جستجوی استاد راهنمای دانشگاهی

Fabrício Benevenuto is an Associate Professor in the Computer Science Department at Federal University of Minas Gerais (UFMG), where he conducts interdisciplinary research at the intersection of social media analysis, data science, and computational journalism. His work spans complex networks, machine learning, and natural language processing with strong societal impact. His research focuses on social media dynamics, particularly in Brazilian contexts, with major contributions to hate speech detection, fake news analysis, and political discourse monitoring. He leads large-scale projects against misinformation, including development of systems like WhatsApp Monitor, Media Bias Monitor, and Purple Feed. His work combines technical innovation with real-world applications for election transparency and public discourse integrity. Benevenuto's recent publications demonstrate strong trends in multilingual NLP for social media analysis, with emphasis on Brazilian Portuguese contexts. His team produces both theoretical contributions and practical systems addressing hate speech, misinformation, and media bias. Notable methodological approaches include combining network analysis with linguistic features, developing culturally-aware detection systems, and creating large annotated datasets for understudied languages. CAPES award for best Brazilian computer science thesis (2010) Humboldt Foundation scholarship recipient (2017-2018) Member of TikTok Safety Advisory Council WWW'20 Best Paper Nominee & CNIL-INRIA Privacy Protection Prize winner Multiple best paper awards at CEAS, WBC, and ICWSM conferences Test-of-Time Award at ICWSM'20 Benevenuto actively mentors PhD and MSc students, with numerous advisees securing academic positions at Brazilian universities and research roles at institutions like Max Planck Institute. His projects often receive funding supporting interdisciplinary collaborations across computer science and social sciences. Current work includes large-scale analysis of Telegram political groups, real-time election monitoring systems, and developing culturally-aware NLP tools for Portuguese. He leads research teams working on social media analysis systems with societal impact, particularly focused on Brazilian digital ecosystems. Projects involve cross-institutional collaborations with researchers from MPI-SWS, Max Planck Institute, and various Brazilian universities, emphasizing practical applications for public discourse integrity.

• Social Media Analysis
• Sentiment Analysis
• Computational Journalism
• +۶ مورد دیگر

Hélio Cortes Vieira Lopes is an Associate Professor at the Department of Informatics of the Pontifical Catholic University of Rio de Janeiro (PUC-Rio) . He joined PUC-Rio in 1996, initially working in the Mathematics Department before transitioning to the Computer Science Department (now Informatics) in 2012. He has also held a Visiting Scholar position at Purdue University in 2001. Education: PhD in Mathematics (1996), Master’s in Informatics (1992), and Bachelor in Computer Engineering (1990), all from PUC-Rio. Research Interests: Hélio focuses on developing advanced mathematical and computational techniques for real-world problems, with recent emphasis on Data Science , Machine Learning , and Process Mining in cloud computing and uncertainty quantification. His work spans Computer Graphics and Visualization , Mesh Generation , Computational Geometry and Topology , and Quantitative Methods for Insurance and Finance . He has applied these techniques to industries like oil, banking, and insurance. Scientific Awards: He received the Business Process Intelligence Challenge (BPIC) Best Report Award in 2017. He also holds productivity grants from CNPq, FAPERJ, CAPES, and FINEP. Advising and Industry Collaboration: Hélio has advised over 80 graduate students and collaborated with companies such as PETROBRAS , VALE , BANCO DO BRASIL , and GLOBO.COM . He has served as an associate editor for journals like Computers & Graphics and IEICE Nonlinear Theory and Its Applications . Laboratories and Initiatives: He leads the DASLAB (Data Science Laboratory) and the ExACTa initiative, while also co-coordinating the GALGOS Laboratory (optimization algorithms) and collaborating with the IDEIAS Laboratory (human-computer interaction and visualization).

