Hye-Won Jung | Food Safety | Innovative Research Award

Posted on by Food Scientist

Innovative Research Award

Hye-Won Jung
Adelaide MRI, Australia

Hye-Won Jung
Affiliation Adelaide MRI
Country Australia
Scopus ID 57037522300
Documents 10
Citations 225
h-index 7
Subject Area Food Safety and Quality Control
Event International Food Scientist Awards
ORCID 0000-0002-0057-0818

Hye-Won Jung is a researcher affiliated with AdelaideMRI whose scholarly activities encompass food safety, quality control, hyperspectral imaging, artificial intelligence, computer vision, and nondestructive analytical technologies. The available Scopus metrics indicate a developing research profile comprising ten indexed publications, 225 citations, and an h-index of 7. The research portfolio demonstrates interdisciplinary collaboration across food science, biomedical imaging, machine learning, and optical sensing, with contributions to rapid contaminant detection and advanced image analysis methods. These achievements provide a strong basis for recognition within the International Food Scientist Awards while reflecting continued engagement with innovative analytical technologies.[1]

Abstract

The research activities of Hye-Won Jung focus on the integration of advanced imaging technologies, artificial intelligence, and chemometric analysis for food quality assessment and biomedical image interpretation. Published studies demonstrate expertise in hyperspectral imaging, optical spectroscopy, deep learning, and computer vision for nondestructive inspection systems. Recent investigations further extend these analytical methods into automated clinical image interpretation using attention-gated deep learning frameworks, illustrating broad interdisciplinary capability across food safety and medical imaging.[2]

Keywords

Food Safety, Quality Control, Hyperspectral Imaging, Artificial Intelligence, Deep Learning, Chemometrics, Optical Imaging, Computer Vision

Introduction

Modern food safety increasingly depends on rapid, nondestructive analytical technologies capable of detecting contaminants while preserving sample integrity. Hye-Won Jung has contributed to this evolving field through research involving hyperspectral imaging, optical spectroscopy, chemometric modelling, and machine learning approaches that improve contaminant detection and product quality evaluation. The interdisciplinary nature of these investigations aligns with international priorities for safer food systems and intelligent analytical technologies.[3]

Research Profile

The research profile combines expertise in food science, biomedical engineering, computer vision, and artificial intelligence. Published work spans peer-reviewed journals including LWT, Comprehensive Reviews in Food Science and Food Safety, Pattern Recognition, and Applied Sciences. Research emphasizes practical analytical solutions that improve diagnostic accuracy, contaminant screening, and automated image interpretation while supporting scientific reproducibility and technological innovation.[2]

Research Contributions

  • Development of SWIR hyperspectral imaging methods for rapid detection of aflatoxin B1 in almonds.
  • Comprehensive reviews of optical imaging technologies for nondestructive mycotoxin detection.
  • Machine learning and attention-gated deep learning applications in medical image analysis.
  • Computer vision algorithms for particle tracking in synchrotron X-ray imaging.
  • Interdisciplinary integration of food safety analytics with advanced computational methods.

Publications

  1. Advanced Clinical Analysis Based on Automated Cardiothoracic Ratio Estimation Using Attention-Gated Deep Learning. Applied Sciences, 2026. DOI: 10.3390/app16147019
  2. Application of SWIR hyperspectral imaging coupled with chemometrics for rapid and non-destructive prediction of Aflatoxin B1 in single kernel almonds. LWT, 2022. DOI: 10.1016/j.lwt.2021.112954
  3. Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts. Comprehensive Reviews in Food Science and Food Safety, 2021. DOI: 10.1111/1541-4337.12801
  4. Multiple particle tracking in time-lapse synchrotron X-ray images using discriminative appearance and neighbouring topology learning. Pattern Recognition, 2019. DOI: 10.1016/j.patcog.2019.05.007
  5. Multiple mucociliary transit marker tracking in synchrotron X-ray images using the global nearest neighbor method. IEEE EMBC, 2017. DOI: 10.1109/EMBC.2017.8037200

