What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Machine learning
- Programming language
Manuela Veloso mostly deals with Artificial intelligence, Robot, Domain, Human–computer interaction and Mobile robot.
Her biological study spans a wide range of topics, including Machine learning, Task and Computer vision.
Her Machine learning study combines topics from a wide range of disciplines, such as Structure, Probabilistic logic and Feature extraction.
As a part of the same scientific study, Manuela Veloso usually deals with the Robot, concentrating on Asynchronous communication and frequently concerns with Planner.
Her work carried out in the field of Domain brings together such families of science as Teamwork, Representation, Adaptation and Set.
Her Mobile robot research incorporates themes from Domain knowledge and Motion planning.
Her most cited work include:
- A survey of robot learning from demonstration (2198 citations)
- Multiagent Systems: A Survey from a Machine Learning Perspective (966 citations)
- SPIRAL: Code Generation for DSP Transforms (708 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of investigation include Artificial intelligence, Robot, Human–computer interaction, Mobile robot and Domain.
Her Artificial intelligence research incorporates elements of Machine learning and Computer vision.
She works in the field of Computer vision, focusing on Object in particular.
As part of her studies on Robot, she often connects relevant subjects like Task.
She interconnects Variety, Human–robot interaction and Set in the investigation of issues within Human–computer interaction.
Domain is closely attributed to Plan in her study.
She most often published in these fields:
- Artificial intelligence (54.42%)
- Robot (46.30%)
- Human–computer interaction (22.22%)
What were the highlights of her more recent work (between 2015-2021)?
- Robot (46.30%)
- Artificial intelligence (54.42%)
- Human–computer interaction (22.22%)
In recent papers she was focusing on the following fields of study:
Her primary areas of study are Robot, Artificial intelligence, Human–computer interaction, Task and Reinforcement learning.
Robot is closely attributed to Set in her research.
She combines subjects such as Machine learning and Computer vision with her study of Artificial intelligence.
Her Human–computer interaction research integrates issues from Human–robot interaction, Service robot, Object, Mobile service and Autonomous robot.
The Reinforcement learning study combines topics in areas such as Control and Markov decision process.
The various areas that Manuela Veloso examines in her Humanoid robot study include Stackelberg competition and Autonomous agent.
Between 2015 and 2021, her most popular works were:
- The grand challenges of Science Robotics (361 citations)
- Mobile Service Robot State Revealing Through Expressive Lights: Formalism, Design, and Evaluation (35 citations)
- Teaching Robots to Predict Human Motion (33 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Machine learning
Manuela Veloso spends much of her time researching Robot, Artificial intelligence, Human–computer interaction, Mobile robot and Computer vision.
Manuela Veloso has included themes like Motion, Task and Heuristic in her Robot study.
Her Machine learning research extends to Artificial intelligence, which is thematically connected.
The study incorporates disciplines such as Human–robot interaction, Object, Mobile service, Autonomous robot and Robustness in addition to Human–computer interaction.
Her work on Mobile robot navigation as part of general Mobile robot study is frequently linked to Active sensing, therefore connecting diverse disciplines of science.
Her study in Computer vision is interdisciplinary in nature, drawing from both Animation and Trajectory.
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