• Data Science
• Machine Learning
• Process Mining
• +۹ مورد دیگر

Valeria de Paiva is a mathematician and AI research scientist, currently serving as Founder of the Topos Institute in Berkeley where she explores the deep connections between mathematics, logic, and computation. She earned her PhD under the supervision of Martin Hyland, working on Dialectica categories, which established her foundational work connecting linear logic with Gödel's Dialectica interpretation. Dr. de Paiva's research spans category theory, programming languages, type theories, and logic in computer science, with special emphasis on the semantics of natural language and lexical semantics. She has pioneered work in linear and modal logics and their applications to mathematics, particularly in building tools to extract, structure, and reason about mathematical knowledge. Her research bridges symbolic/structural and distributional meaning representations through knowledge graphs, ontologies, and computational frameworks. Her recent publications reveal a strong trend toward mathematical concept extraction and natural language processing for mathematical texts. She has developed innovative approaches like MathGloss for building mathematical glossaries and Parmesan for educational concept extraction, demonstrating how theoretical foundations in category theory can solve practical problems in knowledge representation and education. Among her notable recognitions is the unofficial title of 'Ambassador of Logic,' awarded after she was invited by the Division of Logic, Methodology, and Philosophy of Science and Technology to record a video on logic. She has served as council member of this division from 2020-2023. Dr. de Paiva is deeply committed to mentoring and supporting women in logic and computer science. She has mentored 12 PhD students and postdocs at the Applied Category Theory MRC 2022. She co-founded and maintains the Women in Logic website, blog, and Facebook group, serves on the steering committee for Women in Logic, and helps organize the Workshop on Women in Logic, which has held nine editions as of the latest information. She also contributes to the ACM-W Scholarship Program supporting women students in computing worldwide. She is actively involved in numerous academic initiatives including serving as co-chair for CICM 2025 and MFPS 2024, and as scientific committee member for CT2025. She co-founded groups including Women in Logic, Lógicas Brasileiras, and the Women in Logic Workshop, and has organized numerous international conferences and workshops focused on logic, category theory, and computational semantics.

• category theory
• programming languages
• type theories
• +۱۲ مورد دیگر

Eduardo Sany Laber is an Associate Professor in the Computer Science Department at Pontifical Catholic University of Rio de Janeiro (PUC-Rio), with over two decades of academic and industrial experience. He completed his undergraduate (1996), master's (1997), and doctorate (1999) at PUC-Rio, focusing on data compression. Since 2001, he has been a faculty member, with visiting roles at Carnegie Mellon University (2001-2002). Education : PhD in Computer Science (1999), PUC-Rio Master in Computer Science (1997), PUC-Rio BSc in Computer Engineering (1996), PUC-Rio His research centers on designing algorithms with theoretical guarantees for problems in data compression , machine learning , and finance , combining optimization, information theory, and industrial applications. His recent work explores connections between k-means and decision trees , alongside information-theoretic clustering . The 15 most recent publications highlight his focus on algorithm efficiency, spanning machine learning , information retrieval , and combinatorial optimization . Notable venues include ICML , ECAI , and ISAAC , with applications in finance , data analysis , and web engineering . Scientific Awards : Gold Medal, Brazilian Math Olympiad (1990) Bronze Medal, International Math Olympiad (1991) First Prize, Brazilian Computer Society PhD Thesis Contest (2000, 2004 co-advisor) Affiliated Member, Brazilian Academy of Sciences (2008) Best Paper Award, ISAAC (2015) Laber supervises PhD and Master's students intensively, including recipients of national awards like the Brazilian Computer Society's First Prize for Marco Molinaro's Master's Dissertation (2009) and Second Prize for Renato Carmo's PhD Thesis (2006) . He is a CNPq Level 1 Researcher and collaborates with the Greyhounds Laboratory .

