D-Index & Metrics Best Publications
Computer Science
Norway
2022

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 55 Citations 9,827 167 World Ranking 2161 National Ranking 3

Research.com Recognitions

Awards & Achievements

2022 - Research.com Computer Science in Norway Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

His main research concerns Visualization, Information visualization, Data visualization, Data mining and Computer graphics. Helwig Hauser specializes in Visualization, namely Volume rendering. His work deals with themes such as Visual analytics, Scientific visualization, Parallel coordinates and Human–computer interaction, which intersect with Information visualization.

His studies in Data visualization integrate themes in fields like Histogram and Relevance. His Data mining study combines topics in areas such as Information retrieval and State. His Computer graphics research includes themes of Artificial intelligence and Computer vision.

His most cited work include:

  • The State of the Art in Flow Visualisation: Feature Extraction and Tracking (356 citations)
  • The State of the Art in Flow Visualization : Dense and Texture-Based Techniques (297 citations)
  • Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey (223 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Visualization, Data mining, Interactive visual analysis, Data visualization and Information visualization. His Visualization study combines topics from a wide range of disciplines, such as Flow, Computer graphics and Computer vision. His Data mining research is multidisciplinary, incorporating elements of Histogram, Theoretical computer science, Categorical variable and Cluster analysis.

Helwig Hauser combines subjects such as Interactive visualization, Simulation, Computer graphics and Automotive industry with his study of Interactive visual analysis. Much of his study explores Data visualization relationship to Creative visualization. His Information visualization research is multidisciplinary, relying on both Scientific visualization, Parallel coordinates, Feature and Human–computer interaction.

He most often published in these fields:

  • Visualization (60.98%)
  • Data mining (27.32%)
  • Interactive visual analysis (24.39%)

What were the highlights of his more recent work (between 2014-2021)?

  • Visualization (60.98%)
  • Data mining (27.32%)
  • Visual analytics (14.15%)

In recent papers he was focusing on the following fields of study:

Helwig Hauser mainly investigates Visualization, Data mining, Visual analytics, Artificial intelligence and Data visualization. His study in the fields of Information visualization under the domain of Visualization overlaps with other disciplines such as Domain. Helwig Hauser has included themes like Parameter space, Clustering high-dimensional data, Qualitative property and Categorical variable in his Data mining study.

His research integrates issues of Sketch and Data science in his study of Visual analytics. His research investigates the connection between Artificial intelligence and topics such as Machine learning that intersect with problems in Interactive visual analysis, Computing Methodologies, Optimization algorithm and Complex system. His research in Data visualization intersects with topics in Aggregate and Business intelligence.

Between 2014 and 2021, his most popular works were:

  • The State-of-the-Art of Set Visualization (57 citations)
  • Designing Progressive and Interactive Analytics Processes for High-Dimensional Data Analysis (49 citations)
  • Towards Quantitative Visual Analytics with Structured Brushing and Linked Statistics (17 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Machine learning

Helwig Hauser focuses on Visual analytics, Data mining, Interactive visual analysis, Visualization and Machine learning. Helwig Hauser interconnects Data visualization and Data science in the investigation of issues within Visual analytics. His Data visualization research is multidisciplinary, incorporating perspectives in Analytics and Business intelligence.

Many of his research projects under Data mining are closely connected to Quantitative analysis with Quantitative analysis, tying the diverse disciplines of science together. His study looks at the relationship between Visualization and topics such as Theoretical computer science, which overlap with Representation. His Machine learning study which covers Artificial intelligence that intersects with Dynamic simulation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

The State of the Art in Flow Visualisation: Feature Extraction and Tracking

Frits H. Post;Benjamin Vrolijk;Helwig Hauser;Robert S. Laramee.
Computer Graphics Forum (2003)

595 Citations

The State of the Art in Flow Visualization : Dense and Texture-Based Techniques

Robert S. Laramee;Helwig Hauser;Helmut Doleisch;Benjamin Vrolijk.
Computer Graphics Forum (2004)

479 Citations

Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey

J. Kehrer;H. Hauser.
IEEE Transactions on Visualization and Computer Graphics (2013)

369 Citations

Interactive feature specification for focus+context visualization of complex simulation data

Helmut Doleisch;Martin Gasser;Helwig Hauser.
Proceedings of the symposium on Data visualisation 2003 (2003)

343 Citations

Angular brushing of extended parallel coordinates

H. Hauser;F. Ledermann;H. Doleisch.
ieee symposium on information visualization (2002)

336 Citations

Parallel Sets: interactive exploration and visual analysis of categorical data

R. Kosara;F. Bendix;H. Hauser.
IEEE Transactions on Visualization and Computer Graphics (2006)

330 Citations

Outlier-Preserving Focus+Context Visualization in Parallel Coordinates

M. Novotny;H. Hauser.
IEEE Transactions on Visualization and Computer Graphics (2006)

285 Citations

Glyph-based Visualization: Foundations, Design Guidelines, Techniques and Applications

Rita Borgo;Johannes Kehrer;David H. S. Chung;Eamonn Maguire.
eurographics (2013)

279 Citations

High-quality two-level volume rendering of segmented data sets on consumer graphics hardware

M. Hadwiger;C. Berger;H. Hauser.
ieee visualization (2003)

247 Citations

Two-level volume rendering

H. Hauser;L. Mroz;G. Italo Bischi;M.E. Groller.
IEEE Transactions on Visualization and Computer Graphics (2001)

234 Citations

Editorial Boards

Computer Graphics Forum
(Impact Factor: 2.363)

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