation (NSF) and TUBITAK grants. With a portfolio including 10 completed or ongoing research projects, SCI-indexed publications, and growing academic citations, he continues advancing innovation at the intersection of AI, control systems, and environmental sustainability. His professional memberships include IEEE and ASABE, reflecting his active engagement within leading engineering and automation communities. Dr. Sanci has significant teaching experience at Istanbul Technical University and Pamukkale University, assisting in a wide range of courses––from control systems and stochastic processes to microcontrollers, deep learning, intelligent systems, instrumentation, and robotics––contributing to both theoretical education and laboratory-based learning environments. His achievements have been recognized with awards such as the Engineering Research Symposium Poster Prize and scholarships for academic excellence. Skilled in MATLAB, Python, C/C++, ROS, embedded systems, and simulation platforms, he continues to develop innovative technologies for UAVs, environmental monitoring, and smart agriculture toward globally sustainable solutions.
Profiles: Orcid | Google Scholar
Featured Publications
Sancı, M. E. (2025). An AI-enhanced adaptive discrete sliding mode control framework for non-affine nonlinear systems. International Journal of Robust and Nonlinear Control. Advance online publication.
Sancı, M. E., & Öke Günel, G. (2024). Neural network based adaptive inverse optimal control for non-affine nonlinear systems. Neural Processing Letters, 56(2), 46–59.
Sancı, M. E., & Öke Günel, G. (2024). Neural network based adaptive inverse optimal control for non-affine nonlinear systems. Neural Processing Letters, 56(2), 46–59.
Sancı, M. E., Uçak, K., & Öke Günel, G. (2023). A novel adaptive LSSVR based inverse optimal controller with integrator for nonlinear non-affine systems. IEEE Access, Article eXXXXX.