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 solve problems in medicine and biology. Led and collaborated on interdisciplinary research using data-driven approaches for diagnostics, biomedical image analysis, and cognitive health.

Key Projects & Contributions:

Neurosystems

• Applied spectral analysis and statistical modeling on EEG data for postoperative complication prediction.
• Built predictive models to assess the combined effect of anesthetics using clinical and electrophysiological data.
• Developed a machine learning pipeline for automated glaucoma diagnosis from chromatic pupilometry data. Poster

SCIANLab

• Developed RaViTT, a Vision Transformer-based model for biomedical image classification. Paper
• Engineered deep learning models for 3D nuclei segmentation, achieving 2nd place in the Cell Tracking Challenge. Paper
• Co-developed VolumePeeler, a FIJI plugin to improve 3D image visualization and quantification. Publication
• Applied image analysis for membrane deformation quantification and embryo development tracking in live imaging data.
• Conference Service: Member of Review Board, ISICS 2024, Intelligent Computing Systems 5th International Symposium, Sharjah, UAE, Nov 6–7, 2024.

AudioBrain

• Designed and evaluated an audiological test to detect early signs of cognitive decline using signal processing and ML. - Publication
• Conducted data analysis for a national study on social isolation and loneliness in elderly post-pandemic. - Publication

Key Tools & Methods: Python, R, MATLAB, Scikit-learn, TensorFlow, Keras, OpenCV, Signal/Image Processing, EEG Analysis, Deep Learning, SVM, Transformers, Data Visualization.

Applied Research Engineer – Computer Vision & Data Analysis

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

Worked on R&D projects in retail, mining, and biomedical domains, applying computer vision, signal processing, and automation techniques. Participated in both academic and industry-funded initiatives, including field installations and interdisciplinary collaborations.

Key Projects & Contributions:

• Image Processing in Mining & Retail:
  Developed descriptor-based models and optimization strategies for image registration and object detection to support stock breakage detection in supermarkets.
  • INNOVA Project 13IDL2-23589
• Pattern Recognition via Video Analysis:
  Designed machine learning pipelines for automated lithology classification and rock type estimation using video-based pattern recognition.
  • Poster: Lithological Classification
  • Poster: Rock Type Estimation
  • Fondef Project D08I-1060
• Sensor Systems for Slope Stability (CSIRO Chile):
  Built and tested Bluetooth-based telemetry systems for geotechnical monitoring in mining environments. Designed control and data acquisition hardware and software for lab and field experiments. (9-month collaboration)

Key Tools & Methods: Python, OpenCV, MATLAB, Optimization Algorithms, Feature Extraction, SVM, Signal & Image Processing, Computer Vision, Automation Systems

Education

PhD in Electrical Engineering (2020)

• Institution: Faculty of Physical Sciences and Mathematics, University of Chile
• Thesis: Color–Texture Pattern Classification Using Global–Local Feature Extraction, an SVM Classifier, with Bagging Ensemble Post-Processing
• Description:
  This research proposed a novel approach to classification problems using color and texture features, highlighting the importance of multiscale feature extraction to integrate color and texture information effectively. The results led to two publications: a conference article and a journal article.

Diploma of Technology in Electrophysiology (2019)

• Institution: Faculty of Medicine, University of Chile
• Description:
  Specialized in bioelectric signal processing and electrophysiology of sensory systems. Final work involved a theoretical analysis of an electrophysiological signal for clinical use and a proposal for clinical application.

Electrical Engineering (2010)

• Institution: Faculty of Physical Sciences and Mathematics, University of Chile
• Thesis: Molds design for iris detection through Particle Swarm Optimization
• Description:
  Proposed two methodologies to create templates for iris localization: a handcrafted approach and an automated method using Particle Swarm Optimization (PSO). The PSO method generates templates independent of anthropometric data and captures key eye features for improved iris detection accuracy.

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 Profile – Various courses and skill badges related to Cloud, AI, and Generative AI. (2025)

Technical Summary

Languages: Python, R, MATLAB.

Machine Learning & AI: Skilled in supervised and unsupervised learning, deep learning, computer vision, statistical modeling, optimization, predictive analytics, and signal/image processing.

Generative AI & LLMs: Experience in prompt engineering, model deployment, and evaluation of open-weight large language models such as LLaMA 3.2-vision and Qwen-VL 2.5 3B, along with practical use of Gemini via Google Vertex AI. Completed the GenAI Zero to Hero course by Google Cloud Learning Mexico and participated in a generative AI hackathon at Summit País Digital using Huawei Cloud, organized by EY.

Cloud & DevOps Tools: Proficient in deploying multi-container web services with Docker, working with Google Cloud (Vertex AI and AI ethics principles), Huawei Cloud, and basic CI/CD practices.

Version Control & Collaboration: Advanced use of Git, GitHub, and GitLab for collaborative coding, version control, documentation, and issue tracking.

Libraries & Frameworks: Experienced with Scikit-learn, TensorFlow, PyTorch, OpenCV, and FIJI/ImageJ.

Data Handling: Handling large-scale structured and unstructured data, including feature engineering, cleaning, and integration.

Evaluation & Validation: Strong background in cross-validation, performance metrics, robustness testing, and experiment reproducibility.

Visualization & Reporting: Skilled in Matplotlib, Seaborn, Plotly, and Jupyter for effectively communicating results to both technical and non-technical audiences.

Best Practices: Writing maintainable and testable code, ensuring reproducible research, applying version control rigorously, and adhering to data privacy and ethical AI development standards.

Other Projects

• Project: Virtual Beauchef
  • UChile News
  • Description: This project was initiated using the Gather Town platform. It recreates the Beauchef campus to encourage social interactions and collaborative work in a fun environment, creating new digital experiences that bring the University closer to students unable to visit due to the pandemic.
• Project: La Ciudad de Los Cesares Producer
  • Official site
  • Description: As an independent film producer, coordinated people and resources to follow the planned work schedule. Delivering a quality final product was challenging and rewarding. The film was fully financed through crowdfunding.

A Little More About Me

Besides professional activities in engineering, other interests and hobbies include:

• Photography: capturing moments and scenes.
• Cooking: experimenting with recipes and flavors.
• Astronomy: exploring the night sky and stars.
• Cultural Documentation: capturing cultural heritage through photography, focusing on museums, architecture, and heritage events like Día de los Patrimonios. Though not a formal expert, I engage passionately with Chilean culture, enriching my perspective beyond my technical work.