What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Programming language
- Software
Her primary scientific interests are in Artificial intelligence, Software, Robot, Software engineering and Human–computer interaction.
Her Artificial intelligence research is multidisciplinary, relying on both Cognitive psychology, Plan, Conversation and Cognitive decline.
In her research on the topic of Software, Test case, Correctness, Graphical user interface and Component is strongly related with Graphical user interface testing.
In her research, Belief–desire–intention model is intimately related to Resource allocation, which falls under the overarching field of Component.
The concepts of her Robot study are interwoven with issues in Situated and Simulation.
Her Human–computer interaction research incorporates elements of Machine learning and Error-driven learning.
Her most cited work include:
- Plans and resource-bounded practical reasoning (988 citations)
- Intentions in Communication. (789 citations)
- Towards robotic assistants in nursing homes: Challenges and results (525 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of study are Artificial intelligence, Plan, Mathematical optimization, Human–computer interaction and Component.
The Mobile robot research Martha E. Pollack does as part of her general Artificial intelligence study is frequently linked to other disciplines of science, such as Activities of daily living, therefore creating a link between diverse domains of science.
As a part of the same scientific family, Martha E. Pollack mostly works in the field of Mobile robot, focusing on Software engineering and, on occasion, Software.
Her work deals with themes such as Automated planning and scheduling, Management science, Inference, Process and Operations research, which intersect with Plan.
Her research in Mathematical optimization intersects with topics in Algorithm and Space.
Her studies in Human–computer interaction integrate themes in fields like Multimedia, User modeling and Set.
She most often published in these fields:
- Artificial intelligence (30.20%)
- Plan (26.85%)
- Mathematical optimization (16.11%)
What were the highlights of her more recent work (between 2005-2014)?
- Human–computer interaction (11.41%)
- Mathematical optimization (16.11%)
- Set (6.04%)
In recent papers she was focusing on the following fields of study:
Martha E. Pollack mainly focuses on Human–computer interaction, Mathematical optimization, Set, Artificial intelligence and Constraint satisfaction.
Her work on Adaptation as part of general Human–computer interaction research is often related to Focus, thus linking different fields of science.
In Set, Martha E. Pollack works on issues like Context, which are connected to World Wide Web and Human multitasking.
The Artificial intelligence study combines topics in areas such as Machine learning, Function and Internet privacy.
Her work in the fields of Constraint satisfaction, such as Local consistency, intersects with other areas such as Solver, Semiring and Tuple.
Her Activities of daily living investigation overlaps with other disciplines such as Component and Plan.
Between 2005 and 2014, her most popular works were:
- An Intelligent Personal Assistant for Task and Time Management (164 citations)
- An 'object-use fingerprint': the use of electronic sensors for human identification (39 citations)
- Optimal rectangle packing: a meta-CSP approach (31 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Software
Her scientific interests lie mostly in Artificial intelligence, Human–computer interaction, Feature, Task and Machine learning.
Her Artificial intelligence study integrates concerns from other disciplines, such as Schedule and Function.
Her Human–computer interaction research is multidisciplinary, relying on both Multi-task learning, Multimedia, User modeling and Inference.
Her Feature research integrates issues from Neuropsychological assessment and Neuropsychology.
Her Task research incorporates elements of Cognitive load, Time management, User assistance and Belief–desire–intention model.
Her work on Activity recognition is typically connected to Simple as part of general Machine learning study, connecting several disciplines of science.
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