Fang-Rong Hsu | Data Science | Best Researcher Award

Prof. Fang-Rong Hsu | Data Science | Best Researcher Award

Professor at Department of Information Engineering and Computer Science/Feng Chia University, Taiwan

Dr. Fang-Rong Hsu πŸŽ“, a distinguished expert in bioinformatics, AI, and medical image processing πŸ§ πŸ–ΌοΈ, has made remarkable contributions to interdisciplinary research at the intersection of computer science and healthcare πŸ’»β€οΈ. With a Ph.D. in algorithm design from National Chiao-Tung University and decades of academic leadership 🏫, he has published extensively in top-tier SCIE journals and conferences πŸŒπŸ“š. His cutting-edge work spans AI-driven diagnostics, vision transformers, and smart health technologies πŸ€–πŸ§¬. As a professor and former director at Feng Chia University, Dr. Hsu has influenced both research and education profoundly πŸ“ˆπŸ‘¨β€πŸ«. Known for impactful real-world applicationsβ€”from cancer detection to IoT-based safety systemsβ€”his research continues to shape the future of intelligent healthcare and data science πŸš‘πŸ“Š. Dr. Hsu is a leading force in innovation and scientific excellence πŸ….

Professional ProfileΒ 

Scopus Profile
ORCID Profile

πŸŽ“ Education

Dr. Fang-Rong Hsu earned his Ph.D. in Algorithm Design and Analysis from the Department of Computer Science & Information Engineering at National Chiao-Tung University, Taiwan (1992) πŸ§ πŸ’‘. He previously completed his B.S. in Computer Science at the same institution in 1986. His solid academic foundation in theoretical computing laid the groundwork for a multifaceted research career bridging algorithms, AI, and biomedical engineering πŸ“˜πŸ–₯️. With a deep interest in computational science and problem-solving, his educational journey reflects a strong commitment to both innovation and academic excellence πŸŽ―πŸ“š.

🏒 Professional Experience

Dr. Hsu has held multiple prestigious roles across Taiwanese universities 🏫. Currently a Professor in Information Engineering and Computer Science at Feng Chia University, he previously served as Director of the same department (2015–2018) and of the Bioinformatics Research Center (2004–2010) 🧬. His prior appointments include professorships and department chairs at Taichung Healthcare and Providence University, leading initiatives in IT, bioinformatics, and academic administration πŸ§‘β€πŸ«πŸ“ˆ. His career spans over three decades of leadership, education, and research guidance in computing and biomedical applications πŸ€πŸ”.

πŸ”¬ Research Interest

Dr. Hsu’s research interests span bioinformatics, parallel processing, and biomedical image processing πŸ§¬πŸ“ŠπŸ–ΌοΈ. His work focuses on integrating artificial intelligence into healthcare diagnostics, such as deep learning for cancer detection, medical image classification, and behavior analysis in zebrafish 🧠πŸ§ͺ. He is particularly passionate about explainable AI, computer vision, and AIoT applications in medical and public safety domains πŸŒβš•οΈ. His cross-disciplinary approach leverages computing power to address complex biological and clinical challenges, resulting in meaningful innovations that bridge academia and practical medicine πŸ”πŸ’‘.

πŸ… Awards and Honors

Dr. Hsu is a respected researcher recognized through numerous SCIE-indexed publications and invited international collaborations πŸŒπŸ“œ. While specific awards are not listed, his consistent authorship in prestigious journals such as IEEE Access, Frontiers in Bioengineering, and Diagnostics underscores his high-impact research reputation πŸ₯‡πŸ“–. His appointment to leadership roles in multiple institutions also reflects strong peer recognition and institutional trust. His global conference presence and academic service contributions further reinforce his standing as an accomplished scholar and thought leader in computer science and bioinformatics πŸŒŸπŸ§‘β€πŸ”¬.

