What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Mechanical engineering
- Programming language
Her main research concerns Simulated annealing, Actuator, Computer Aided Design, Structural engineering and Tensegrity.
Her Simulated annealing study frequently links to other fields, such as Artificial intelligence.
Her work deals with themes such as Engineering drawing, Shape optimization, XML, Cantilever and Generative grammar, which intersect with Computer Aided Design.
Her research in Shape optimization focuses on subjects like Full scale, which are connected to Topology and Rule-based machine translation.
Her research integrates issues of Mechanical engineering, Nozzle and Process in her study of Structural engineering.
Her Tensegrity research is multidisciplinary, relying on both Search problem and Search algorithm.
Her most cited work include:
- Towards integrated performance-driven generative design tools (158 citations)
- Computer-Based Design Synthesis Research: An Overview (128 citations)
- Harnessing bistability for directional propulsion of soft, untethered robots. (109 citations)
What are the main themes of her work throughout her whole career to date?
Kristina Shea focuses on Computational design, Systems engineering, Engineering drawing, Rule-based machine translation and Artificial intelligence.
Her Systems engineering research incorporates themes from Software, Conceptual design, Software engineering and Electronic design automation.
Her studies deal with areas such as Task and Product as well as Software engineering.
Kristina Shea has researched Engineering drawing in several fields, including Generative Design and Process.
Her Rule-based machine translation study combines topics in areas such as Simulated annealing, Generative grammar and Engineering design process.
Artificial intelligence is often connected to Machine learning in her work.
She most often published in these fields:
- Computational design (14.35%)
- Systems engineering (13.91%)
- Engineering drawing (11.74%)
What were the highlights of her more recent work (between 2015-2021)?
- Computational design (14.35%)
- 3D printing (6.52%)
- Actuator (6.52%)
In recent papers she was focusing on the following fields of study:
Her primary areas of investigation include Computational design, 3D printing, Actuator, Mechanical engineering and Composite material.
Kristina Shea combines subjects such as Toughness, Nanotechnology and Polymer with her study of 3D printing.
She interconnects Shape-memory polymer, Robot and Bistability in the investigation of issues within Actuator.
Her research in Bistability intersects with topics in Battery, Electrical engineering, Electronic engineering and Topology.
Her work on Multi material is typically connected to Fabrication as part of general Mechanical engineering study, connecting several disciplines of science.
Her study in Artificial intelligence is interdisciplinary in nature, drawing from both Control engineering, Topology and Machine learning.
Between 2015 and 2021, her most popular works were:
- Harnessing bistability for directional propulsion of soft, untethered robots. (109 citations)
- Rotational 3D printing of damage-tolerant composites with programmable mechanics. (88 citations)
- Integrated Design and Simulation of Tunable, Multi-State Structures Fabricated Monolithically with Multi-Material 3D Printing. (66 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Programming language
The scientist’s investigation covers issues in 3D printing, Actuator, Composite material, 3d printed and Artificial intelligence.
In 3D printing, she works on issues like Polymer, which are connected to Nanotechnology, Fiber orientation, Rotational speed and Fiber.
Her Actuator research includes themes of Shape-memory polymer and Bistability.
Her Composite material study combines topics from a wide range of disciplines, such as Orientation, Lattice and Orthotropic material.
Her work on Robotics as part of general Artificial intelligence study is frequently linked to Computational design, therefore connecting diverse disciplines of science.
The Robot study which covers Electrical engineering that intersects with Engineering design process.
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