Xue Wu | Cognitive Science | Outstanding Scientist Award

Assoc. Prof. Dr. Xue Wu | Cognitive Science | Outstanding Scientist Award

Associate Professor | Peking University | China

Dr. Xue Wu is a highly active and emerging scholar whose research contributions reflect a growing impact in nursing science, healthcare safety, and clinical decision-support systems. With 621 citations, 39 publications, and an h-index of 8, her work demonstrates both productivity and increasing global relevance across interdisciplinary domains. She has contributed to the advancement of cognitive workload assessment, nursing brand development, and predictive modeling for critical care, including the integration of radiology notes and structured clinical data for early ICU readmission risk prediction. Her publications span peer-reviewed journals and collaborative multi-author studies, reflecting strong engagement with diverse research teams—evidenced by collaborations with over 80 co-authors across nursing, medical informatics, and safety management. Dr. Wu’s recent projects, including integrative and scoping reviews on safety-related cognitive workload and professional identity in nursing, reinforce her commitment to strengthening healthcare systems through evidence-based analysis. Her work emphasizes methodological rigor, interdisciplinary synthesis, and the development of tools that enhance patient safety, workforce identity, and clinical outcomes. Through her contributions to predictive analytics and safety frameworks, she supports the transformation of healthcare environments into more adaptive, data-informed, and patient-centered systems. Dr. Xue Wu’s research trajectory continues to contribute meaningfully to the global nursing and healthcare community, advancing knowledge that informs policy, technology design, and clinical practice.

Profiles: Scopus | ResearchGate

Featured Publications

  1. Feng, T., Huang, L., Peng, X., & Wu, X. (2025). An integrative review of cognitive workload assessment for safety management. BMC Nursing.

  2. Ge, H., Hu, H., Li, J., & Wu, X. (2025). Development of a professional profile for enhancing nursing brand image: A scoping review. International Nursing Review.

  3. Hu, H., Ma, L., Ge, H., & Wu, X. (2025). ReAdmit: Predicting early unplanned ICU readmission using radiology notes and structured data. Nursing in Critical Care.

  4. Hu, H., Teng, H., Bai, L., & Wu, X. (2025). Effect of interference on nurses in using nursing information system: A field-based eye tracking study. In Nursing Informatics Research (Book chapter).

  5. Ge, H., Feng, T., Hu, H., & Wu, X. (2025). Profiling learning styles and strategies of nursing students: A cluster analysis study. Nurse Education Today.

Feng Mao | Cognitive Science | Best Researcher Award

Assist. Prof. Dr. Feng Mao | Cognitive Science | Best Researcher Award

Associate Professor | Shanghai University of International Business and Economics | China

Assist. Prof. Dr. Feng Mao is a distinguished Associate Professor and Senior Translator at Shanghai University of International Business and Economics with 28 years of higher education experience, specializing in country and area studies, translation studies, and foreign language education. He is currently pursuing a Ph.D. at Shanghai International Studies University (since 2022) and serves as a Master’s supervisor for MA in Linguistics and MTI programs. Over his career, he has led 11 research projects, including a national-level Social Science Fund project, and collaborated with international scholars from Singapore, Canada, the UK, and Germany, reflecting his strong global research network. His professional experience includes mentoring MA students, peer reviewing for SSCI and AHCI journals, editorial committee service, and contributions to national professional assessments, including CATTI examination grading. His research interests focus on translation and interpreting studies, foreign language education and policy, cross-cultural communication, applied linguistics, audiovisual translation, and country and area studies. MAO Feng has developed advanced research skills in big data analysis for textbook and material compilation, literary analysis, audiovisual translation methods, and educational program evaluation, supporting both theoretical and applied projects. He has authored 64 academic publications, including 20 SSCI/AHCI journal papers with 5 in Q1 journals, and published 5 academic monographs and translations totaling over 2 million words, alongside textbooks and review articles that serve thousands of students. He has also contributed to industry and government consultancy projects such as cultural brand promotion and copyright export research. His awards and honors include national-level recognition for professional degree assessment and leadership roles within the China Association for Educational Linguistics and the Translators Association of China. Overall, MAO Feng’s extensive research, teaching, publications, and international collaborations highlight his exceptional academic leadership and ongoing potential to advance translation studies and foreign language education globally. 7 Citations, 8 Documents, h-index 2.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

Mao, F., & Yang, X. (2024). Literary therapy based on positive psychology: Impact on college students’ happiness. Journal of Poetry Therapy, 37(1), 16–34. https://doi.org/[insert DOI] (Citations: 5)

Mao, F., & Liu, S. (2024). Book review: Networked feminism: How digital media makers transformed gender justice movements (R. Clark-Parsons, California, University of California Press, 2022). Feminist Media Studies, 24(2), 404–406. (Citations: 3)

Feng, M., Wenhui, L., Xinle, Y., & Biyu, W. (2022). Romantic narrative in the film The Battle at Lake Changjin. International Journal of English and Comparative Literary Studies, 3(1), 19–27. (Citations: 3)

Feng, M., Quan, L., & Wu, B. (2021). A review on the compilation of college English textbooks in China based on big data. Sino-US English Teaching, 18(3), 60–65. (Citations: 3)

Feng, M., Quan, L., & Biyu, W. (2021). Exploration of the compilation of English learning materials for Chinese college students based on big data under the guidance of complex dynamic theory. International Journal of Linguistics, Literature and Translation, 4(3), 22–32. (Citations: 2)