πŸ› οΈ Research Skills

Dr. Hsu brings a powerful blend of skills including deep learning model development (CNN, ResNet, U-Net, ViT), biomedical image analysis, algorithm design, data mining, and AI-driven diagnostic systems πŸ€–πŸ”¬. He excels at integrating computer vision with health informatics and is experienced in parallel and embedded system implementation πŸ–₯οΈβš™οΈ. Skilled in interdisciplinary collaboration and academic writing, he leads high-impact research teams with strategic direction and technical precision. His technical expertise is matched by his ability to innovate across domainsβ€”from zebrafish modeling to smart city technologies πŸš€πŸ“‘.

Publications Top Note πŸ“

  • Title: Enhancing Safety with an AI-Empowered Assessment and Monitoring System for BSL-3 Facilities
    Authors: Yi-Ling Fan, Ching-Han Hsu, Fang-Rong Hsu, et al.
    Year: 2025
    Source: Heliyon

  • Title: Hybrid Top Features Extraction Model for Detecting X Rumor Events Using an Ensemble Method
    Authors: Taukir Alam, Wei Chung Shia, Fang-Rong Hsu, Taimoor Hassan, Pei-Chun Lin, Eric Odle, Junzo Watada
    Year: 2025
    Source: Journal of Web Engineering

  • Title: Coating Process Control in Lithium-Ion Battery Manufacturing Using Cumulative Sum Charts
    Authors: Min-Chang Liu, Fang-Rong Hsu, Chua-Huang Huang
    Year: 2024
    Citations: 1
    Source: Production Engineering

  • Title: Next-Generation Swimming Pool Drowning Prevention Strategy Integrating AI and IoT Technologies
    Authors: Wei-Chun Kao, Yi-Ling Fan, Fang-Rong Hsu, Chien-Yu Shen, Lun-De Liao
    Year: 2024
    Citations: 3
    Source: Heliyon

  • Title: Complex Event Recognition and Anomaly Detection with Event Behavior Model
    Authors: Min-Chang Liu, Fang-Rong Hsu, Chua-Huang Huang
    Year: 2024
    Citations: 1
    Source: Pattern Analysis and Applications

πŸ“Œ Conclusion

Dr. Fang-Rong Hsu exemplifies the spirit of research excellence through his deep academic roots, broad interdisciplinary vision, and unwavering dedication to solving real-world challenges 🌐🧠. His contributions to artificial intelligence in healthcare, sustained publication record, and leadership roles make him a standout figure in the scientific community πŸ…πŸ“š. As a scholar, mentor, and innovator, he continues to influence both present and future generations of researchers in computing, biomedicine, and beyond πŸŒ±πŸ”. Dr. Hsu is an exemplary candidate for top-tier recognition in research leadership and innovation πŸ†πŸŽ“.

Meichen Feng | Data Science | Best Researcher Award

Prof. Meichen Feng | Data Science | Best Researcher Award

Professor at Shanxi Agricultural University, China.

Feng Meichen is a distinguished professor at Shanxi Agricultural University, specializing in crop ecology, precision agriculture, and agricultural information technology. As the Deputy Dean of the College of Agriculture, she has led 22 research projects, authored 82 SCI/Scopus-indexed papers, and secured 18 patents, demonstrating a strong commitment to advancing sustainable agriculture. With 988 citations and an H-index of 19, her work has significantly impacted agricultural innovation and technology. She has published 5 books, contributed to multiple academic committees, and serves on the editorial boards of leading agricultural journals. Her research focuses on improving crop yield, resource efficiency, and environmental sustainability, benefiting both academia and local farming communities. While her expertise is well-recognized in China, expanding global collaborations could further enhance her research impact. With a remarkable career in agricultural research and innovation, Feng Meichen is an outstanding candidate for the Best Researcher Award.

Professional ProfileΒ 

Scopus Profile
ORCID Profile

Education

Feng Meichen holds an advanced degree in agriculture and crop ecology, equipping her with a deep understanding of agricultural information technology, precision farming, and ecological sustainability. Her academic journey has been dedicated to exploring innovative agricultural techniques that improve productivity while ensuring environmental sustainability. Through extensive research and continuous professional development, she has gained expertise in 3S technology (GIS, GPS, and remote sensing) and its application in modern agriculture. Her education has provided a strong foundation for her contributions to precision agriculture, crop management, and smart farming technologies. With a commitment to advancing agricultural science, she has successfully integrated academic knowledge with practical applications, benefiting both researchers and farming communities. Her ability to translate theoretical concepts into real-world solutions has made her a recognized leader in the field of crop science and agricultural technology.

