What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Machine learning
Artificial intelligence, Human–robot interaction, Robot, Human–computer interaction and Natural language are his primary areas of study.
His Artificial intelligence research incorporates themes from Ambiguity and Computer vision.
His study in Human–robot interaction is interdisciplinary in nature, drawing from both Action, Task, Cognition, Social robot and Process management.
His Robot research is multidisciplinary, incorporating elements of Cognitive psychology, Simulation, Perception and Component.
His research integrates issues of Affect, Human multitasking, Inference and Task analysis in his study of Human–computer interaction.
His Natural language study combines topics from a wide range of disciplines, such as Annotation and Treebank.
His most cited work include:
- Development environments for autonomous mobile robots: A survey (213 citations)
- What to do and how to do it: Translating natural language directives into temporal and dynamic logic representation for goal management and action execution (153 citations)
- Looking the Part: Social Status Cues Shape Race Perception (146 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Robot, Human–computer interaction, Human–robot interaction and Task.
The Artificial intelligence study combines topics in areas such as Computer vision and Natural language processing.
His Natural language processing research includes elements of Utterance and Resolution.
Matthias Scheutz works mostly in the field of Robot, limiting it down to concerns involving Cognition and, occasionally, Cognitive science.
The concepts of his Human–computer interaction study are interwoven with issues in Robot learning and Situated.
His studies deal with areas such as Cognitive psychology, Social psychology, Affect, Perception and Knowledge management as well as Human–robot interaction.
He most often published in these fields:
- Artificial intelligence (40.46%)
- Robot (35.33%)
- Human–computer interaction (26.50%)
What were the highlights of his more recent work (between 2016-2021)?
- Robot (35.33%)
- Human–computer interaction (26.50%)
- Artificial intelligence (40.46%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Robot, Human–computer interaction, Artificial intelligence, Human–robot interaction and Task.
His studies in Robot integrate themes in fields like Context, Perception, Cognition, Applied psychology and Cognitive science.
His Human–computer interaction study integrates concerns from other disciplines, such as One-shot learning, Situated, Natural language and Component.
His work carried out in the field of Artificial intelligence brings together such families of science as Situational ethics, Ambiguity and Natural language processing.
His Human–robot interaction research incorporates elements of Social psychology, Affect, Emotional intelligence, Knowledge management and Gesture.
His Task research integrates issues from Robotic systems, Real-time computing, Natural language understanding and Autonomous robot.
Between 2016 and 2021, his most popular works were:
- Interactive Task Learning (45 citations)
- Value Alignment or Misalignment - What Will Keep Systems Accountable? (39 citations)
- AI Challenges in Human-Robot Cognitive Teaming. (35 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Machine learning
Matthias Scheutz focuses on Robot, Artificial intelligence, Human–robot interaction, Human–computer interaction and Context.
His Robot research includes themes of Perception, Cognitive architecture, Cognitive science, Task analysis and Component.
His study in Artificial intelligence focuses on Robotics in particular.
His research integrates issues of Social psychology, Emotional intelligence and Social robot in his study of Human–robot interaction.
His Human–computer interaction research includes elements of Task, Natural language and One-shot learning.
His work deals with themes such as Probabilistic logic and Cognitive robotics, which intersect with Context.
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