I am a final-year Computer Science student at ESPOL (Ecuador) with a deep passion for the intersection of data and intelligent systems. My journey balances rigorous academic research with practical, real-world deployment.
Currently, I work as a Research Assistant at CIDIS-ESPOL, developing Computer Vision solutions to automate food quality assessment. Previously, I optimized ETL pipelines and automated SAP processes as a Business Intelligence Intern.
I am also the President of the Kokoa Free Software Club, where I advocate for open source, Linux, and knowledge sharing.
- 🔭 I’m currently working on: Hybrid Deep Learning architectures (CNN + KAN) for agriculture.
- 🌱 I’m currently learning: High-Performance Computing (HPC) & Rust.
- 🏆 Achievements:
- 🥇 1st Place: Pyweekend Hackathon (9th Ed.)
- 🗣️ Best Storytelling: TAWS Club Datathon
- 🥉 3rd Place: NASA Space Apps Challenge (Guayaquil)
| Role | Organization | Focus |
|---|---|---|
| Research Assistant | 🔬 CIDIS - ESPOL | Developing Computer Vision algorithms for defect detection in food; curating datasets and publishing academic research. |
| President | 🐧 Kokoa Free Software Club | Leading workshops on Linux/Virtualization and organizing tech events like CLI Week. |
| Business Intelligence Intern | 🦐 Vitapro | Automated SAP processes using Python, managed ETL pipelines, and created dashboards using Google BigQuery. |
| UI Designer Intern | 🎨 ZEDE del Litoral | Prototyped internal management systems (Low to High fidelity) to improve operational efficiency. |
An intelligent diagnosis system for cotton leaf diseases.
- Tech: Python, PyTorch, React, FastAPI.
- Innovation: Uses a hybrid SBTAYLOR-KAN architecture (94.8% accuracy) and Grad-CAM for interpretability.
🚲 Ride!
Facial recognition system for bike rentals.
- Recognition: Winner of the ESPOL innovation competition.
- Focus: Computer Vision applied to campus mobility.
🧩 PsychoPy
Consultant allocation optimization.
- Focus: Algorithmic logic to improve project management efficiency.
I am always open to discussing Computer Vision research, Data Engineering challenges, or Open Source initiatives.
- 📧 Personal: [email protected]
- 🏛️ Academic: [email protected]