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About

Mariel Alfaro-Ponce is a rising leader in the intersection of robotics, control systems, and advanced manufacturing, with a focus on creating intelligent, adaptive machines for real-world applications. Her primary research areas include assistive robotics, robust trajectory tracking, and collaborative automation. Alfaro-Ponce’s most influential work, “Assistive robotic exoskeleton using recurrent neural networks for decision taking for the robust trajectory tracking” (2022, 30 citations), pioneers the use of neural networks to enable exoskeletons to make autonomous decisions for stable movement, a critical step toward practical rehabilitation and mobility aids. She further advances control theory with her work on robotized arms under joint constraints (2023, 12 citations) and hybrid robust control for mobile manipulators in industrial recycling (2024, 2 citations), demonstrating her ability to bridge theoretical rigor with tangible engineering challenges. Notably, her 2025 study on a collaborative heterogeneous mini-robotic 3D printer for complex food structures (4 citations) showcases her innovative application of robotics to additive manufacturing, enabling precise, multi-material food fabrication. Alfaro-Ponce’s work is distinguished by its integration of neural network-based decision-making with robust control, positioning her as a key contributor to the next generation of autonomous, human-assistive, and industrial robotic systems.