What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Operating system
Cláudio T. Silva mostly deals with Visualization, Artificial intelligence, Data visualization, Rendering and Algorithm.
His biological study spans a wide range of topics, including World Wide Web, Computer graphics, Workflow and Human–computer interaction.
The concepts of his Artificial intelligence study are interwoven with issues in Manifold, Machine learning, Computer vision and Surface reconstruction.
His work carried out in the field of Data visualization brings together such families of science as Software system, Projection, Pipeline, Analytics and Component.
In his research on the topic of Rendering, Differential geometry and Point set is strongly related with Frame rate.
The study incorporates disciplines such as Point cloud, Mesh generation and Theoretical computer science in addition to Algorithm.
His most cited work include:
- The ball-pivoting algorithm for surface reconstruction (843 citations)
- Computing and rendering point set surfaces (708 citations)
- Point set surfaces (582 citations)
What are the main themes of his work throughout his whole career to date?
Visualization, Data visualization, Data science, Computer graphics and Artificial intelligence are his primary areas of study.
His Visualization research includes themes of Analytics and Human–computer interaction.
His work deals with themes such as Data modeling, Theoretical computer science and Computer graphics, which intersect with Data visualization.
His Data science research is multidisciplinary, incorporating elements of World Wide Web, Data management, Workflow and Interactive visualization.
His research integrates issues of Mesh generation and Computational geometry in his study of Computer graphics.
His Artificial intelligence study integrates concerns from other disciplines, such as Algorithm, Machine learning, Computer vision and Pattern recognition.
He most often published in these fields:
- Visualization (34.65%)
- Data visualization (18.56%)
- Data science (18.81%)
What were the highlights of his more recent work (between 2016-2021)?
- Visualization (34.65%)
- Artificial intelligence (15.35%)
- Data visualization (18.56%)
In recent papers he was focusing on the following fields of study:
Cláudio T. Silva focuses on Visualization, Artificial intelligence, Data visualization, Visual analytics and Data science.
His studies in Visualization integrate themes in fields like Feature extraction, Computer graphics and Human–computer interaction.
His studies deal with areas such as Detector, Construct, Computer vision, Machine learning and Pattern recognition as well as Artificial intelligence.
Cláudio T. Silva studied Data visualization and Variety that intersect with Use case.
His Visual analytics research is multidisciplinary, relying on both Motion, Pipeline and Set.
His Data science research is multidisciplinary, incorporating perspectives in Data management, Offensive and Identification.
Between 2016 and 2021, his most popular works were:
- A Survey of Surface Reconstruction from Point Clouds (185 citations)
- Deep Geometric Prior for Surface Reconstruction (63 citations)
- SONYC: a system for monitoring, analyzing, and mitigating urban noise pollution (63 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Programming language
His main research concerns Data visualization, Artificial intelligence, Visualization, Visual analytics and Data mining.
His Data visualization research integrates issues from Programming language and Data science.
Cláudio T. Silva has researched Artificial intelligence in several fields, including Machine learning, Computer vision and Surface reconstruction.
His work in Surface reconstruction covers topics such as Algorithm which are related to areas like Parametrization.
The Visualization study combines topics in areas such as Data flow diagram, Feature extraction and Computer graphics, Computer graphics.
His Information visualization research incorporates themes from Data modeling, Timeline, Row and Rendering.
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