What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Optics
His scientific interests lie mostly in Control theory, Artificial intelligence, Mechanics, Nonlinear system and Structural engineering.
His work on Actuator, Feedback linearization and Robust control as part of general Control theory research is often related to Electromagnetic suspension and Magnetic levitation, thus linking different fields of science.
His research integrates issues of Noise, Observability, Measure and Computer vision in his study of Artificial intelligence.
His work deals with themes such as Mechanical system and Classical mechanics, Contact area, which intersect with Mechanics.
His work carried out in the field of Nonlinear system brings together such families of science as Smoothing, Parametric surface and Parameterized complexity.
His research in Structural engineering intersects with topics in Metal cutting, Contact pressure and End milling.
His most cited work include:
- Automated precision measurement of surface profile in CAD-directed inspection (180 citations)
- Determination of optimal measurement configurations for robot calibration based on observability measure (174 citations)
- Smooth-surface approximation and reverse engineering (154 citations)
What are the main themes of his work throughout his whole career to date?
Control theory, Artificial intelligence, Control engineering, Computer vision and Actuator are his primary areas of study.
His Control theory study often links to related topics such as Motion control.
His Control engineering research is multidisciplinary, incorporating elements of Robot, Position and Robustness.
His Computer vision research is multidisciplinary, relying on both White light interferometry and Coordinate-measuring machine.
As a member of one scientific family, he mostly works in the field of Nonlinear system, focusing on Mechanics and, on occasion, Kinematics, Shroud and Perpendicular.
His Kinematics research includes elements of Structural engineering and Turbine blade.
He most often published in these fields:
- Control theory (29.37%)
- Artificial intelligence (16.08%)
- Control engineering (13.99%)
What were the highlights of his more recent work (between 2009-2021)?
- Control theory (29.37%)
- Actuator (12.59%)
- Motion control (11.19%)
In recent papers he was focusing on the following fields of study:
Chia-Hsiang Menq mostly deals with Control theory, Actuator, Motion control, Optics and Match moving.
His Control theory study focuses mostly on Feedback linearization, Control system and Nonlinear system.
His studies in Actuator integrate themes in fields like Workspace, Magnetic flux, Mechanical engineering and Control engineering.
His Motion control research incorporates elements of Force dynamics and Electronic engineering.
While the research belongs to areas of Optics, Chia-Hsiang Menq spends his time largely on the problem of Orientation, intersecting his research to questions surrounding Nanometrology, Plane and Micromanipulator.
Chia-Hsiang Menq is investigating Image registration as part of his Artificial intelligence and Computer vision and Image registration study.
Between 2009 and 2021, his most popular works were:
- Design, Implementation, and Force Modeling of Quadrupole Magnetic Tweezers (29 citations)
- Actively Controlled Manipulation of a Magnetic Microbead Using Quadrupole Magnetic Tweezers (26 citations)
- Dynamic Force Sensing Using an Optically Trapped Probing System (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Optics
His primary areas of study are Actuator, Motion control, Control theory, Magnetic circuit and Micromagnetics.
His Actuator study combines topics from a wide range of disciplines, such as Scanning probe microscopy, Mechanical engineering, Modeling and simulation, Finite element method and Brownian motion.
His studies deal with areas such as Magnetic tweezers, Proportional control, Feedback linearization, Control theory and Adaptive estimator as well as Motion control.
His study in Control theory is interdisciplinary in nature, drawing from both Force dynamics, Estimation theory and Bandwidth.
His Magnetic circuit research includes themes of Magnetic dipole, Magnetostatics and Classical mechanics.
His biological study spans a wide range of topics, including Workspace, Tracking and CMOS.
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