Improved system performance, cutting processing time through better code and system design.

Optimized database queries and introduced caching mechanisms to handle increased data loads more efficiently.

Added error monitoring with Sentry, reducing the time to fix issues through automated alerts. This allowed for quicker identification and resolution of critical system errors.

Automated reporting workflows in Google Sheets and set up alerts for flight deals, reducing manual work and ensuring timely updates when high-value opportunities are detected.

Worked with other teams to ensure technical solutions matched business needs and were easy to use.

Designed and implemented a new architecture for the flight tracking system, enabling better scalability and maintainability.

Improved flight tracking software by automating data processing and integrating real-time APIs, resulting in faster and more accurate flight deal updates for users.

Built a Svelte dashboard and a Python-based Slack bot to streamline internal communication and cut manual updates by half. The bot shared real-time data, reducing the need for manual checks.

Developed a machine learning model to identify top-flight deals by analyzing multiple data sources, significantly reducing manual decision-making.

Automated software delivery with GitHub Actions to speed up deployments, improve code quality, and reduce human error.

Used Docker to simplify deployment and ensure consistency across environments, reducing production issues.

Delivered continuous improvements through rapid iteration, accelerating feature development and supporting evolving requirements.

Developed an IoT-powered smart lighting system that cut energy usage with intelligent scheduling, building the web app entirely from the ground up.

Built a Python backend with SQLAlchemy and MySQL, improving data management and making it easier to scale.

Created a Vue.js dashboard to give users an intuitive interface to monitor and control devices.

Set up real-time monitoring and automated alerts with Grafana to catch and report unusual device behavior quickly.

Worked with IoT engineers to improve communication between the cloud and physical devices, making the system more reliable.

Taught Logic, Machine Learning, and Programming, using hands-on projects to help students learn better. Designed interactive assignments to give students practical experience with real-world applications.

Improved AutoGOAL, an AutoML system that finds solutions to generic machine learning problems, by adding a meta-learning feature, reducing model training time. This enhancement made the system more adaptable to new datasets and improved model accuracy.

Helped students with artificial intelligence research projects, guiding them to complete and publish their work. Provided mentorship and technical guidance, resulting in successful project completion.

Assisted in teaching Logic classes, enhancing student understanding and engagement.

Prepared and graded exams, ensuring fair assessment and timely feedback.

Conducted research in NLP, contributing to the creation of corpus for IberLEF eHealth Challenges.

Achieved notable results in IberLEF eHealth Knowledge Discovery Challenge 2021.

Won awards at school and national levels in various Student Congresses.

Presented findings at the XVI COMPUMAT 2019 International Congress.

Built a web app for psychological testing, increasing talent selection accuracy through automated assessments. This helped streamline the hiring process and improve candidate evaluation.

Carl Jung's personality theory was applied to improve psychological profiling and make tests more reliable.

Added a CMS system to create new psychological tests easily, speeding up test creation. This allowed the team to design and deploy customized assessments without technical assistance quickly.