Bernard K. Chen
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Associate Professor
Also affiliated: University of Southern California (2018); Troy University (2025); Emory University (2022); The University of Melbourne (2019–2024); Georgia State University (2006–2008); Kun Shan University (2006); The Royal Victorian Eye & Ear Hospital (2019–2025); The University of Texas at San Antonio (2022–2023); Monash University (1989–2024); East Stroudsburg University (2012); Beihang University (1985); Nanjing University of Aeronautics and Astronautics (2022)
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Bernard K. Chen's research has explored the mechanical behavior of geological materials, particularly granite, under varying temperature and pressure conditions. His work has investigated applications in geothermal energy extraction, including hydraulic fracturing and thermal stimulation methods. Chen has also contributed to studies on the crush responses of composite structures, employing both experimental and numerical finite element modeling techniques.
With a significant publication record of over 160 peer-reviewed articles and more than 3,900 citations, Chen is recognized as a highly cited researcher. His scholarly output demonstrates a consistent engagement with materials science and engineering principles. He leads a research group at the University of Central Arkansas and collaborates with several faculty members within the institution.
Metrics
- h-index: 28
- Publications: 161
- Citations: 3,944
Positions
-
Associate Professor publications 2008–2025University of Central Arkansas Institution web page
Selected Publications
-
Privacy-Preserving Secure Framework for Intelligent Transportation Systems (2025)
-
Wineinformatics: Wine Score Prediction with Wine Price and Reviews (2024)
-
Applying Neural Networks in Wineinformatics with the New Computational Wine Wheel (2023)
-
Advanced Usage of the Computational Wine Wheel (2022)
-
Introduction (2022)
-
Wineinformatics (2022)
-
Data Collection and Preprocessing (2022)
-
Multi-Class, Multi-Label and Multi-Target in Wineinformatics (2022)
-
Conclusion and Future Works (2022)
-
Regression in Wineinformatics (2022)
-
Classification in Wineinformatics (2022)
-
Evaluation of Wine Judges (2022)
-
Wineinformatics: Comparing and Combining SVM Models Built by Wine Reviews from Robert Parker and Wine Spectator for 95 + Point Wine Prediction (2022)
-
Wineinformatics: Can Wine Reviews in Bordeaux Reveal Wine Aging Capability? (2021)
-
Clustering in Wineinformatics with Attribute Selection to Increase Uniqueness of Clusters (2021)
Collaboration Network
Top Collaborators
- Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches
- GIST: Genomic island suite of tools for predicting genomic islands
- Understanding the Wine Judges and Evaluating the Consistency Through White-Box Classification Algorithms
- Hierarchically clustered HMM for protein sequence motif extraction with variable length
- Discovering genomic islands in microbial genomes using a genetic algorithm
- Sparse nonnegative matrix factorization for protein sequence motif discovery
- Novel efficient granular computing models for protein sequence motifs and structure information discovery
- Using Hybrid Hierarchical K-means (HHK) clustering algorithm for protein sequence motif Super-Rule-Tree (SRT) structure construction
- Protein Sequence Motif Super-Rule-Tree (SRT) Structure Constructed by Hybrid Hierarchical K-Means Clustering Algorithm
- PROTEIN LOCAL TERTIARY STRUCTURE PREDICTION BY SUPER GRANULE SUPPORT VECTOR MACHINES WITH CHOU-FASMAN PARAMETER
- Wineinformatics: A Quantitative Analysis of Wine Reviewers
- Classification on grade, price, and region with multi-label and multi-target methods in wineinformatics
- Wineinformatics: Using the Full Power of the Computational Wine Wheel to Understand 21st Century Bordeaux Wines from the Reviews
- Granular computing in wineinformatics
- Wineinformatics: A Quantitative Analysis of Wine Reviewers
- Wineinformatics: Regression on the Grade and Price of Wines through Their Sensory Attributes
- Classification on grade, price, and region with multi-label and multi-target methods in wineinformatics
- Multi-class wine grades predictions with hierarchical support vector machines
- Variable-Length Protein Sequence Motif Extraction Using Hierarchically-Clustered Hidden Markov Models
- Hierarchically clustered HMM for protein sequence motif extraction with variable length
- Protein Local Tertiary Structure Prediction Using the Adaptively-Branching FGK-DF Model
- Wineinformatics: A Quantitative Analysis of Wine Reviewers
- The Computational Wine Wheel 2.0 and the TriMax Triclustering in Wineinformatics
- Wineinformatics: Uncork Napa's Cabernet Sauvignon by Association Rule Based Classification
- Wineinformatics: Applying Data Mining on Wine Sensory Reviews Processed by the Computational Wine Wheel
- The Computational Wine Wheel 2.0 and the TriMax Triclustering in Wineinformatics
- Understanding the Wine Judges and Evaluating the Consistency Through White-Box Classification Algorithms
- PROTEIN LOCAL TERTIARY STRUCTURE PREDICTION BY SUPER GRANULE SUPPORT VECTOR MACHINES WITH CHOU-FASMAN PARAMETER
- Protein Local Tertiary Structure Prediction Using the Adaptively-Branching FGK-DF Model
- Protein local 3D structure prediction by Super Granule Support Vector Machines (Super GSVM)
- PROTEIN LOCAL TERTIARY STRUCTURE PREDICTION BY SUPER GRANULE SUPPORT VECTOR MACHINES WITH CHOU-FASMAN PARAMETER
- Sparse nonnegative matrix factorization for protein sequence motif discovery
- PROTEIN LOCAL TERTIARY STRUCTURE PREDICTION BY SUPER GRANULE SUPPORT VECTOR MACHINES WITH CHOU-FASMAN PARAMETER
- Analysis of density based and fuzzy c-means clustering methods on lesion border extraction in dermoscopy images
- Mining Positional Association Super-Rules on Fixed-Size Protein Sequence Motifs
- Interval-Valued Centroids in K-Means Algorithms
- A Computational Study of Interval-Valued Matrix Games
- Wineinformatics: Applying Data Mining on Wine Sensory Reviews Processed by the Computational Wine Wheel
- Protein Local Tertiary Structure Prediction Using the Adaptively-Branching FGK-DF Model
- Classification on grade, price, and region with multi-label and multi-target methods in wineinformatics
- Interval-Valued Centroids in K-Means Algorithms
- Using Hybrid Hierarchical K-means (HHK) clustering algorithm for protein sequence motif Super-Rule-Tree (SRT) structure construction
- Protein Sequence Motif Super-Rule-Tree (SRT) Structure Constructed by Hybrid Hierarchical K-Means Clustering Algorithm