Professional Experience

As a Professor and Deputy Dean at the College of Agriculture, Shanxi Agricultural University, Feng Meichen has established herself as a leader in agricultural research and education. She has successfully led 22 major research projects, contributing to advancements in crop ecology, precision farming, and smart agriculture. Her expertise extends beyond academia, as she actively collaborates with government agencies, research institutions, and industry leaders to develop sustainable farming practices. She has authored 82 peer-reviewed journal articles, secured 18 patents, and published 5 books, showcasing her multidisciplinary expertise. Additionally, she serves on the editorial boards of prestigious agricultural journals, including the Journal of Smart Agriculture and Shanxi Agricultural Sciences. She is also a member of multiple professional committees, influencing agricultural policies and research directions in China. Her extensive academic, research, and administrative experience highlights her dedication to advancing agricultural science and technology for long-term sustainability.

Research Interests

Feng Meichen’s research focuses on crop ecology, precision agriculture, and agricultural information technology, with an emphasis on sustainable and smart farming solutions. She integrates 3S technology (GIS, GPS, remote sensing) with crop production models to enhance agricultural efficiency, resource management, and environmental conservation. Her work aims to optimize crop yield, reduce environmental impact, and improve agricultural decision-making processes. She is particularly interested in applying artificial intelligence and big data analytics to develop predictive models for crop health monitoring and precision irrigation systems. Her research extends to organic dryland agriculture, where she explores climate-resilient farming techniques. By collaborating with industry experts, policymakers, and farmers, she ensures that her research findings have practical applications that benefit the agricultural sector. Her commitment to advancing smart agriculture technologies positions her as a pioneering researcher in the field of modern agriculture.

Awards and Honors

Feng Meichen has received multiple awards and recognitions for her outstanding contributions to agricultural science and research. As a Deputy Chief Expert in the Shanxi Modern Agricultural Specialty Grain Industry Technology System, she has played a pivotal role in shaping agricultural policies and technologies. Her patents and scientific contributions have earned her recognition at national and provincial levels. She has been honored by Shanxi Agricultural University and various academic organizations for her contributions to precision farming, agricultural technology development, and ecological sustainability. She is a member of several prestigious agricultural committees, including the China Modern Agriculture Graduate School and the Chinese Society of Crops. Through her active involvement in academic and industry collaborations, she continues to make a lasting impact on the agricultural sector. Her dedication to agricultural innovation and sustainability has established her as a leading researcher and academician.

Conclusion

Feng Meichen is a highly accomplished researcher, academic leader, and innovator in agricultural science. With extensive research contributions, patents, and leadership roles, she has significantly advanced the fields of crop ecology, precision agriculture, and smart farming technologies. Her work has not only improved crop productivity and resource efficiency but also contributed to sustainable farming practices that benefit both academic research and practical applications. While her impact is widely recognized in China, expanding international collaborations and industry partnerships could further elevate her global research influence. Her dedication to scientific excellence, innovation, and sustainability makes her an outstanding candidate for the Best Researcher Award.

Publications Top Noted

2025 Publications

πŸ”Ή Evaluating the Potential of Airborne Hyperspectral Imagery in Monitoring Common Beans with Common Bacterial Blight at Different Infection Stages

  • Authors: Binghan Jing, Jiachen Wang, Xin Zhang, Xiaoxiang Hou, Kunming Huang, Qianyu Wang, Yiwei Wang, Yaoxuan Jia, Meichen Feng, Wude Yang et al.
  • Year: 2025
  • DOI: 10.1016/j.biosystemseng.2025.02.002
  • Source: Biosystems Engineering (Crossref)

πŸ”Ή Potential Impacts of Climate Change on the Spatial Distribution Pattern of Naked Oats in China