Research Impact

Based on the available Scopus profile, the researcher has accumulated 225 citations with an h-index of 7 across ten indexed publications. Citation performance reflects meaningful scholarly influence within interdisciplinary research involving food safety, imaging science, chemometrics, and computational analysis. The body of work has contributed to improved methodologies for contaminant detection, optical sensing, and intelligent image processing, supporting continued scientific advancement.[1]

Award Suitability

The available publication record demonstrates sustained contributions to innovative analytical technologies applicable to food safety and quality control. The integration of hyperspectral imaging, chemometric modelling, artificial intelligence, and optical sensing reflects research that addresses contemporary scientific and industrial challenges. These achievements indicate strong suitability for recognition under the Innovative Research Award category of the International Food Scientist Awards, particularly for interdisciplinary research advancing nondestructive food analysis and intelligent imaging technologies.[3]

Conclusion

Hye-Won Jung has established an interdisciplinary research portfolio spanning food science, biomedical imaging, computer vision, and artificial intelligence. Through peer-reviewed publications and measurable citation impact, the researcher has contributed to the advancement of nondestructive analytical technologies and intelligent image analysis. The documented scholarly achievements provide a well-supported academic profile suitable for international professional recognition.

References

  1. Elsevier. (n.d.). Scopus Author Details: Hye-Won Jung, Author ID 57037522300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57037522300
  2. Jung, H.-W., et al. (2026). Advanced Clinical Analysis Based on Automated Cardiothoracic Ratio Estimation Using Attention-Gated Deep Learning. Applied Sciences.
    DOI: https://doi.org/10.3390/app16147019
  3. Jung, H.-W., et al. (2022). Application of SWIR hyperspectral imaging coupled with chemometrics for rapid and non-destructive prediction of Aflatoxin B1 in single kernel almonds. LWT. DOI: https://doi.org/10.1016/j.lwt.2021.112954
  4. Jung, H.-W., et al. (2021). Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts. Comprehensive Reviews in Food Science and Food Safety. DOI: https://doi.org/10.1111/1541-4337.12801
  5. Jung, H.-W., et al. (2019). Multiple particle tracking in time-lapse synchrotron X-ray images using discriminative appearance and neighbouring topology learning. Pattern Recognition.
    DOI: https://doi.org/10.1016/j.patcog.2019.05.007

Ahmed Mostafa | Food Safety | Innovative Research Award

Posted on by Food Scientist

Innovative Research Award

Ahmed Mostafa
Affiliation Imam Abdulrahman Bin Faisal University
Country Saudi Arabia
Scopus ID 7006119393
Documents 50
Citations 1235
h-index 22
Subject Area Food Safety and Quality Control
Event International Food Scientist Awards
ORCID 0000-0002-3350-8519

Ahmed Mostafa
Imam Abdulrahman Bin Faisal University, Saudi Arabia

Ahmed Mostafa is a researcher affiliated with Imam Abdulrahman Bin Faisal University, Saudi Arabia. His scholarly work focuses on food safety, analytical chemistry, green extraction technologies, pharmaceutical residue monitoring, biomaterials, computational drug discovery, and quality control methodologies. His publication portfolio demonstrates sustained contributions toward environmentally sustainable analytical methods and advanced instrumental techniques for food contaminant determination, making his research relevant to modern food quality assurance and public health initiatives.[1]

Abstract

Ahmed Mostafa research portfolio combines sustainable analytical chemistry with food safety applications. His studies emphasize the development of environmentally friendly deep eutectic solvent extraction systems, ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC–MS/MS), and computational methodologies for antimicrobial drug discovery. These investigations contribute to accurate monitoring of antibiotic residues, endocrine-disrupting chemicals, and other contaminants while promoting greener laboratory practices.[2]

Keywords

Food Safety, Quality Control, Natural Deep Eutectic Solvents, UHPLC-MS/MS, Green Analytical Chemistry, Antibiotic Residues, Food Contaminants, Microextraction

