جستجوی استاد راهنمای دانشگاهی

• 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.

Peter Wankeمشاهده پروفایل

استاد

• Soft computing applications in business
• Multicriteria modeling for sectoral benchmarking
• Information theory in business analytics and economics
• +۳ مورد دیگر

Peter Wanke is a Full Professor of Data Science & Business Analytics at COPPEAD/UFRJ and a Joint Appointment Professor at EBAPE/FGV. He has coordinated the Graduate Program in Business Administration at COPPEAD (2018-2021) and the Doctoral Program in Administration since 2011. He leads the Business Analytics and Economics Research Unit (BAE RU) and has published over 200 high-impact journal articles. B.Sc. in Production Engineering (Poli/UFRJ) M.Sc. and D.Sc. in Production Engineering (COPPE/UFRJ) Visiting Scholar at Ohio State University Research Focus: Soft computing in business (finance, marketing, logistics), multicriteria benchmarking in public management, infrastructure, and finance, with applications of information theory to business analytics and economics. His work spans decision-making modeling, efficiency analysis, and data-driven solutions for global sectors. Scientific Recognition: He has received multiple awards, including the IEOM Outstanding Researcher title (2020), CNPq and FAPERJ scholarships, and global influence rankings in PLOS Biology. He serves as Associate Editor for journals like Socio-Economic Planning Sciences and Tourism Economics.

Waldemar Celes Filhoمشاهده پروفایل

دانشیار

• Computer Graphics
• Scientific Visualization
• Numerical Simulation
• +۵ مورد دیگر

Waldemar Celes Filho is an Associate Professor in the Department of Computer Science at Pontifical Catholic University of Rio de Janeiro (PUC-Rio) and serves as Director of the Tecgraf Institute/PUC-Rio. With a career spanning over three decades, he has established himself as a leading researcher in computer graphics and scientific visualization. His educational background includes a Civil Engineering degree from UFRJ (1986), a Master's in Civil Engineering from PUC-Rio (1990), a Doctorate in Computer Science from PUC-Rio (1995), and postdoctoral studies in Computer Graphics at Cornell University (1995-1997). Dr. Celes Filho's research focuses primarily on Computer Graphics with special emphasis on Scientific Visualization, Numerical Simulation, Distributed Visualization, and Real-Time Rendering. He is particularly known for his work on visualization techniques for black oil reservoir models and as a co-creator of the Lua programming language. His research has resulted in over 50 publications spanning nearly three decades, with consistent output continuing through 2025. His recent publications demonstrate a strong trend toward applying advanced visualization techniques to complex industrial problems, particularly in petroleum engineering and construction informatics. His work bridges theoretical computer graphics with practical applications in engineering domains, showing particular strength in volume rendering, CAD model visualization, and distributed rendering systems. As Director of the Tecgraf Institute, he leads research initiatives that connect academic work with industry applications, fostering collaborations that translate visualization research into practical tools. Dr. Celes Filho has mentored numerous students who have become co-authors on his publications, including Paulo Ivson, Fábio Markus Miranda, and Lucas Caracas de Figueiredo, among others. His work continues to be influential in both academic and industrial settings.

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.

Joaquim Armando Pires Jorgeمشاهده پروفایل

استاد

• Computer Graphics
• Virtual Reality
• Human-Computer Interaction
• +۵ مورد دیگر

Joaquim Armando Pires Jorge is a Full Professor at Instituto Superior Técnico, University of Lisbon, where he holds the UNESCO Chair on AI & Virtual Reality. He is also an Adjunct Full Professor at Victoria University of Wellington and an Honorary Invited Professor at the Catholic University of Rio de Janeiro. His career spans AI, VR, and human-centered computing, with leadership roles in IEEE Computer Society, ACM/SIGGRAPH, and Eurographics. Teaching: Computer Graphics, VR, and Human-Computer Interaction (HCI) Leadership: IEEE Computer Society Board of Governors (2023–present), ACM Europe Council (2015–2019) Research: 400+ peer-reviewed publications, focusing on VR, AI ethics, and interactive systems Jorge’s research bridges theoretical and applied computing, emphasizing ethical AI, reproducible science, and immersive technologies. His work includes foundational contributions to pseudo-haptics, gamification in education, and 3D user interfaces. He advocates for open science and global collaboration in XR (Extended Reality) development. His publications span topics like NFTs, remote assistance in MR (Mixed Reality), and gamified learning analytics, reflecting a career dedicated to innovation in graphics, interaction, and education. Notable awards include IEEE Fellow (2025), IEEE Golden Core (2024), and IFIP Silver Core (2014). He has supervised 18 doctoral theses and 70+ MSc dissertations, including Pedro Duarte Parreira’s Fraunhofer-winning MSc thesis (2016). As Editor-in-Chief of Computers & Graphics (since 2007) and IEEE Computer Society Publications Board member (2025–present), he shapes academic discourse in computing. Selected Awards IEEE Fellow (2025) Golden Core Award (2024) IFIP Silver Core (2014) Best Paper Award, IEEE CG&A (2011) Fellow, Eurographics Association (2010)