  • Authors: Zhenwei Yang, Xujing Yang, Yuheng Huang, Yalin Zhang, Yao Guo, Meichen Feng, Mingxing Qin, Ning Jin, Muhammad Amjad, Chao Wang et al.
  • Year: 2025
  • DOI: 10.3390/agronomy15020362
  • Source: Agronomy (Crossref)

2024 Publications

πŸ”Ή A Model for the Detection of Ξ²-Glucan Content in Oat Grain Based on Near Infrared Spectroscopy

  • Authors: Yang Z., Cheng Z., Su P., Wang C., Qin M., Song X., Xiao L., Yang W., Feng M., Zhang M.
  • Year: 2024
  • DOI: 10.1016/j.jfca.2024.106105
  • Source: Journal of Food Composition and Analysis (Scopus – Elsevier)

πŸ”Ή Combined Use of Spectral Resampling and Machine Learning Algorithms to Estimate Soybean Leaf Chlorophyll

  • Authors: Gao C., Li H., Wang J., Zhang X., Huang K., Song X., Yang W., Feng M., Xiao L., Zhao Y. et al.
  • Year: 2024
  • DOI: 10.1016/j.compag.2024.108675
  • Source: Computers and Electronics in Agriculture (Scopus – Elsevier)

πŸ”Ή Efficient Prediction of SOC and Aggregate OC Components by Continuous Wavelet Transform Spectra Under Different Feature Selection Methods

  • Authors: Yang S., Wang Z., Ji C., Hao Y., Liang Z., Yan X., Qiao X., Feng M., Xiao L., Song X. et al.
  • Year: 2024
  • DOI: 10.1016/j.compag.2023.108550
  • Source: Computers and Electronics in Agriculture (Scopus – Elsevier)

πŸ”Ή Prediction of the Potential Distribution and Analysis of the Freezing Injury Risk of Winter Wheat on the Loess Plateau Under Climate Change

  • Authors: Qing Liang, Xujing Yang, Yuheng Huang, Zhenwei Yang, Meichen Feng, Mingxing Qing, Chao Wang, Wude Yang, Zhigang Wang, Meijun Zhang et al.
  • Year: 2024
  • Source: Journal of Integrative Agriculture

2023 Publications

πŸ”Ή AMF Inoculation Positively Regulates Soil Microbial Activity and Drought Tolerance of Oat

  • Authors: Li Y., Li L., Zhang B., LΓΌ Y.-F., Feng M.-C., Wang C., Song X.-Y., Yang W.-D., Zhang M.-J.
  • Year: 2023
  • DOI: 10.11674/zwyf.2022561
  • Source: Journal of Plant Nutrition and Fertilizers (Scopus – Elsevier)

πŸ”Ή Analyzing Protein Concentration from Intact Wheat Caryopsis Using Hyperspectral Reflectance

  • Authors: Zhang X., Hou X., Su Y., Yan X., Qiao X., Yang W., Feng M., Kong H., Zhang Z., Shafiq F. et al.
  • Year: 2023
  • DOI: 10.21203/rs.3.rs-2887647/v1
  • Source: Research Square

πŸ”Ή Hyperspectral Monitoring of Growth and Physiology Parameters of Winter Wheat Based on Different Quantification Methods

  • Authors: Wang Z.-G., Yang S., Feng M.-C., Yang W.-D., Liang Q., Yang X.-J., Yan X.-B., Sun X.-K., Qin M.-X., Wang C. et al.
  • Year: 2023
  • DOI: 10.2139/ssrn.4535833
  • Source: SSRN

πŸ”Ή Identification of Structural Variations Related to Drought Tolerance in Wheat (Triticum aestivum L.)

  • Authors: Zhao J., Li X., Qiao L., Zheng X., Wu B., Guo M., Feng M., Qi Z., Yang W., Zheng J.
  • Year: 2023
  • DOI: 10.1007/s00122-023-04283-4
  • Source: Theoretical and Applied Genetics (Scopus – Elsevier)