جست‌وجوی استاد و پژوهشگر

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

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.

Marco Antonio Casanovaمشاهده پروفایل

استاد

• Database Systems
• Conceptual Modeling
• Semantic Web
• +۵ مورد دیگر

Marco Antonio Casanova is a Full Professor at the Department of Informatics and Coordinator of the Central Planning and Evaluation Office of the Pontifical Catholic University of Rio de Janeiro (PUC-Rio). He has held significant leadership positions at PUC-Rio including Graduate Program Coordinator (2005-2007) and Director of the Department of Informatics (2007-2011). His research interests concentrate on database conceptual modeling, construction of database management systems, and applications of Large Language Models. Dr. Casanova's work focuses on technologies that facilitate the dissemination and interpretation of data on the Web, with particular emphasis on techniques for designing databases to facilitate interoperability. His academic journey began with a degree in Electronic Engineering from the Military Institute of Engineering (1974), followed by an M.Sc. in Informatics from PUC-Rio (1976), and culminated with an M.Sc. (1978) and Ph.D. (1979) in Applied Mathematics from Harvard University. His recent publications (2023-2025) demonstrate a strong focus on the intersection of Large Language Models with database technologies, particularly in developing advanced Text-to-SQL and Text-to-SPARQL systems. His research spans both theoretical database concepts and practical applications across various domains including engineering, healthcare, and cultural heritage. Dr. Casanova has been particularly active in exploring how LLMs can enhance traditional database query interfaces while addressing real-world challenges in complex database environments. Scientific Recognition: Recipient of the Scientific Merit Award from the Brazilian Computer Society (2012) CNPq Level 1B Productivity Grant recipient Dr. Casanova maintains an active research program with numerous collaborations across Brazil and internationally. His work bridges theoretical database research with practical applications, particularly in the evolving landscape of AI-enhanced database systems. He has contributed significantly to the field of semantic technologies, knowledge graphs, and natural language interfaces to databases, with a recent emphasis on leveraging Large Language Models to solve longstanding database interoperability challenges. His laboratory and research team at PUC-Rio focus on developing innovative approaches to database management that incorporate cutting-edge AI techniques while maintaining strong theoretical foundations in database systems.

Haniel Barbosaمشاهده پروفایل

استادیار

• SMT Solvers
• Formal Verification
• Proof Certificates
• +۵ مورد دیگر

Haniel Barbosa is a tenured Assistant Professor in the Department of Computer Science at Universidade Federal de Minas Gerais (UFMG), Brazil. His research focuses on improving SMT solvers for formal verification and enhancing their trustworthiness through proof certificates, as detailed in his work on projects like Lean-SMT and Carcara. He also serves as a senior technical lead for the state-of-the-art SMT solver cvc5 and actively collaborates with institutions like the University of Iowa, Stanford University, and Inria Nancy. Barbosa's research is supported by grants from the Defense Advanced Research Projects Agency (DARPA), CAPES, and Amazon Web Services. He mentors a diverse team of postdoctoral scholars, PhD students, and MSc students, including Caio Raposo, Tomaz Mascarenhas, Pedro Saccomani, and Bruno Andreotti. His teaching portfolio includes courses like Introduction to Computational Logic, Theory and Practice of SMT Solving, and Formal Methods. His publications span topics such as SMT proof production, proof reconstruction, and syntax-guided synthesis, with a focus on scalable algorithms, higher-order logic extensions, and industrial-strength solver development. Key trends in his work include formal verification, automated reasoning, and the intersection of logic with software engineering. Scientific awards include the Distinguished Tutorial Paper Award at FM 2024 and the Best Tool Paper Award at TACAS 2022 . Barbosa also contributes extensively to academic service as a steering committee member for SBMF, PC chair for LSFA and SBMF conferences, and organizer for SMT-COMP. His outreach includes invited tutorials at ATVA 2024, Dagstuhl Seminars, and workshops on SMT solving.

