As a Data Scientist and Researcher with a predoctoral grant from the Universitat Politècnica de València, I work in the Networking Research Group (GRC) of the Computer Engineering Department (DISCA). My responsibilities include:

• Developed and implemented Python-based algorithms and machine learning models for optimizing pollution-impacted vehicle routing, improving urban traffic efficiency by 20% through advanced statistical analysis and linear regression techniques.
• Designed and maintained data pipelines using Python and SQL for data cleaning, processing, and ETL, enabling the efficient organization of large experimental datasets for research and development purposes.
• Collaborated with international research teams to present findings at conferences and contributed to scientific publications on data science and traffic management, enhancing the academic community’s understanding of urban planning and data-driven solutions.
• Conducted in-depth data analysis and built predictive models using Python, Matplotlib, Seaborn, and Scikit-Learn on traffic pattern datasets, generating actionable insights and reports that influenced city planning and policy development.
• Developed data-driven research proposals and presentations, leveraging machine learning techniques to improve the clarity and impact of complex traffic and environmental data for academic and public stakeholders.

As a Visiting Researcher and Data Scientist, I've been immersed in an intensive 3-month research collaboration with DLR in Berlin. My efforts were geared towards:

• Led urban traffic management projects using Python, GIS, GeoPandas, and machine learning methods, contributing to the development of sustainable city planning frameworks by optimizing vehicle traffic flows.
• Applied statistical models and machine learning algorithms to analyze large datasets and study environmental impacts, providing data-driven recommendations to support sustainable urban development.
• Integrated external data sources and developed geospatial and predictive models using Python and Scikit-Learn for forecasting urban pollution levels, aiding policymakers in implementing effective environmental measures.
• Conducted performance monitoring and evaluation of traffic management models, identifying data drifts, deploying model updates, and optimizing model accuracy by refining data inputs and parameters.

As an Assistant Professor, I teach lab sessions for second, and third-year courses in the Bachelor's Degree in Informatics Engineering. Specifically, I teach the following courses:

• Design and Configuration of Local Area Networks (11607) (1.5 ECTS) for the group in English
• Network Technology (11579) (1.5 ECTS)
• Computer Networks (12990) (3.3 ECTS)

My main functions are:
• Developing and revising course materials such as lab manuals, assignments, and exams to ensure they align with the learning objectives of the courses.
• Providing guidance and support to students during lab sessions, office hours, and via email to help them achieve their academic goals.

As an Android Developer Intern at Sanpani, I worked on the development of an app for managing the data of biological activity in human cells. My responsibilities included:

• Collaborating with the development team to design and implement the app's features and functionality.
• Writing efficient and scalable code using Java.
• Conducting testing and debugging to ensure the app's performance and usability met the project's requirements.

Through this internship, I gained experience in developing Android applications and working in a team-based development environment.