I'm a Systems Engineer from Bogotá, Colombia, with a strong foundation in software design and a deep interest in the mathematical structure of complex systems. My work lives at the intersection of two disciplines: on one side, I design and build software with a focus on clean solid engineering principles, design patterns, good practices and quality of code; on the other, I do research in nonlinear system identification and data-driven control, where the goal is to build models that are not just accurate, but physically meaningful and computationally tractable.
I focus on building efficient, scalable, and well-structured systems. I care deeply about design principles, clean abstractions, and code that communicates intent clearly.
Languages
| 🗄️ SQL | Relational queries, schema design, constraints |
| 🗄️ PL/SQL | Stored procedures, triggers, Oracle-specific logic |
Frameworks & Libraries
| λ Scotty | Lightweight Haskell web framework |
| λ Cabal | Haskell build system & package manager |
| 🔗 REST API | Design and consumption of RESTful services |
Databases & Infrastructure
| 🔶 Oracle DB | Enterprise relational database, used with PL/SQL |
Tools
Primary distro: Nobara Linux (Fedora-based)
Design & Paradigms
| 🧱 OOP & OOD | UML, SOLID principles, Object-oriented Design, etc. |
| 🔁 Functional Programming | Inmutability, Lazy programming, Recursive Programming, High-order functions, etc. |
| 🎨 GoF Design Patterns | Strategy, Mediator, Decorator, Adapter, Bridge, etc. |
| 🗂️ Relational Databases | ER diagramming, normalization, schema design, relational algebra, etc. |
I work on nonlinear system identification and data-driven control, with an emphasis on methods that combine deep learning with physical structure. My research targets systems where neither pure data-driven nor purely analytical approaches are sufficient on their own.
Languages & Tools
| 📐 Simulink | Model-based simulation of dynamic systems |
| ⚙️ CasADi | Symbolic framework for numerical optimization & optimal control |
Areas of Focus
| 📦 System Identification | White, grey & black-box approaches to nonlinear systems |
| 🧠 Physics-Informed Neural Networks | PINNs — embedding physical laws into neural network training |
| 🌀 Koopman Operator Theory | Bilinear realizations for lifting nonlinear dynamics |
| 📈 NLARX Modeling | Nonlinear autoregressive models with exogenous inputs |
| 🎯 Model Predictive Control | MPC & NMPC for trajectory tracking and robust control |
| 🇨🇴 Spanish | Native |
| 🇬🇧 English | Advanced — technical reading, writing & comprehension |
| 🇩🇪 German | Basic — academic training |