What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Programming language
His scientific interests lie mostly in Visualization, Data visualization, Artificial intelligence, Rendering and Volume rendering.
His Visualization research is under the purview of Data mining.
The various areas that he examines in his Data visualization study include Visual analytics, User interface, Interactive visualization, Computer graphics and Information visualization.
Kwan-Liu Ma has researched Artificial intelligence in several fields, including Machine learning and Computer vision.
His Rendering study incorporates themes from Software rendering, Texture memory and Pattern recognition.
His Volume rendering study combines topics in areas such as Image processing, Algorithm, Massively parallel and Graphics.
His most cited work include:
- Terascale direct numerical simulations of turbulent combustion using S3D (420 citations)
- Parallel volume rendering using binary-swap compositing (254 citations)
- Data, Information, and Knowledge in Visualization (196 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Visualization, Data visualization, Artificial intelligence, Rendering and Computer graphics.
His work in Visualization tackles topics such as Human–computer interaction which are related to areas like User interface.
His Data visualization study integrates concerns from other disciplines, such as Data modeling, Scientific visualization, Computer graphics, Scalability and Data science.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Computer vision.
His research integrates issues of Tiled rendering and Texture memory in his study of Rendering.
He interconnects Computational science and Graphics in the investigation of issues within Volume rendering.
He most often published in these fields:
- Visualization (57.67%)
- Data visualization (35.45%)
- Artificial intelligence (21.16%)
What were the highlights of his more recent work (between 2015-2021)?
- Visualization (57.67%)
- Data visualization (35.45%)
- Visual analytics (13.93%)
In recent papers he was focusing on the following fields of study:
Visualization, Data visualization, Visual analytics, Data mining and Human–computer interaction are his primary areas of study.
His research in Visualization intersects with topics in Information retrieval and Data science.
While the research belongs to areas of Data visualization, Kwan-Liu Ma spends his time largely on the problem of Scalability, intersecting his research to questions surrounding Network topology and Distributed computing.
His research on Visual analytics concerns the broader Artificial intelligence.
Kwan-Liu Ma usually deals with Artificial intelligence and limits it to topics linked to Computer vision and Computer graphics.
He focuses mostly in the field of Information visualization, narrowing it down to topics relating to Rendering and, in certain cases, General-purpose computing on graphics processing units and Computational science.
Between 2015 and 2021, his most popular works were:
- Stereoscopic Thumbnail Creation via Efficient Stereo Saliency Detection (101 citations)
- A Study of Layout, Rendering, and Interaction Methods for Immersive Graph Visualization (83 citations)
- VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures (78 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Programming language
Kwan-Liu Ma spends much of his time researching Visualization, Data visualization, Data mining, Visual analytics and Information visualization.
He studies Visualization, namely Interactive visualization.
His Data visualization research includes themes of Graph, Graph drawing, Information retrieval, Task analysis and Information sensitivity.
He combines subjects such as Data modeling, Workflow and Curse of dimensionality with his study of Data mining.
His Visual analytics research incorporates elements of Supercomputer, Distributed computing, Data management, Dimensionality reduction and Principal component analysis.
The concepts of his Information visualization study are interwoven with issues in Rendering, Domain knowledge, Analytics, Data science and Big data.
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