Mrs. Teresa Peixoto | Data Quality in Smart Manufacturing | Young Scientist Award

📌 Education 

Teresa Peixoto is currently pursuing a Master’s Degree in Computer Engineering at the School of Technology and Management – IPP (2023–Present), focusing on advanced computing techniques and software engineering principles. She previously earned her Bachelor’s Degree in Computer Engineering (2019–2023) from the same institution, where she gained extensive experience in software development, databases, and system architecture. During her studies, she actively engaged in academic projects, including Portugal Transports, a microservices-based system improving train travel experiences, and HereNow, a blockchain-powered event participation and NFT-based POAP management platform. Her academic journey is complemented by extracurricular involvement, including her leadership role in the ESTG Academic Female Musical Group, AvenTUNA, and her participation in school sports as a speed skater. Teresa’s dedication to education and hands-on learning has equipped her with technical proficiency in programming languages, agile methodologies, and data management strategies essential for her career in software engineering.

📌 Experience 

Teresa Peixoto is a Student Researcher at CIICESI (Feb 2024–Present) in Porto, Portugal, contributing to the PRODUTECH R3 project. She researches and develops methods for data quality management in big data, data streaming, and Industry 4.0, utilizing Python, Data Profiling, IoT, and Data Quality Metrics. Previously, she worked as a Full-Stack Developer Intern at BIMMS (Feb 2023–June 2023), where she improved the Digi4Construction digital platform. Her key contributions included automated project status reports, an intuitive interface for report customization, and JSON data integration to enhance functionality. She has also developed innovative academic projects such as Portugal Transports, a microservices-based system for train journey optimization, and HereNow, a Web3 event participation and POAP management platform. Teresa’s experience spans backend and frontend development, database management, and software architecture, making her a well-rounded engineer ready to tackle complex software challenges.

📌 Awards & Honors 

Teresa Peixoto has demonstrated excellence in both technical and extracurricular fields, earning recognition for her academic achievements, leadership, and innovation. During her tenure as President of AvenTUNA (2022/2023), she led the group to multiple performances and competitions, fostering a strong academic culture. In competitive programming and hackathons, she received accolades for her innovative solutions in software development and data quality research. Her Portugal Transports project, developed as part of her academic work, was recognized for its efficient microservices architecture and real-world applicability in smart transportation. Additionally, her blockchain-based HereNow project received praise for integrating NFT technology into event management. Teresa also excelled in speed skating from 2012 to 2019, competing at a high level and showcasing her dedication and discipline. Her commitment to software engineering, data quality research, and leadership continues to earn her recognition in both academic and professional circles.

📌 Research Focus  

Teresa Peixoto’s research focuses on data quality management in big data, Industry 4.0, and data streaming environments. As part of her role at CIICESI, she contributes to the PRODUTECH R3 project, developing advanced methods for ensuring data integrity and accuracy. Her work revolves around data profiling, data quality dimensions, data metrics, and IoT-based data validation, leveraging Python and machine learning techniques to enhance data reliability. Teresa is particularly interested in how AI and automation can optimize real-time data processing in smart manufacturing. Her academic projects, such as Portugal Transports and HereNow, reflect her expertise in integrating modern technologies like microservices, blockchain, and real-time analytics into practical applications. Through her research, Teresa aims to address challenges in data governance, anomaly detection, and predictive analytics, contributing to the advancement of data-driven decision-making in industrial and smart factory environments.