What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Quantum mechanics
- Operating system
Thomas Ertl mostly deals with Visualization, Computer graphics, Rendering, Data visualization and Artificial intelligence.
His research investigates the connection with Visualization and areas like Human–computer interaction which intersect with concerns in Eye tracking.
His Computer graphics study frequently draws connections between adjacent fields such as Frame rate.
His Rendering research integrates issues from Computational science and Software rendering.
In his research, Information retrieval, Data science, Creative visualization and Analytics is intimately related to Visual analytics, which falls under the overarching field of Data visualization.
His Artificial intelligence research incorporates themes from Vector field and Computer vision.
His most cited work include:
- High-quality pre-integrated volume rendering using hardware-accelerated pixel shading (446 citations)
- Efficiently using graphics hardware in volume rendering applications (366 citations)
- Interactive volume on standard PC graphics hardware using multi-textures and multi-stage rasterization (280 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Visualization, Computer graphics, Rendering, Artificial intelligence and Computer vision.
Visualization is represented through his Data visualization, Interactive visualization, Information visualization, Scientific visualization and Visual analytics research.
In Visual analytics, Thomas Ertl works on issues like Data science, which are connected to Social media.
His study in Volume rendering, Graphics hardware, Graphics, Computer graphics and Software rendering is carried out as part of his Computer graphics studies.
Thomas Ertl has included themes like Polygon mesh and Texture mapping in his Volume rendering study.
Thomas Ertl has researched Rendering in several fields, including Tiled rendering and Texture memory.
He most often published in these fields:
- Visualization (42.11%)
- Computer graphics (29.88%)
- Rendering (22.60%)
What were the highlights of his more recent work (between 2015-2021)?
- Visualization (42.11%)
- Artificial intelligence (20.59%)
- Data visualization (16.56%)
In recent papers he was focusing on the following fields of study:
Thomas Ertl spends much of his time researching Visualization, Artificial intelligence, Data visualization, Visual analytics and Rendering.
Thomas Ertl combines subjects such as Eye tracking, Information retrieval and Human–computer interaction with his study of Visualization.
His Artificial intelligence research is multidisciplinary, incorporating elements of Natural language processing, Machine learning, Computer vision and Pattern recognition.
He interconnects Social media and Analytics, Data science in the investigation of issues within Visual analytics.
The subject of his Rendering research is within the realm of Computer graphics.
His work on Scientific visualization, Ray tracing and Volume rendering as part of general Computer graphics study is frequently linked to High resolution, bridging the gap between disciplines.
Between 2015 and 2021, his most popular works were:
- Visualizing ontologies with VOWL (113 citations)
- Visualization of Eye Tracking Data: A Taxonomy and Survey (85 citations)
- CiteRivers: Visual Analytics of Citation Patterns (57 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Quantum mechanics
- Operating system
Thomas Ertl focuses on Visualization, Artificial intelligence, Visual analytics, Human–computer interaction and Information visualization.
His Visualization research is multidisciplinary, incorporating perspectives in Eye tracking and Information retrieval.
Thomas Ertl has included themes like Natural language processing, Machine learning, Metric and Pattern recognition in his Artificial intelligence study.
His studies deal with areas such as Analytics, Data science and Geovisualization as well as Visual analytics.
His Analytics research includes elements of Social media, Cultural analytics, Theoretical computer science and Volume rendering.
His study explores the link between HTML5 and topics such as Dynamic data that cross with problems in Rendering.
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