EDISON SANTILLÁN
8+ years building intelligent systems that bridge electronics with artificial intelligence — from neural networks to real-time prediction algorithms.
ABOUT ME
Electronics and Automation Engineer specialized in Artificial Intelligence and Machine Learning — designing intelligent systems from neural networks to real-time prediction algorithms.
When I'm not building models, I mentor developers, participate in hackathons, and contribute to projects advancing AI and intelligent automation.
PROFESSIONAL JOURNEY
Led development of ML pipelines, neural networks for computer vision and time-series forecasting, smart home systems and real-time IoT inference systems.
Distributed consensus algorithms research. Designed neural network predictors for convergence and stability estimation in multi-agent systems.
Smart home and industrial automation systems. Led multidisciplinary teams for IoT integration and delivered technical training programs.
Electronic prototypes for automotive security — PCB design, ATmega128P in C, 2.4GHz RF wireless communication.
TECHNICAL SKILLS
NEURAL PIPELINE
DATA INGESTION
Robust pipelines handling streaming and batch inputs from sensors, APIs and databases — fault-tolerant, schema-validated, real-time ready.
PREPROCESSING
Noise filtering, normalization, outlier detection and feature extraction — maximizing signal quality before training.
MODEL TRAINING
LSTM, CNN and Transformer architectures trained GPU-accelerated with custom loss functions and automated hyperparameter tuning.
EVALUATION
Rigorous validation via cross-validation, confusion matrices, ROC curves and SHAP explainability.
DEPLOYMENT
Containerized models on cloud with autoscaling, 24/7 monitoring and automated retraining. Sub-100ms inference via REST APIs.
RESEARCH
Sliding Mode Control Approach for H₂ Purity Regulation in High-Pressure Alkaline Electrolyzers
Innovative sliding mode control strategies for hydrogen purity regulation in high-pressure alkaline electrolyzers — advancing sustainable energy and industrial process control in the renewable sector.
VIEW PUBLICATIONFEATURED PROJECTS
LSTM neural network for wind speed & direction at Minas de Huascachaca Wind Farm (14 turbines), optimizing renewable energy decisions.
RRT & RMP algorithms for multi-agent navigation in ROS-Gazebo with collision-free trajectory optimization and Rviz visualization.
Cloud-based emergency alert on DigitalOcean + ISSABEL PBX — remote activation via Zoiper for real-time community safety.
GET IN TOUCH
Have an interesting project? Let's talk about how we can apply AI, machine learning, or automation to your next challenge.