I. del Campo
Papers
4
Total Citations
16
H-Index
3
About
I. del Campo is a researcher specializing in hardware-accelerated intelligent systems, with a core focus on reconfigurable computing for robotics and industrial automation. Her work bridges the gap between advanced algorithms and practical embedded implementations, particularly through the use of Field-Programmable Gate Arrays (FPGAs). A key contribution is the development of a scalable architecture for high-speed multidimensional fuzzy inference systems, based on the Takagi–Sugeno model, which enables flexible, high-performance decision-making on reconfigurable hardware. She also pioneered an FPGA-based neural-network recognition module for visual servoing in mobile robots, designed to assist workers in manufacturing plants by integrating object detection and manipulation capabilities. Her research extends to fault-tolerant single-chip intelligent agents with feature extraction, demonstrating a commitment to robust, real-world deployment. While her citation counts (ranging from 3 to 5 per paper) reflect a focused, early-stage impact, her work is foundational for engineers seeking to embed adaptive intelligence into resource-constrained, industrial systems.
Research Focus
Key Achievements
Top Papers
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