What is he best known for?
The fields of study he is best known for:
- Statistics
- Normal distribution
- Algorithm
His primary scientific interests are in Mathematical optimization, Statistics, Algorithm, Surface and Data mining.
His work carried out in the field of Mathematical optimization brings together such families of science as Degree, Orthogonal array, Fuzzy logic and Plan.
His Statistics study integrates concerns from other disciplines, such as EWMA chart and Control chart.
Dennis K.J. Lin does research in Algorithm, focusing on Random search specifically.
His Surface study combines topics from a wide range of disciplines, such as Composite number and Response surface methodology.
His study on Fractional factorial design is often connected to Mixed level as part of broader study in Factorial experiment.
His most cited work include:
- Uniform Design: Theory and Application (627 citations)
- Dual response surface optimization (301 citations)
- A new class of supersaturated designs (298 citations)
What are the main themes of his work throughout his whole career to date?
Dennis K.J. Lin mostly deals with Mathematical optimization, Algorithm, Statistics, Fractional factorial design and Computer experiment.
His studies deal with areas such as Econometrics, Measure, Surface and Orthogonal array as well as Mathematical optimization.
His Algorithm study typically links adjacent topics like Bayesian probability.
His Statistics research is multidisciplinary, incorporating perspectives in System failure, Control chart and Applied mathematics.
Dennis K.J. Lin interconnects Orthogonality and Latin hypercube sampling in the investigation of issues within Computer experiment.
His Latin hypercube sampling research is multidisciplinary, relying on both Discrete mathematics, Hypercube and Combinatorics.
He most often published in these fields:
- Mathematical optimization (20.88%)
- Algorithm (23.81%)
- Statistics (22.71%)
What were the highlights of his more recent work (between 2014-2021)?
- Algorithm (23.81%)
- Mathematical optimization (20.88%)
- Computer experiment (10.26%)
In recent papers he was focusing on the following fields of study:
Dennis K.J. Lin mainly investigates Algorithm, Mathematical optimization, Computer experiment, Latin hypercube sampling and Combinatorics.
His research in Algorithm intersects with topics in Artificial neural network, Perceptron, Kernel regression, Regression and Nonlinear system.
While working on this project, Dennis K.J. Lin studies both Mathematical optimization and Approximate theory.
His biological study spans a wide range of topics, including Design of experiments, Space, Computer simulation and Kriging.
His studies examine the connections between Latin hypercube sampling and genetics, as well as such issues in Discrete mathematics, with regards to Group.
The Combinatorics study combines topics in areas such as Blocking and Confounding.
Between 2014 and 2021, his most popular works were:
- Computer Experiments With Both Qualitative and Quantitative Variables (21 citations)
- Construction of sliced maximin-orthogonal Latin hypercube designs (11 citations)
- Uniform sliced Latin hypercube designs (11 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Normal distribution
- Machine learning
The scientist’s investigation covers issues in Latin hypercube sampling, Combinatorics, Mathematical optimization, Algorithm and Computer experiment.
In his study, which falls under the umbrella issue of Latin hypercube sampling, Orthogonal array is strongly linked to Discrete mathematics.
The study incorporates disciplines such as Blocking and Confounding in addition to Combinatorics.
His studies in Mathematical optimization integrate themes in fields like Order and Optimal design.
Dennis K.J. Lin integrates several fields in his works, including Algorithm and Scalability.
His Computer experiment study which covers Kriging that intersects with Similarity, Measure and Cross-validation.
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.
