Carlos Eduardo da Silva Santos
Papers
1
Total Citations
5
H-Index
1
About
Carlos Eduardo da Silva Santos is a researcher at the intersection of machine learning, control systems, and embedded hardware design. His primary contributions lie in optimizing Support Vector Machines (SVMs) through bio-inspired algorithms and deploying them on Field-Programmable Gate Arrays (FPGAs) for real-time applications. His most cited work, "A SVM optimization tool and FPGA system architecture applied to NMPC" (2017), introduces the Bio-inspired Optimization Tool for SVM (BIOTS), which uses a Multi-Objective Particle Swarm Algorithm (MOPSO) to automatically tune SVM hyperparameters—a critical step for model performance. By integrating this optimized SVM into a Nonlinear Model Predictive Control (NMPC) framework on FPGA, Santos bridges the gap between advanced machine learning and practical, hardware-accelerated control systems. With 5 citations, this paper demonstrates his ability to combine theoretical optimization with tangible engineering solutions. His work is particularly relevant for students and researchers exploring efficient, real-time AI deployment in cyber-physical systems, showcasing how nature-inspired algorithms can enhance both learning accuracy and computational speed.
Research Focus
Key Achievements
Top Papers
- 1A SVM optimization tool and FPGA system architecture applied to NMPC5 citations · 2017