What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Software
Georges Grinstein mainly focuses on Visualization, Data visualization, Data mining, Information visualization and Computer graphics.
In his works, Georges Grinstein undertakes multidisciplinary study on Visualization and Texture.
His Data visualization study deals with the bigger picture of Artificial intelligence.
The Data mining study combines topics in areas such as Statistical classification, Parallel array and Clustering high-dimensional data, Cluster analysis.
His research integrates issues of Data management, Visual analytics, Computer graphics, Web mining and Data science in his study of Information visualization.
In the subject of general Computer graphics, his work in Graphics is often linked to Multidimensional systems, thereby combining diverse domains of study.
His most cited work include:
- Information Visualization in Data Mining and Knowledge Discovery (407 citations)
- Interactive Data Visualization: Foundations, Techniques, and Applications (320 citations)
- Iconographic Displays For Visualizing Multidimensional Data (220 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Visualization, Data visualization, Information visualization, Data science and Visual analytics.
Visualization is a subfield of Data mining that he tackles.
His Data mining research is multidisciplinary, incorporating perspectives in Clustering high-dimensional data, Cluster analysis, Set and Categorical variable.
His study looks at the intersection of Data visualization and topics like Software with Software engineering.
He combines subjects such as Creative visualization, Scientific visualization and Database with his study of Information visualization.
His work in the fields of Analytics overlaps with other areas such as CONTEST.
He most often published in these fields:
- Visualization (47.69%)
- Data visualization (32.31%)
- Information visualization (22.05%)
What were the highlights of his more recent work (between 2010-2020)?
- Visualization (47.69%)
- Data visualization (32.31%)
- Visual analytics (21.03%)
In recent papers he was focusing on the following fields of study:
Visualization, Data visualization, Visual analytics, Data science and Information visualization are his primary areas of study.
The various areas that Georges Grinstein examines in his Visualization study include Multimedia and World Wide Web.
His Data visualization research incorporates elements of The Internet, Information retrieval, Computer graphics and Human–computer interaction.
His work deals with themes such as Population Decrease and System software, which intersect with Visual analytics.
When carried out as part of a general Data science research project, his work on Analytics is frequently linked to work in CONTEST, therefore connecting diverse disciplines of study.
His Information visualization study integrates concerns from other disciplines, such as Field, Human–computer information retrieval, Session and Visual attention.
Between 2010 and 2020, his most popular works were:
- A human cognition framework for information visualization (74 citations)
- Properties of normalized radial visualizations (35 citations)
- Benchmark Development for the Evaluation of Visualization for Data Mining (34 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Software
His primary scientific interests are in Visual analytics, Visualization, Data science, Data visualization and Cultural analytics.
Georges Grinstein is interested in Information visualization, which is a branch of Visualization.
The concepts of his Information visualization study are interwoven with issues in Field and Conceptual model.
His study in Data science is interdisciplinary in nature, drawing from both HERO, Metadata and Software development.
His Data visualization study combines topics in areas such as Multimedia, Formal methods and Engineering drawing.
The study incorporates disciplines such as Analytics and End user in addition to Cultural analytics.
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