Introduction

Food safety continues to be an important component of public health, requiring sensitive analytical technologies capable of detecting trace contaminants. Ahmed Mostafa’s research addresses this challenge by integrating sustainable extraction approaches with advanced chromatographic and mass spectrometric techniques. His work also reflects increasing international interest in reducing solvent consumption and environmental impact while maintaining high analytical accuracy.[3]

Research Profile

According to the available scholarly metrics, Ahmed Mostafa has authored 50 indexed publications with more than 1,235 citations and an h-index of 22. His research interests include analytical chemistry, food contaminant monitoring, green solvent technology, biomaterials, pharmaceutical analysis, computational chemistry, and laboratory quality assurance.[1]

Research Contributions

  • Development of natural deep eutectic solvent-based microextraction methods for food contaminant analysis.
  • Application of UHPLC-MS/MS platforms for ultra-trace detection of antibiotic residues.
  • Research on environmentally sustainable analytical methodologies supporting green chemistry principles.
  • Computational identification of antimicrobial lead compounds using high-throughput molecular modeling.
  • Studies involving biomaterials and dental resin cytocompatibility.

Publications

  1. Natural Deep Eutectic Solvent-Based Dispersive Liquid–Liquid Microextraction Coupled with UHPLC–MS/MS for the Determination of Antibiotic Residues in Food Products (Antibiotics, 2026).
  2. Sustainable Anisaldehyde-Based Natural Deep Eutectic Solvent Dispersive Liquid–Liquid Microextraction for Monitoring Antibiotic Residues in Commercial Milk and Eggs (Foods, 2026).
  3. In Silico Lead Identification of Staphylococcus aureus LtaS Inhibitors (International Journal of Molecular Sciences, 2025).
  4. Monomer Leaching and Cytocompatibility Analyses of Bioactive Glasses-Based Dental Resin Infiltrants (Journal of Applied Polymer Science, 2025).
  5. DES-DLLME Followed by UPLC–MS/MS for Simultaneous Determination of Selected Parabens and Bisphenols in Food Products (Microchemical Journal, 2024).

Research Impact

The research demonstrates practical significance for food safety laboratories, regulatory agencies, and analytical scientists seeking environmentally responsible testing procedures. Publications on natural deep eutectic solvent extraction have contributed to expanding sustainable analytical methodologies while maintaining analytical sensitivity and reliability for complex food matrices.[4]

Award Suitability

Based on documented publication output, citation performance, and research focus, Ahmed Mostafa’s work aligns with the objectives of the Innovative Research Award within the International Food Scientist Awards. His scholarly activities demonstrate continuous contributions toward analytical innovation, sustainable laboratory practices, food quality monitoring, and interdisciplinary scientific advancement.

Conclusion

Ahmed Mostafa has established a research profile characterized by rigorous analytical methodology, sustainable chemistry, and food safety applications. His scientific publications contribute to improving contaminant detection technologies while promoting environmentally responsible analytical practices. Collectively, these achievements represent meaningful contributions to food science and quality control research.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Ahmed Mostafa, Author ID 7006119393. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7006119393
  2. Mostafa A. (2026). Natural Deep Eutectic Solvent-Based Dispersive Liquid–Liquid Microextraction Coupled with UHPLC–MS/MS for the Determination of Antibiotic Residues in Food Products. Antibiotics.
    DOI:https://doi.org/10.3390/antibiotics15070644
  3. Mostafa A. (2026). Sustainable Anisaldehyde-Based Natural Deep Eutectic Solvent Dispersive Liquid–Liquid Microextraction for Monitoring Antibiotic Residues in Commercial Milk and Eggs. Foods.
    https://doi.org/10.3390/foods15020258
  4. Mostafa A. (2024). Anisaldehyde-based DES-DLLME followed by UPLC–MS/MS for simultaneous determination of selected parabens and bisphenols in food products. Microchemical Journal.
    https://doi.org/10.1016/j.microc.2024.110981