Melissa Lemos Cavaliereمشاهده پروفایل

استاد

• Big Data
• Streaming Systems
• Web Development
• +۲ مورد دیگر

Melissa Lemos Cavaliere serves as a Tenured Professor in the Department of Computer Science at the Pontifical Catholic University of Rio de Janeiro (PUC-Rio) and holds a research position at the Tecgraf Institute. Her academic responsibilities include teaching undergraduate courses in Big Data & Streaming Systems and Web Development, with emphasis on practical implementation using technologies such as Cassandra, Kafka, HTML/CSS, JavaScript, Bootstrap, and Meteor. Her research and teaching focus centers on applied computing technologies, particularly real-time data processing, distributed systems, and full-stack web application development. Through project-based courses like Supervised Internship (Estágio Supervisionado), she guides students in building production-ready software solutions using modern frameworks and database systems including MongoDB, emphasizing industry-relevant software engineering practices. Professor Cavaliere actively supervises student projects through the Supervised Internship program where participants develop complete software solutions. Her work with Tecgraf Institute indicates involvement in applied research projects bridging academic theory and industrial implementation, though specific grant details are not documented in available sources. She maintains strong institutional ties with Tecgraf Institute at PUC-Rio, a research center specializing in computer graphics, interactive systems, and software development for both academic and industrial applications, contributing to technological innovation in Brazil's tech ecosystem.

Andrew Diniz da Costaمشاهده پروفایل

استاد

• Software Engineering
• Computer Science Education
• Software Architecture
• +۷ مورد دیگر

Andrew Diniz da Costa is a Professor and Researcher at the Computer Science Department of Pontifical Catholic University of Rio de Janeiro (PUC-Rio), where he has worked since 2014. He is also a mentor in the Apple Developer Academy | PUC-Rio program and collaborates with the Software Engineering Laboratory (LES). His expertise spans software engineering, education, and innovation. Education: Bachelor's, Master's, Doctorate, and Postdoctoral degrees in Computer Science from PUC-Rio (2002-2013) Technical Schooling at IBPI (1999-2001) Andrew specializes in software architecture, processes, requirements, and quality, with a focus on integrating pedagogical methodologies like Challenge-Based Learning (CBL) into technology education. He leverages Apple technologies to enhance in-person, remote, and hybrid learning experiences, emphasizing practical, motivating iOS development training. Scientific Awards: Apple Distinguished Educator (2023) With over 20 years of software development experience, he has mentored hundreds of iOS developers through the Apple Developer Academy. His work bridges software engineering research and educational innovation, emphasizing collaborative methodologies and real-world applications. Research Affiliation: Software Engineering Laboratory (LES), PUC-Rio

• Computer simulation of nanomaterials
• Quantum materials
• 2D and topological materials
• +۴ مورد دیگر

Dr. Marcos Gonçalves de Menezes serves as an Associate Professor at the Institute of Physics, Federal University of Rio de Janeiro (UFRJ), where he maintains an active research program in computational materials physics while teaching core undergraduate courses including Electromagnetism 1 & 2, Physics 1 & 3, and Condensed Matter Physics. His research focuses on computer simulation of nanomaterials, quantum materials, 2D and topological materials, semiconductors, defects, surfaces, interfaces, heterostructures, and energy conversion and storage . He employs computational methods to investigate electronic properties at the nanoscale, with particular emphasis on novel materials systems for next-generation electronic and energy applications. Dr. Menezes holds a CNPq Research Productivity Scholarship at Level 2, recognizing his significant contributions to Brazilian science. His publication record includes 31 papers with 330 citations and an h-index of 11 according to Web of Science (August 2025). He actively contributes to educational outreach through the Preparation Material for the Brazilian Physics Olympiad (OBF) initiative, where he supervises undergraduate students developing solutions to competition problems. Additionally, he is a key member of the NAMOR Group (Nanoscience Modeling in Rio), which focuses on quantum materials research. His teaching methodology incorporates both traditional classroom instruction and digital resources, with courses featuring comprehensive lecture notes, exercise lists, and virtual learning environments. Current teaching responsibilities include courses scheduled through the 2025 academic year, demonstrating his active faculty status.