• Algorithm Design
• Machine Learning
• Optimization
• +۵ مورد دیگر

Marcos Kalinowski is an Associate Professor at the Department of Informatics, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), where he has served as a faculty member since 2017. He is the co-founder and coordinator of the ExACTa PUC-Rio laboratory, General Chair of the International Conference on Software Engineering (ICSE) 2026, and Associate Editor of the Journal of Systems and Software. His academic affiliations also include membership on the steering committees of ICSE and the Ibero-American Conference on Software Engineering (CIbSE), as well as being a Senior Advisor and Lead Appraiser for the Brazilian Software Quality Program (MPS.BR). Dr. Kalinowski earned his Ph.D. and M.Sc. in Software Engineering from COPPE/UFRJ under advisor Guilherme Travassos, and his B.Sc. in Computer Science from UFRJ. His academic career includes previous faculty positions at Fluminense Federal University (UFF) from 2014-2017 and the Federal University of Juiz de Fora (UFJF) from 2012-2014. His research focuses on bridging software engineering and data science, with particular emphasis on developing reliable and maintainable AI/ML systems through rigorous engineering practices. His work addresses critical challenges in requirements engineering for ML-enabled systems, investigating how to effectively specify quality attributes and functional requirements for complex AI applications. His research on software process and product quality emphasizes agile methods adapted to modern data-intensive development contexts. Through experimental software engineering approaches, he validates these methods through empirical studies in both academic and industrial settings. His work has significantly contributed to establishing Software Engineering for Data Science as a distinct discipline, including creating Brazil's first extension course on the subject in 2021. His publication record demonstrates a strong focus on the intersection of software engineering and artificial intelligence, with recent work addressing technical debt in ML systems, requirements engineering for AI, and lean methodologies for industry-academia collaboration. His research shows a clear trajectory toward making AI development more systematic, reliable, and aligned with software engineering best practices, evidenced by his over 160 scientific publications and multiple books including the Jabuti Acadêmico award-finalist 'Engenharia de Software para Ciência de Dados' (2023). Dr. Kalinowski has received numerous prestigious awards including: CNPq Research Productivity Grant (Level 1D, 2024-2028) FAPERJ Scientist of Rio de Janeiro State Distinction (2024) Multiple best paper awards at international conferences including SWQD 2025 and CAIN 2024 Recognition as advisor of multiple award-winning Ph.D. and M.Sc. theses SBES 2024 Advisor of the Best Brazilian Software Engineering Ph.D. Thesis As an academic leader, Dr. Kalinowski has supervised numerous doctoral and master's students, many of whom have received national awards for their research. He has secured significant research funding from Brazilian Research Council (CNPq) and Rio State Agency (FAPERJ), as well as industry collaborations with major organizations including CEPEL, Eletrobras, Galp, Petrobras, and Stone. His laboratory, ExACTa PUC-Rio, has established successful industry partnerships through its Lean R&D approach, creating a robust pipeline between research and practical application. Dr. Kalinowski leads the ExACTa PUC-Rio laboratory which focuses on applying lean R&D methodologies to industry-academia collaboration projects. He also created and coordinates PUC-Rio's specialization courses in Software Engineering and Full Stack Development through CCEC PUC-Rio, demonstrating his commitment to bridging academic research with industry needs. His leadership in bringing ICSE 2026 to Brazil represents a significant milestone for the software engineering community in Latin America.

• Software Engineering for Data Science and Artificial Intelligence
• Requirements Engineering
• Software Process and Product Quality
• +۳ مورد دیگر

Simone Diniz Junqueira Barbosa is an Associate Professor at the Informatics Department of Pontifical Catholic University of Rio de Janeiro (PUC-Rio). She leads the IDEIAS-SERG lab, focusing on Human-Computer Interaction (HCI) and Information Visualization research. Her work spans model-based interactive systems design, visual analytics, digital storytelling, and AI techniques for improving system usability and accessibility. Her research explores: Model-based approaches for interactive systems Data science and visual analytics for complex datasets Digital storytelling techniques Accessibility and usability enhancement through AI Semiotic engineering foundations for HCI Publication analysis reveals strong emphasis on HCI methodologies, data visualization literacy, ethical AI development, and applications in legal informatics/industrial automation. Recent works focus increasingly on explainable AI, visualization cognition, and ethical ML practices. Awards & Honors: IFIP TC13 Pioneer Award (2019) Outstanding HCI Career Award (Brazilian Computer Society, 2020) Selo de Inovação SBC Innovation Award (2022) IFIP Fellow Award (2024) She has advised over 45 graduate students (PhD/MSc) and coordinates multiple labs including DasLab, ExACTa, and Americanas Futuro Lab. Funded projects include CNPq, FAPERJ, Microsoft Research, and Petrobras collaborations focusing on HCI innovations and data visualization tools. Leads the IDEIAS-SERG research group merging semiotic engineering with interaction design. Serves on steering committees for ACM CHI and IFIP TC13, previously co-edited ACM Interactions Magazine (2016-2019).

• Human-Computer Interaction
• Information Visualization
• Model-based Interactive Systems Design
• +۷ مورد دیگر