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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.

• Computer Graphics
• Scientific Visualization
• Numerical Simulation
• +5 more

Roberta Maira de Melo serves as a Full-Time Adjunct Professor in the Department of Visual Arts at the Institute of Arts, Federal University of Uberlandia, where she has held faculty positions since 1998 and teaches in the Professional Master's Degree in Arts program. Her academic credentials include: Bachelor's degree in Art Education with Fine Arts specialization from Federal University of Uberlandia (1994) Bachelor's degree in Art Education with Decoration specialization from Federal University of Uberlandia (1993) Master's degree in Arts from University of São Paulo - ECA (2004) PhD in Visual Arts from University of São Paulo - ECA (2010) Her research centers on art education methodologies, women's educational experiences, contemporary pedagogical approaches in visual arts, historical analysis of art education systems, and the interplay between collective memory and artistic practice. With deep expertise in educational history and teacher development, her work critically examines how socio-cultural contexts shape art instruction and learning outcomes in modern educational settings. No scientific awards were documented in the source material. Professor de Melo leads the Center for Research in Art Education (NUPEA) and contributes to the Center for Research in Painting and Art Education (NUPPE). Her academic supervision focuses on graduate students within the Professional Master's program, where she integrates historical perspectives with contemporary teaching practices to advance art education scholarship.

• Art Education
• Women's Education
• Contemporary Teaching and Learning
• +2 more

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
• +12 more

Juliana Alves Pereira is an Assistant Professor in the Computer Science Department at Pontifical Catholic University of Rio de Janeiro (PUC-Rio), where she supervises master's and doctoral research in Software Engineering. She collaborates with the Software Engineering Laboratory (LES/OPUS) and focuses on Machine Learning applications for software system management, evolution, and maintenance. Education: PhD (summa cum laude) in Software Engineering from Otto-von-Guericke-Universität Magdeburg (2018), Master's in Computer Science from Federal University of Minas Gerais (2015), and Postdoctoral studies at University of Rennes/Inria-IRISA (France) Her research spans Machine Learning, Explainability, Transfer Learning, Generative AI, Deep Learning, Natural Language Processing, and Recommender Systems, particularly in software quality and human-centric contexts. Juliana has received international recognition through awards at conferences like SPLC, ICPE, and CBSoft. Scientific Awards: Dissertationspreis 2018 – Otto-von-Guericke-Universität Magdeburg GI-Dissertationspreis 2018 nomination – German Computer Society ACM Best Paper Awards – SPLC 2021, ICPE 2020 CBSoft Most Influential Paper Award 2022 – Brazilian Computer Society Juliana actively engages in academic leadership through program committee roles at major conferences including ICSE Demo, SANER, MSR, and ICSME. She collaborates with national and international research groups while maintaining memberships in the Brazilian Computer Society (SBC) and LES/OPUS research group.

• Machine Learning
• Software Quality
• Human Aspects in Software Engineering
• +6 more

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.

• Data Visualization
• Scientific Visualization
• Computer Graphics
• +6 more

Paulo Ivson Netto Santos is a Professor in the Department of Computer Science at the Pontifical Catholic University of Rio de Janeiro (PUC-Rio) and serves as a project manager at the Tecgraf Institute. His work bridges academic research and industrial application across Oil and Gas, Civil Construction, Manufacturing, and Logistics sectors. Educational background: Bachelor's in Computer Engineering (2006, PUC-Rio) Master's in Computer Science with emphasis on Computer Graphics (2008, PUC-Rio) PhD in Computer Science (2018, PUC-Rio) Research interests span Computer Graphics and Artificial Intelligence , with specialized focus on 3D Visualization, Computational Geometry, and Deep Learning applications. His work integrates Industry 4.0 and Building Information Modeling (BIM) concepts through the Genesis Institute to develop eco-sustainable Digital Twin solutions for construction and asset management. Professional engagements: Tecgraf Institute: Leads R&D&I projects in collaboration with Electrical Engineering, Industrial Engineering, and Civil Engineering departments Genesis Institute: Drives innovation in digital transformation for industrial lifecycle management Active in startup collaborations and cross-departmental initiatives at PUC-Rio

• Computer Graphics
• Artificial Intelligence
• 3D Visualization and Rendering
• +5 more

Prof. Luis C. Lamb is a Professor at the Institute of Informatics (Universidade Federal do Rio Grande do Sul, UFRGS), specializing in Foundations of Computer Science and Artificial Intelligence. His research focuses on Neurosymbolic AI, AI Ethics, and Technology Strategy. He holds a DIC and PhD. Research Interests: Integrated Machine Learning & Reasoning, AI Ethics, Social Computing, and Innovation Strategy. Notable work includes Neurosymbolic AI frameworks and studies on collective intelligence in problem-solving. Recent contributions include talks at AAAI, IBM Neuro-Symbolic AI workshops, and the Montreal AI Debate. His work bridges statistical and symbolic AI approaches, emphasizing ethical considerations and hybrid models.

• Neurosymbolic AI
• Artificial Intelligence
• AI Ethics
• +3 more