Augusto Baffaمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Decision-making under Uncertainty
• Electronic Game Development
• +۱ مورد دیگر

Augusto Baffa is an Associate Professor at the Department of Informática, Pontifical Catholic University of Rio de Janeiro (PUC-Rio). He coordinates the Computer Engineering undergraduate program and serves as a Laboratory Collaborator at ICAD/IGames/VisionLab. His research focuses on Artificial Intelligence for electronic games and decision-making under uncertainty. Key research areas include: Artificial Intelligence Decision-making under Uncertainty Electronic Game Development He teaches courses like INF1010 (Advanced Data Structures), INF1031 (Introduction to Computing), and INF1771 (Artificial Intelligence). Contact details include office extension +55 21 3527-1500 (room 417 RDC) and personal website augustobaffa.pro.br . Collaborations include development of Woofy chatbot and Drone Challenge AI competitions.

Hélio Cortes Vieira Lopesمشاهده پروفایل

دانشیار

• Data Science
• Machine Learning
• Process Mining
• +۹ 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).

Adriano Francisco Brancoمشاهده پروفایل

استاد

• Internet of Things (IoT)
• Wireless Sensor Networks
• Embedded Systems
• +۸ مورد دیگر

Adriano Francisco Branco is a Tenured Professor in the Computer Science Department at Pontifical Catholic University of Rio de Janeiro (PUC-Rio). He also serves as a researcher and mentor in technological innovation programs, with affiliations to initiatives like ExACTa, Gist LabLua, and Tecgraf at PUC-Rio. PhD in Computer Science (2015) and Master's in Computer Science (2011) from PUC-Rio Bachelor's in Electronic Engineering from CEFET/RJ (1992) His research focuses on bridging distributed systems, IoT, wireless sensor networks, embedded systems, and data science, with emphasis on practical applications in industrial and energy sectors. He leads projects in collaboration with oil & gas and telecommunications companies, integrating energy harvesting and edge AI techniques. Key scientific recognition includes the FAPERJ Excellence Award (Grade 10) .

Raul Pierre Renteriaمشاهده پروفایل

استاد

• Computer Science
• Artificial Intelligence
• Data Science
• +۳ مورد دیگر

Raul Pierre Renteria serves as a Tenured Professor in the Computer Science Department at Pontifical Catholic University of Rio de Janeiro (PUC-Rio), contributing to academic instruction and departmental initiatives within the university's technical education framework. His research spans foundational and applied domains of computing, with emphasis on: Artificial Intelligence Data Science Software Engineering Algorithms Computer Networks Computer Science Professional correspondence may be directed to renteria@inf.puc-rio.br . No documented scientific awards or honors were specified in the source material. Information regarding graduate student supervision, research funding, or laboratory affiliations remains unavailable in the provided context.

Eduardo Sany Laberمشاهده پروفایل

دانشیار

• Algorithm Design
• Machine Learning
• Optimization
• +۵ 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 .

• Data Visualization
• Scientific Visualization
• Computer Graphics
• +۶ مورد دیگر

João Luiz Dihl Comba is a Professor at the Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Brazil. With a PhD in Computer Science from Stanford University (1993-2000) under advisor Leonidas J. Guibas, he has established himself as a leading researcher in visualization and computer graphics. His academic journey includes a M.Sc. in Systems Engineering and Computing from UFRJ (1988-1991) and a B.Sc. in Computer Science from UFRGS (1983-1987), along with a sabbatical at the University of Utah (2010-2011). Comba's research focuses on data and scientific visualization, visual analytics, computer graphics, and their applications in medical imaging, sports analytics, and pandemic response. His work bridges theoretical advances in multidimensional projections with practical applications in healthcare, oil and gas, and digital twins. Recent publications demonstrate his continued leadership in applying machine learning techniques to visualization problems, particularly in biomedical contexts. His publication record spans over three decades with consistent output through 2025, showing evolution from foundational computer graphics work to contemporary applications of AI in visualization. The publications reveal strong collaborations with researchers across Brazil and internationally, with particular emphasis on solving real-world problems through visual analytics. As an advisor, Comba has mentored numerous graduate students who have become active researchers in visualization and computer graphics, with several continuing to collaborate with him on publications. His research group at UFRGS appears to be particularly strong in medical visualization applications, as evidenced by multiple recent publications related to COVID-19 analysis and medical image processing.

