CARLOS FELIPE NAVARRO CLAVERIA

Email: carlosnavarroc@uchile.cl
Phone: +569 9445 9922
Personal Website: https://carlosnavarroc.github.io/

PROFESSIONAL SUMMARY

Data Scientist and Electrical Engineer with over 15 years of experience in machine learning, signal processing, and computer vision applied to biomedical, mining, and retail problems. Skilled in designing data-driven solutions for diagnostics, predictive modeling, and image analysis, with strong expertise in deep learning frameworks and statistical modeling. Proven ability to lead interdisciplinary research and deliver impactful results in academic and applied environments.

EXPERIENCE

Data Scientist

Faculty of Medicine, University of Chile
Neurosystems, SCIANLab & AudioBrain
September 2019 – August 2025

• Applied machine learning, signal processing, and computer vision to biomedical and cognitive health challenges.
• Led development of spectral analysis and predictive models on EEG data for postoperative risk assessment.
• Built automated glaucoma diagnosis pipelines using chromatic pupilometry and machine learning.
• Developed RaViTT, a Vision Transformer model for biomedical image classification.
• Engineered deep learning solutions for 3D nuclei segmentation, achieving second place in a competitive challenge.
• Co-created VolumePeeler, a FIJI plugin for enhanced 3D image visualization.
• Designed audiological tests for early detection of cognitive decline.
• Contributed data analysis for a national social isolation study post-pandemic.

Technologies & Tools: Python, R, MATLAB, TensorFlow, Keras, Scikit-learn, OpenCV, EEG analysis, Deep Learning, Transformers, Data Visualization.

Applied Research Engineer – Computer Vision & Data Analysis

Faculty of Physical Sciences and Mathematics, University of Chile
2009 – 2018

• Developed computer vision and machine learning models for retail and mining applications, including object detection and image registration.
• Designed automated lithology classification pipelines from video data using pattern recognition.
• Built Bluetooth telemetry systems for geotechnical slope stability monitoring.

Technologies & Tools: Python, MATLAB, OpenCV, SVM, Feature Extraction, Signal Processing, Automation Systems.

EDUCATION

• PhD in Electrical Engineering — University of Chile (2020)
  Thesis: Color–Texture Pattern Classification Using Global–Local Feature Extraction, an SVM Classifier, with Bagging Ensemble Post-Processing.

• Diploma in Electrophysiology Technology — Faculty of Medicine, University of Chile (2019)

• Electrical Engineering (Ingeniero Civil Electricista) — University of Chile (2010)
  Thesis: Design of Molds for Iris Detection Using Particle Swarm Optimization.

CERTIFICATIONS & ACHIEVEMENTS

• IEEE RAS Summer School on Deep Learning for Robot Vision (2019)
• Finalist, Hackathon Summit País Digital by EY (2024)
• Google Cloud Skills Boost: Cloud AI and Generative AI courses and badges

SELECTED PUBLICATIONS & PROJECTS

• Cochlear dysfunction as an early biomarker of cognitive decline in normal hearing and mild hearing loss. (2024) — Alzheimer’s & Dementia
• RaViTT: Random Vision Transformer Tokens (2023) — arXiv preprint
• VolumePeeler: a novel FIJI plugin for geometric tissue peeling to improve visualization and quantification of 3D image stacks (2023) — BMC Bioinformatics
• 3D Nuclei Segmentation through Deep Learning (2023) — IEEE CAI Conference
• Color–Texture Pattern Classification Using Global–Local Feature Extraction, an SVM Classifier, with Bagging Ensemble Post-Processing (2019) — Applied Sciences

TECHNICAL SKILLS

• Programming: Python, R, MATLAB
• ML & AI: Supervised/unsupervised learning, deep learning (CNNs, Transformers), SVM, signal and image processing
• Tools & Frameworks: TensorFlow, Keras, PyTorch, Scikit-learn, OpenCV, FIJI/ImageJ
• Data Science: Data cleaning, feature engineering, predictive modeling, cross-validation, experiment reproducibility
• Visualization: Matplotlib, Seaborn, Plotly, Jupyter Notebooks
• Cloud & DevOps: Docker, Google Cloud (Vertex AI), basic CI/CD, Git/GitHub/GitLab
• Generative AI & LLMs: Prompt engineering, deployment, evaluation of LLaMA, Qwen-VL, Gemini models

ADDITIONAL PROJECTS

• Virtual Beauchef: Creator of a virtual campus space on Gather Town to enhance social interaction during COVID-19.
• La Ciudad de Los Cesares: Independent film producer; managed crowdfunding and production.
• Antiguas placas, antiguos nombres: Cultural documentation project focused on photographing and cataloging historical street signs and plaques in Chilean cities. The results were published in Cuadernos de Beauchef (2024), highlighting urban memory and heritage.

INTERESTS

Photography, cooking, astronomy, and cultural documentation.