👋 Welcome to my profile!!
🔥 Overview
As an Informatics Engineer and PhD Candidate 🇪🇨, I specialize in the demanding intersection of Advanced Computational Tools and Environmental Science. My research is dedicated to leveraging Machine Learning (ML), Remote Sensing, and Data Analysis to foster sustainable development and territorial resilience.
I am deeply committed to interdisciplinary research, integrating knowledge from fields like silviculture and forest planning to address critical climate change impacts through advanced modeling and computational techniques. I advocate for collaborative science, contributing to multidisciplinary teams through open data practices and collective problem-solving.
🔬 Core Expertise & Technical Skills
My technical strength lies in processing and analyzing large-scale, multi-source datasets to derive actionable environmental intelligence.
| Category | Key Skills |
|---|---|
| Data & AI Tools | Python, R, SQL, TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy. |
| GIS & Remote Sensing | ArcGIS, QGIS, Google Earth Engine (GEE), Agisoft Metashape, Pix4D, Cloud Compare, Drone Deploy, DJI Terra, DJI Pilot, SCENE, TRIMBLE Business Center. |
| Data Acquisition | LiDAR (UAV and terrestrial), Multispectral, RGB, and Thermal sensors (UAV-based). |
| OS & Platforms | Linux, Windows, macOS, GCP, AWS, Azure, KVM, Terraform, Ansible, Vagrant, Git, LaTeX. |
🚀 Research & Professional Experience
Since 2018, my work as a Research and Laboratory Assistant at the University of Cuenca has focused on translating advanced computational theory into applied environmental research:
Key Achievements
- ML Model Implementation: Designed and implemented ML models for environmental and geospatial data analysis.
- Data Acquisition Leadership: Led campaigns using UAVs for LiDAR, multispectral, and RGB data acquisition, successfully integrating these inputs for complex forest and environmental modeling.
- Data Processing: Processed and analyzed large-scale datasets using Python and R for applied research in sustainability.
- Academic Support: Supported teaching activities in computer science, GIS, and data science, including technical mentoring.
Relevant Projects
- 2025 (Ongoing): Integration of LiDAR and multispectral UAV data for individual tree modeling in urban forests.
- 2025 (Ongoing): Development and implementation of ML algorithms for vegetation indices prediction using multi-source remote sensing data (Sentinel-2 and UAV imagery).
- 2024: Monitoring wildfire recovery of Andean vegetation in southern Ecuador using UAV RGB and thermal sensors.
- 2024: Classification of land cover types using ML algorithms within the Google Earth Engine environment.
🎓 Education & Career Goals
My academic journey is aimed at specialized research in climate-sensitive forest modeling.
| Degree / Program | Institution | Location | Years |
|---|---|---|---|
| Doctorate Internship (Erasmus+) | University of Valladolid | Soria, Spain | 2025–2026 |
| Computer Science, PhD Student | University of Cuenca | Cuenca, Ecuador | 2024–Present |
| MSc. Direction and Management of IT | International University of La Rioja | Logroño, Spain | 2020–2021 |
| BSc. Informatics Engineer | Technical University of Loja | Cuenca, Ecuador | 2014–2019 |
My primary career goal is to obtain my PhD, focused on climate-sensitive forest growth modeling using AI, and build an academic career that integrates teaching and applied research in environmental data science and sustainable development.
| Languages: Spanish (Native) | English (Upper Intermediate B2) |