Welcome to my portfolio! I am a MSc Software Design student specializing in software development and machine learning. With a background in architectural engineering, I bring a unique cross-disciplinary mindset to building scalable systems and solving complex technical challenges. I’m passionate about designing intelligent solutions and exploring how machine learning can enhance real-world applications.
Software Developer – Sealytix, Copenhagen
April 2025 – Present
- Automate vessel onboarding processes through backend development and API integration.
- Develop and optimize machine learning workflows, including implementing models such as autoencoders to accelerate data generation and model training.
- Work with Azure-based data infrastructure and CI/CD pipelines to ensure scalability and automation efficiency.
- Evaluate model performance, refine feature engineering, and streamline preprocessing of structured and unstructured maritime data.
Teaching Assistant – Software Engineering, IT University of Copenhagen
August 2025 – Present
- Support students in agile practices, software architecture, and testing methodologies.
- Provide feedback on assignments and facilitate discussions on software design concepts.
Architect / Computational Designer – Bjarke Ingels Group (BIG), Copenhagen
January 2022 – July 2024
- Developed Python scripts and automation workflows to optimize design and data analysis processes.
- Conducted environmental simulations and produced analytical reports for large-scale projects.
- Collaborated with multidisciplinary teams to integrate computational insights into design decisions.
M.S., Software Design – IT University of Copenhagen
August 2024 – August 2027
- Focus: Data Analytics, AI, Big Data Systems, Machine Learning
B.S., Engineering – University of São Paulo
January 2016 – December 2021
- Languages: Python, Java, SQL, C#, LaTeX
- Python Libraries: pandas, numpy, matplotlib, seaborn
- Data & Analytics Tools: Power BI, Power Automate (learning), Excel, DBeaver
- Development Tools: Git, GitHub, VS Code, Jira
- Concepts: Data Cleaning, Data Visualization, Relational Databases, Data Mining, Big Data Systems, Agile Framework (SCRUM)
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Object Tracking & Image Projection 🔗
Implemented affine 2D transformations to project tracked image coordinates onto a spatial map, combining geometric modeling, regression, and visualization techniques.
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Iris Detection and Tracking
Implemented iris detection to locate pupil centers in eye images and built a screen coordinates model for calibration.
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USA Housing Price Prediction 🔗
Created a linear regression model to predict U.S. housing prices based on demographic data. -
Heart Attack Prediction 🔗
Performed comparative analysis with logistic regression and decision tree classifiers.
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Othello AI with Alpha-Beta MinMax 🔗
Designed a strategic AI player for Othello using alpha-beta pruning optimization. -
Sudoku Solver 🔗
Implemented constraint satisfaction techniques including forward checking and arc consistency.
- Search Engine in Java 🔗
Developed a search engine featuring indexing, ranking algorithms, and query processing.
This project recreates a digital analytics environment for a fictional toy retailer, showcasing my ability to simulate user behavior tracking, build clean data pipelines, and deliver actionable insights through tailored dashboards and communication assets.
- Designed and implemented simulated tracking variables to analyze customer journeys, engagement patterns, and conversion metrics.
- Focused on transforming behavioral data into clear, business-relevant insights to support decision-making.
Tools Used: Power BI, SQL, Python, Pandas, NumPy
Customer Journey & Purchase Metrics - Q3 2025
View the Power BI Dashboard
Last updated: August 7, 2025 — content subject to change as the project develops.
A data-driven analysis of Brazil's 2024 exports to the U.S., visualized using Power BI, in light of new tariffs announced by U.S. President Donald Trump, set to take effect in August 2025. These tariffs, targeting Brazilian goods, could affect a trade flow worth nearly $40 billion.
Key findings show that nearly half of exports come from São Paulo and Rio de Janeiro—driven by Embraer aircraft and crude oil, respectively. While the U.S. plans a 50% tariff on many imports, almost half of Brazilian exports—including aircraft, oil, and orange juice—will remain at a 10% rate. However, coffee and meat will face steeper increases.
View the Power BI Dashboard (PDF)
Thank you for visiting my portfolio. Feel free to explore my projects and reach out if you'd like to connect! I'm looking forward to hearing from you!