What is he best known for?
The fields of study he is best known for:
- Mechanical engineering
- Artificial intelligence
- Electrical engineering
Sridhar Kota mostly deals with Compliant mechanism, Control engineering, Actuator, Genetic algorithm and Engineering design process.
Finite element method covers he research in Compliant mechanism.
His Control engineering study incorporates themes from Shape optimization, Precision engineering, Miniaturization and Deflection.
The Actuator study combines topics in areas such as Systems design and Stiffness.
His Genetic algorithm research integrates issues from Input/output, Discrete optimization, Network topology and Benchmark.
Sridhar Kota usually deals with Engineering design process and limits it to topics linked to Systems engineering and Machine design, Industrial design, Subspace topology and Theoretical computer science.
His most cited work include:
- Topological synthesis of compliant mechanisms using multi-criteria optimization (383 citations)
- DESIGN OF LARGE-DISPLACEMENT COMPLIANT JOINTS (289 citations)
- Reconfigurable machine tool (235 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Compliant mechanism, Control engineering, Structural engineering, Actuator and Kinematics.
His study in Compliant mechanism is interdisciplinary in nature, drawing from both Control theory, Nonlinear system, Topology and Topology.
His studies deal with areas such as Development, Machine tool, Morphing, Microelectromechanical systems and Grippers as well as Control engineering.
His work in Machine tool addresses subjects such as Screw theory, which are connected to disciplines such as Engineering drawing.
His Structural engineering study which covers Mechanical engineering that intersects with Stiffness and Elastomer.
In his study, Block is inextricably linked to Mechanism, which falls within the broad field of Actuator.
He most often published in these fields:
- Compliant mechanism (33.88%)
- Control engineering (21.31%)
- Structural engineering (18.03%)
What were the highlights of his more recent work (between 2008-2020)?
- Structural engineering (18.03%)
- Robot (8.74%)
- Actuator (18.03%)
In recent papers he was focusing on the following fields of study:
His main research concerns Structural engineering, Robot, Actuator, Compliant mechanism and Mechanical engineering.
The various areas that he examines in his Structural engineering study include Frame, Stress, Drive shaft, Nonlinear system and Work.
His Robot research is multidisciplinary, relying on both Fiber and Control theory.
His Actuator study incorporates themes from Continuum, Kinematics, Surface and Mobile robot.
He interconnects Ellipse, Point of interest, Block, Control engineering and Network topology in the investigation of issues within Compliant mechanism.
His research in Control engineering intersects with topics in Constraint and Topology.
Between 2008 and 2020, his most popular works were:
- Design and Modeling of Generalized Fiber-Reinforced Pneumatic Soft Actuators (68 citations)
- Design of soft robotic actuators using fluid-filled fiber-reinforced elastomeric enclosures in parallel combinations (57 citations)
- Kinematics of a Generalized Class of Pneumatic Artificial Muscles (50 citations)
In his most recent research, the most cited papers focused on:
- Mechanical engineering
- Artificial intelligence
- Electrical engineering
Structural engineering, Stiffness, Mechanical engineering, Kinematics and Deformation are his primary areas of study.
The concepts of his Structural engineering study are interwoven with issues in Work, Wind power, Actuator and Turbine.
His Actuator research is mostly focused on the topic Soft robotics.
His work deals with themes such as Control engineering, Exoskeleton and Topology, which intersect with Stiffness.
His research integrates issues of Robot, Elastomer and Finite element method in his study of Mechanical engineering.
He has included themes like Class, Helix angle and Rotary actuator in his Kinematics study.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
