What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Human–computer interaction
- Software
David B. Kaber mainly focuses on Task, Simulation, Human–computer interaction, Control and Information processing.
His Task study frequently draws connections between adjacent fields such as Teleoperation.
David B. Kaber studied Simulation and Applied psychology that intersect with Decision rule.
The study incorporates disciplines such as Multimedia and Robotic arm in addition to Human–computer interaction.
His Control research is multidisciplinary, incorporating perspectives in Reliability, Real-time computing, Adaptive system and Mobile phone.
In his study, Artificial intelligence is strongly linked to Industrial engineering, which falls under the umbrella field of Adaptive system.
His most cited work include:
- Level of automation effects on performance, situation awareness and workload in a dynamic control task (690 citations)
- The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task (499 citations)
- Common metrics for human-robot interaction (495 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Task, Simulation, Human–computer interaction, Artificial intelligence and Virtual reality.
David B. Kaber has researched Task in several fields, including Cognitive load, Control and Cognitive psychology, Information processing.
His Simulation research includes themes of Cockpit, Distraction, Applied psychology and Teleoperation.
David B. Kaber is studying Usability, which is a component of Human–computer interaction.
His Artificial intelligence study combines topics in areas such as Clutter, Machine learning, Computer vision and Pattern recognition.
His biological study spans a wide range of topics, including Motor skill, Haptic technology and Psychomotor learning.
He most often published in these fields:
- Task (31.94%)
- Simulation (29.17%)
- Human–computer interaction (19.44%)
What were the highlights of his more recent work (between 2015-2021)?
- Task (31.94%)
- Artificial intelligence (17.13%)
- Simulation (29.17%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Task, Artificial intelligence, Simulation, Usability and Human–computer interaction.
The Task study combines topics in areas such as Information processing, Cognitive load, Modality, Control and Pattern recognition.
The concepts of his Artificial intelligence study are interwoven with issues in Distraction, Visual perception, Computer vision, Machine learning and Pattern recognition.
His Simulation research incorporates elements of Replication and Audiology.
In Usability, he works on issues like Identification, which are connected to Management science and Variety.
His biological study deals with issues like Cognitive model, which deal with fields such as Task, Mobile computing, Emergency vehicle and Task analysis.
Between 2015 and 2021, his most popular works were:
- Issues in Human–Automation Interaction Modeling: Presumptive Aspects of Frameworks of Types and Levels of Automation: (48 citations)
- The effect of driver cognitive abilities and distractions on situation awareness and performance under hazard conditions (17 citations)
- Driver performance and attention allocation in use of logo signs on freeway exit ramps. (14 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Software
- The Internet
His primary scientific interests are in Task, Identification, Simulation, Artificial intelligence and Systems engineering.
David B. Kaber works mostly in the field of Task, limiting it down to topics relating to Cognitive load and, in certain cases, Control and Pattern recognition.
His Identification research incorporates themes from Mobile device, Physical therapy, Usability and Taxonomy.
His Simulation study integrates concerns from other disciplines, such as Replication, Similarity and Presentation.
His work deals with themes such as Visual perception, Distraction and Pattern recognition, which intersect with Artificial intelligence.
His studies in Pattern recognition integrate themes in fields like Eye tracking and Human–computer interaction.
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