D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 35 Citations 4,527 160 World Ranking 5403 National Ranking 346

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His scientific interests lie mostly in Crystal, Data mining, Artificial intelligence, Mineralogy and Artificial neural network. His study in the field of Crystal habit and Crystal morphology is also linked to topics like Biological system. His biological study spans a wide range of topics, including Principal component analysis, Statistical process control and Process.

His study in Artificial intelligence is interdisciplinary in nature, drawing from both System identification and Pattern recognition. His Mineralogy research includes elements of Crystal growth, Crystallization, Filtration and Optics. His study focuses on the intersection of Crystallization and fields such as Supersaturation with connections in the field of Growth kinetics, Crystallography and Facet.

His most cited work include:

  • A new approach to near-infrared spectral data analysis using independent component analysis. (124 citations)
  • Multi-scale segmentation image analysis for the in-process monitoring of particle shape with batch crystallisers (123 citations)
  • Data Mining and Knowledge Discovery for Process Monitoring and Control (96 citations)

What are the main themes of his work throughout his whole career to date?

Xue Z. Wang mainly investigates Crystallization, Crystal, Artificial intelligence, Biological system and Crystal growth. His work carried out in the field of Crystallization brings together such families of science as Process engineering, Process analytical technology, Supersaturation and Analytical chemistry. His work is dedicated to discovering how Crystal, Work are connected with Nanotechnology and other disciplines.

His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Data mining, Computer vision and Pattern recognition. His Data mining research integrates issues from Artificial neural network, Fuzzy logic, Principal component analysis and Process. His Crystal growth research is multidisciplinary, incorporating elements of Scientific method, Mineralogy and Phase.

He most often published in these fields:

  • Crystallization (45.99%)
  • Crystal (42.78%)
  • Artificial intelligence (19.25%)

What were the highlights of his more recent work (between 2015-2021)?

  • Crystallization (45.99%)
  • Crystal (42.78%)
  • Supersaturation (18.18%)

In recent papers he was focusing on the following fields of study:

Xue Z. Wang focuses on Crystallization, Crystal, Supersaturation, Thermodynamics and Optics. His studies in Crystallization integrate themes in fields like Crystal growth, Analytical chemistry, Physical chemistry, Seeding and Process engineering. His research investigates the connection between Crystal and topics such as Work that intersect with issues in Crystal morphology.

His Supersaturation research includes themes of Solubility and Particle size. His work deals with themes such as Calibration, Computer vision and Artificial intelligence, which intersect with Optics. The study incorporates disciplines such as Deconvolution, Economies of agglomeration, Mineralogy and Pattern recognition in addition to Artificial intelligence.

Between 2015 and 2021, his most popular works were:

  • In-situ crystal morphology identification using imaging analysis with application to the L-glutamic acid crystallization (22 citations)
  • In-situ crystal morphology identification using imaging analysis with application to the L-glutamic acid crystallization (22 citations)
  • Accurate and interpretable nanoSAR models from genetic programming-based decision tree construction approaches (22 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary scientific interests are in Nanotechnology, Crystal, Crystallization, Engineered nanomaterials and Crystallography. His Nanotechnology study combines topics in areas such as Mechanical engineering, Crystal size distribution, Distribution, Crystal morphology and Facet. His Crystal research incorporates elements of Work, Feature, Growth kinetics, Image processing and Calibration.

Xue Z. Wang incorporates Crystallization and Biological system in his studies. Xue Z. Wang has researched Engineered nanomaterials in several fields, including Control and Biochemical engineering. His Crystallography study integrates concerns from other disciplines, such as Scanning electron microscope, Differential scanning calorimetry, Spray drying and Infrared spectroscopy.

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.

Best Publications

Multi-scale segmentation image analysis for the in-process monitoring of particle shape with batch crystallisers

J. Calderon De Anda;X.Z. Wang;K.J. Roberts.
Chemical Engineering Science (2005)

188 Citations

A new approach to near-infrared spectral data analysis using independent component analysis.

J. Chen;X. Z. Wang.
Journal of Chemical Information and Computer Sciences (2001)

186 Citations

Data Mining and Knowledge Discovery for Process Monitoring and Control

Xue Zhang Wang;C. McGreavy.
(1999)

150 Citations

Crystal growth measurement using 2D and 3D imaging and the perspectives for shape control

Xue Z. Wang;Kevin J. Roberts;Caiyun Ma.
Chemical Engineering Science (2008)

145 Citations

Agent-based information flow for process industries' supply chain modelling

R. García-Flores;X.Z. Wang;G.E. Goltz.
Computers & Chemical Engineering (2000)

129 Citations

Statistical Process Control Charts for Batch Operations Based on Independent Component Analysis

Hamza Albazzaz;Xue Z. Wang.
Industrial & Engineering Chemistry Research (2004)

128 Citations

Application of wavelets and neural networks to diagnostic system development, 1, feature extraction

B.H. Chen;X.Z. Wang;S.H. Yang;C. McGreavy.
Computers & Chemical Engineering (1999)

128 Citations

Classifying organic crystals via in-process image analysis and the use of monitoring charts to follow polymorphic and morphological changes

J. Calderon De Anda;X.Z. Wang;X. Lai;K.J. Roberts.
Journal of Process Control (2005)

127 Citations

Knowledge discovery from process operational data using PCA and fuzzy clustering

Y.M. Sebzalli;X.Z. Wang.
Engineering Applications of Artificial Intelligence (2001)

124 Citations

Dimension reduction of process dynamic trends using independent component analysis

R.F Li;X.Z Wang.
Computers & Chemical Engineering (2002)

111 Citations

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