Bernard Chen
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Researcher
Also affiliated: University of Southern California (2018); Troy University (2025); Emory University (2022); The University of Melbourne (2019–2024); The University of Texas at San Antonio Health Science Center (2023); Georgia State University (2006–2008); Kun Shan University (2006); Australian Regenerative Medicine Institute (2014–2016); The Royal Victorian Eye & Ear Hospital (2019–2025); Conway School of Landscape Design (2009–2025); CRC for Rail Innovation (2011); The University of Texas at San Antonio (2022–2023); Monash University (1989–2024); East Stroudsburg University (2012); University of Pennsylvania (2012); Beihang University (1985); Nanjing University of Aeronautics and Astronautics (2022)
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Bernard Chen's research centers on developing and validating predictive models for health and performance, drawing on data from wearable sensors, biological samples, and medical imaging. His work includes a focus on exercise-induced fatigue, using motion data and advanced algorithms to forecast real-time fatigue levels. This research aims to improve training regimens and potentially prevent injuries in athletes and individuals engaged in physical activity.
Chen also investigates therapeutic interventions and treatment planning in oncology. He has published research on voxel-based dosimetry for predicting treatment response and toxicity in patients with hepatocellular carcinoma (HCC) undergoing Yttrium-90 radioembolization. This work involves analyzing imaging data to optimize radiation therapy delivery and improve patient outcomes. Additionally, his research extends to medical device development, including the use of polymeric fiber sensors for monitoring insertion forces and trajectory during cochlear implant surgeries, with an emphasis on hearing preservation.
His broader research interests encompass the application of data-driven approaches and biomechanical principles across various domains. This includes quantifying the impact of infrastructure on advanced driver-assistance systems and exploring sustainable materials for construction. Chen leads a research group and has an h-index of 28 with over 3,800 citations across 164 publications, indicating significant impact in his fields of study.
Metrics
- h-index: 28
- Publications: 164
- Citations: 3,871
Selected Publications
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Privacy-Preserving Secure Framework for Intelligent Transportation Systems (2025)
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Wineinformatics: Wine Score Prediction with Wine Price and Reviews (2024)
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Applying Neural Networks in Wineinformatics with the New Computational Wine Wheel (2023)
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Advanced Usage of the Computational Wine Wheel (2022)
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Introduction (2022)
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Wineinformatics (2022)
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Data Collection and Preprocessing (2022)
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Multi-Class, Multi-Label and Multi-Target in Wineinformatics (2022)
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Conclusion and Future Works (2022)
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Regression in Wineinformatics (2022)
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Classification in Wineinformatics (2022)
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Evaluation of Wine Judges (2022)
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Wineinformatics: Comparing and Combining SVM Models Built by Wine Reviews from Robert Parker and Wine Spectator for 95 + Point Wine Prediction (2022)
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Wineinformatics: Can Wine Reviews in Bordeaux Reveal Wine Aging Capability? (2021)
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Clustering in Wineinformatics with Attribute Selection to Increase Uniqueness of Clusters (2021)
Collaboration Network
Top Collaborators
- Applying Neural Networks in Wineinformatics with the New Computational Wine Wheel
- Wineinformatics: Comparing and Combining SVM Models Built by Wine Reviews from Robert Parker and Wine Spectator for 95 + Point Wine Prediction
- Wineinformatics: Wine Score Prediction with Wine Price and Reviews
- Privacy-Preserving Secure Framework for Intelligent Transportation Systems
- Wineinformatics: Using the Full Power of the Computational Wine Wheel to Understand 21st Century Bordeaux Wines from the Reviews
- Wineinformatics: Using the Full Power of the Computational Wine Wheel to Understand 21st Century Bordeaux Wines from the Reviews
- Clustering in Wineinformatics with Attribute Selection to Increase Uniqueness of Clusters
- Clustering in Wineinformatics with Attribute Selection to Increase Uniqueness of Clusters
- Wineinformatics: Can Wine Reviews in Bordeaux Reveal Wine Aging Capability?
- Wineinformatics: Can Wine Reviews in Bordeaux Reveal Wine Aging Capability?
- Wineinformatics: Can Wine Reviews in Bordeaux Reveal Wine Aging Capability?
- Wineinformatics: Comparing and Combining SVM Models Built by Wine Reviews from Robert Parker and Wine Spectator for 95 + Point Wine Prediction
- Applying Neural Networks in Wineinformatics with the New Computational Wine Wheel
- Applying Neural Networks in Wineinformatics with the New Computational Wine Wheel
- Applying Neural Networks in Wineinformatics with the New Computational Wine Wheel
- Privacy-Preserving Secure Framework for Intelligent Transportation Systems
- Privacy-Preserving Secure Framework for Intelligent Transportation Systems
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