• Condensed Matter Physics
• Superconductivity
• Phase Transitions
• +۵ مورد دیگر

Vitorvani Soares is an Associate Professor in the Department of Mathematical Physics at the Institute of Physics, Federal University of Rio de Janeiro (UFRJ), where he has been a faculty member since 1994. He holds a BSc (1981) and MSc (1984) from UFRJ, and a PhD (1991) from the University of Lausanne, Switzerland, where he also completed postdoctoral research and served as a professor until returning to UFRJ. He coordinates UFRJ's Physics Degree program and is a faculty member of the Master's Program in Physics Teaching. His research focuses on condensed matter physics , including adiabatic nucleation, superconductivity, refractory metals, and phase transitions, with recent extensions to relativistic thermodynamics and cosmological fluids. He maintains active interests in physics education, developing innovative teaching methodologies and experimental demonstrations for thermodynamics, kinematics, and astronomy. Publication trends show dual emphasis: (1) Fundamental condensed matter research on nucleation theory and superconducting junctions (1990s-2011), and (2) Physics education innovations, particularly kinematics paradoxes, thermodynamic experiments, and astronomy pedagogy (2010-present). His educational works frequently employ geometric modeling, low-cost experiments, and historical context to resolve conceptual challenges. He has supervised over 40 students, including 2 PhDs, 8 MSc candidates, and 30+ undergraduate researchers. Major advising themes include experimental thermodynamics (e.g., Boltzmann constant measurement), kinematics paradoxes, astronomy education, and superconductor applications. No awards or dedicated lab spaces are mentioned, though he collaborates on experimental work in superconductivity and material science.

Marco Molinaroمشاهده پروفایل

استاد

• Online Algorithms
• Convex Optimization
• Machine Learning
• +۵ مورد دیگر

Marco Molinaro is a Professor in the Computer Science Department at PUC-Rio . He previously held Assistant Professor positions at TU Delft (EWI), Georgia Tech (ISyE, ACO), and was a PhD student in the ACO program at Carnegie Mellon University . Education: PhD in Algorithms, Combinatorics, and Optimization (ACO), Carnegie Mellon University Research Interests: Marco's work lies at the intersection of online algorithms , convex optimization , machine learning , and operations research . His recent publications analyze: Online scheduling and VM allocation in data centers Complexity of branch-and-bound trees Information-theoretic bounds for optimization problems Explainable decision trees and their theoretical limits Stochastic and adversarial bandit algorithms Curvature properties in optimization sets His research often bridges abstract mathematical frameworks (e.g., Lipschitz functions, supermodular norms) with practical applications in cloud computing, machine learning, and game theory. Publication Trends: Marco's recent work focuses on online convex optimization and its extensions to data center resource allocation (Kamino: latency-driven VM scheduling), dynamic bin packing , and information complexity in mixed-integer models. He frequently collaborates with researchers at institutions like Carnegie Mellon University and TU Delft, with recurring co-authors Santanu Dey, Amitabh Basu, and Thomas Kesselheim. Teaching: Marco teaches advanced courses in algorithm design and analysis at PUC-Rio, including: Analise de Algoritmos (2020–2025) Projeto e Analise de Algoritmos (postgraduate, 2020–2025) Algoritmos e Incerteza (postgraduate, 2020) Estruturas Discretas (2021) His curriculum emphasizes online learning , random-order models , and PAC learning , with connections to game theory and practical implementations.

Joísa de Souza Oliveiraمشاهده پروفایل

استاد

• Computer Science
• Artificial Intelligence
• Data Structures
• +۳ مورد دیگر

Joísa de Souza Oliveira is a Tenured Professor at the Computer Science Department of Pontifical Catholic University of Rio de Janeiro (PUC-Rio). Her work focuses on foundational areas of computer science including algorithms, data structures, and software engineering. She can be contacted via email at joisa@inf.puc-rio.br.

José Carlos Ramalho Moreiraمشاهده پروفایل

استادیار

• Computer Science
• Software Engineering
• Data Structures
• +۳ مورد دیگر

José Carlos Ramalho Moreira is an Assistant Professor at the Computer Science Department of the Pontifical Catholic University of Rio de Janeiro (PUC-Rio), affiliated with the School of Engineering . His academic role centers on teaching and research within computer science disciplines. Fields of Interest: Computer Science, Software Engineering, Data Structures, Algorithms, Databases, Artificial Intelligence