Professor Auxiliar, FCUP – Universidade do Porto, Portugal
Profile
Orcid
Álvaro Figueira is a distinguished academic and researcher in the field of Computer Science, currently serving as a Professor (Prof. Auxiliar) at Universidade do Porto, Faculdade de Ciências in Portugal. With a robust academic background and extensive experience, his research focuses on data mining, machine learning, social network analysis, and eLearning. Figueira’s passion for technology and innovation is evident in his contribution to various scientific fields, including data visualization and text mining, where his work aims to bridge theory with practical applications. With years of experience in teaching and leading research initiatives, Figueira is a prominent figure in his discipline. 📚💻
Education
Álvaro Figueira’s academic journey is distinguished by his advanced qualifications in Computer Science. He obtained his Bachelor’s (BSc) degree from Universidade do Porto, followed by a Master’s (MSc) from Imperial College London. He continued his academic excellence by completing a Ph.D. at Universidade do Porto in 2004, where he focused on Computer Science. Additionally, Figueira pursued Post-Graduation in Business Intelligence and Analytics at Porto Business School in 2017, further enhancing his expertise. 🎓📖
Experience
Throughout his career, Álvaro Figueira has amassed a wealth of academic and professional experience. He is currently a Professor at Universidade do Porto, where he teaches and supervises students in the field of Computer Science. He has also worked on a variety of research projects related to eLearning, data science, and machine learning, particularly focused on how these technologies can improve education and business practices. His previous experience includes a prestigious Master’s thesis position at Imperial College London. 🌍📊
Research Interests
Álvaro Figueira’s research interests span a wide array of cutting-edge fields within Computer Science. His primary focus areas include Data Mining, Text Mining, Machine Learning, Social Network Analysis, Data Visualization, and eLearning. Figueira’s work aims to apply computational techniques to improve the analysis of large datasets, making significant strides in understanding and enhancing social networks and educational systems. His research has contributed to the advancement of automated assessment systems and the optimization of learning processes. 📈🔍
Award
Álvaro Figueira’s contributions to computer science and education have been recognized with various awards and accolades. Notably, his research has been funded by several prestigious grants, including those from the Fundação para a Ciência e Tecnologia I.P. and Instituto de Engenharia de Sistemas e Computadores. His excellence in research is further highlighted by his numerous publications in top-tier journals, where he continues to make an impact in the fields of data science and machine learning. 🏆🎖️
Publications Top Notes
Álvaro Figueira’s publication record reflects his significant contributions to the fields of data science, machine learning, and eLearning. Some of his recent publications include:
“Topic Extraction: BERTopic’s Insight into the 117th Congress’s Twitterverse” – Informatics (2024).
“Clustering source code from automated assessment of programming assignments” – International Journal of Data Science and Analytics (2024).
“Comparing Semantic Graph Representations of Source Code: The Case of Automatic Feedback on Programming Assignments” – Computer Science and Information Systems (2024).
“GANs in the Panorama of Synthetic Data Generation Methods” – ACM Transactions on Multimedia Computing, Communications, and Applications (2024).
“On the Quality of Synthetic Generated Tabular Data” – Mathematics (2023).
“Bibliometric Analysis of Automated Assessment in Programming Education: A Deeper Insight into Feedback” – Electronics (2023).