As a Bioengineering, I am passionate about data analyst and Python development with expertise in using Python libraries such as Pandas, Scikit-Learn, Numpy and SciPy for data analysis and machine learning. Proficient in programming microcontrollers using C and C++, and experienced in web development with JavaScript, Node.js, Docker, and React.
- Python
- Pandas, Scikit-Learn, SciPy, Scikit-Learn, Numpy, Tensorflow, Pytorch.
- Data Analysis
- Machine Learning
- C and C++ Programming
- Microcontroller Programming
- JavaScript
- React and Vue
- Docker
- AWS in python aplications certificate
- Google cloud basic infraestructure and GKE certificate
- Relevant Coursework: Biomedical Signal Processing, Biomaterials, Machine Learning.
- Relevant Coursework: LLMs, Agents workflows, Supervise and Unsupervise learning, Reinforce learning, Data analitycs, Deep Learning.
Data Analyst | H&M project
- Conduct data preprocessing, analysis, and visualization using Python, Pandas and SciPy.
- Develop and implement machine learning models to extract insights from data.
Microcontroller-controlled Biomedical Device | Infusion pump
- Programmed a microcontroller using C to regulate and monitor a medical device.
- Integrated sensors and actuators to ensure accurate functionality, demonstrating the application of programming in the medical field.
Web App for Deaf Users | Docker deployment
- Developed a web application using Node.js and React to assist deaf individuals in understanding technical words in engineering using sign language.
- Utilized JavaScript to create interactive visualizations and provided easy and interactive access to videos and definitions.
- Deployed as a Docker Flask service to ensure seamless accessibility and availability.
FMRI Task Images Pre and Post-Processing Pipeline with FSL and BIDS | Docker Pipeline
- Designed and implemented a comprehensive pipeline for pre-processing and post-processing functional magnetic resonance imaging (fMRI) task images using the FSL (FMRIB Software Library) toolkit and adhering to the BIDS (Brain Imaging Data Structure) standard.
- Utilized Python alongside FSL to perform data cleaning, normalization, and quality control, ensuring robust data for subsequent analysis.
- Implemented BIDS organization to enhance data management and reproducibility across different studies.
- Developed custom algorithms for noise reduction and artifact removal, enhancing the accuracy of subsequent analysis.
- Containerized the pipeline using Docker to facilitate consistent and reproducible execution across different environments.
- Documented the pipeline thoroughly and collaborated with the research team to ensure its effective integration into the analysis workflow.
- Assist in experiments and data collection for ongoing research projects.
- Apply Python for data preprocessing and assist in analyzing biological data.
- Contribute to team efforts in understanding complex enzymatic processes.
- Built Neo4j-backed pipelines for static code analysis, dependency tracking, and relationship modeling.
- Implemented agents capable of querying and synthesizing graph data from Neo4j for downstream automation.
- Developed internal tools to analyze architecture dependencies, improving visibility into change impact and system risk.
- English (C1)
- Spanish (Native)