Qiuli Gu | Human Factors related to Air Traffic Controllers | Innovative Research Award

Posted on by Global HRM Awards

Innovative Research Award

Qiuli Gu
Civil Aviation University of China, China

Qiuli Gu
Affiliation Civil Aviation University of China
Country China
Scopus ID 56185253500
Documents 7
Citations 6
h-index 2
Subject Area Human Factors related to Air Traffic Controllers
Event Global HRM Awards

Qiuli Gu is a researcher affiliated with the Civil Aviation University of China whose work focuses on human factors, air traffic control systems, workload assessment, psychophysiological monitoring, and aviation safety. Her research contributes to understanding the interaction between human cognitive performance and operational efficiency within aviation environments. Recent studies have explored personalized workload tolerance models using multimodal psychophysiological data to support safer and more adaptive air traffic management systems.[1]

Abstract

This article presents an overview of the academic profile and research contributions of Qiuli Gu. Her research investigates workload tolerance, psychophysiological assessment, human performance, and decision-support mechanisms within air traffic control systems. By integrating multimodal data approaches into aviation research, her work contributes to the development of personalized and adaptive operational frameworks that support aviation safety and efficiency.[1]

Keywords

Air Traffic Control, Human Factors, Industrial Ergonomics, Aviation Safety, Cognitive Workload, Psychophysiological Data, Human Performance, Aviation Psychology, Multimodal Analytics, Decision Support Systems.

Introduction

The increasing complexity of modern aviation operations requires advanced methods for monitoring human performance and managing cognitive workload. Research in human factors and ergonomics plays a critical role in ensuring operational safety. Qiuli Gu’s work addresses these challenges through innovative approaches that combine physiological measurements, behavioral indicators, and data-driven analysis to improve workload assessment in air traffic control environments.[1]

Research Profile

According to Scopus, Qiuli Gu has authored seven indexed publications, received six citations, and achieved an h-index of two. Her research interests are centered on aviation ergonomics, cognitive workload measurement, psychophysiological monitoring, and personalized assessment frameworks for air traffic controllers. Her work reflects an interdisciplinary approach combining engineering, psychology, and aviation sciences.[1]

Research Contributions

  • Development of personalized workload tolerance frameworks for air traffic control operations.
  • Application of psychophysiological indicators to evaluate cognitive workload.
  • Integration of multimodal data sources for human performance assessment.
  • Research supporting aviation safety and operational decision-making.
  • Advancement of human-centered approaches in industrial ergonomics.

Publications

A representative publication within her research portfolio is listed below:[2]

  • Toward a Personalized Framework for Workload Tolerance in Air Traffic Control: A Psychophysiological Multimodal Data Approach (International Journal of Industrial Ergonomics, 2026).
  • A Study of Eye Movement Behavioral Differences Among Air Traffic Controllers.

Research Impact

Qiuli Gu’s research contributes to the growing field of human-centered aviation systems. By examining workload tolerance through psychophysiological and multimodal data analysis, her studies support the design of adaptive technologies and evidence-based strategies that can enhance aviation safety, controller well-being, and operational effectiveness. Such contributions are increasingly relevant as air traffic systems become more technologically sophisticated.[2]

Award Suitability

Qiuli Gu’s research demonstrates innovation through the integration of psychophysiological monitoring, multimodal analytics, and personalized workload assessment models. Her interdisciplinary approach addresses contemporary challenges in aviation safety and human performance, making her work relevant to recognition within programs that celebrate innovative research and emerging scholarly contributions.[1]

Conclusion

Qiuli Gu has contributed to the advancement of aviation human factors research through studies focused on workload tolerance, psychophysiological assessment, and multimodal data integration. Her work supports the development of safer and more adaptive air traffic management systems while demonstrating the value of interdisciplinary innovation in addressing operational challenges within modern aviation.

References

  1. Elsevier. (n.d.). Scopus author details: Qiuli Gu, Author ID 56185253500. Scopus.

    https://www.scopus.com/authid/detail.uri?authorId=56185253500

  2. Gu, Q. (2026). Toward a Personalized Framework for Workload Tolerance in Air Traffic Control: A Psychophysiological Multimodal Data Approach. International Journal of Industrial Ergonomics.

    https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5445930

  3. A Study of Eye Movement Behavioral Differences Among Air Traffic Controllers.

    http://link.springer.com/chapter/10.1007/978-3-032-12392-3_20

  4. Toward a Personalized Framework for Workload Tolerance in Air Traffic Control: A Psychophysiological Multimodal Data Approach (International Journal of Industrial Ergonomics, 2026).
    https://www.sciencedirect.com/science/article/abs/pii/S0169814126000995

Jun Yin | Organizational behavior | Innovative Research Award

Posted on by Global HRM Awards

Innovative Research Award

Jun Yin
Affiliation Shenzhen University
Country China
Scopus ID 57222541034
Documents 8
Citations 81
h-index 4
Subject Area Organizational behavior
Event Global HRM Awards

Jun Yin
Shenzhen University, Shenzhen, China

Jun Yin is a management scholar whose research explores organizational theories, workplace psychology, paradox mindset, mentoring, employee engagement, artificial intelligence in organizations, and knowledge management. His academic profile reflects interdisciplinary contributions that connect behavioral science with contemporary management challenges, particularly in the context of organizational learning, innovation, leadership, and employee performance.[1][2]

Abstract

This article presents an academic profile of Jun Yin, Assistant Professor at Shenzhen University. His scholarly work focuses on paradox mindset, organizational learning, mentoring, employee engagement, artificial intelligence in the workplace, and employee adaptive performance. Through publications in recognized management and behavioral science journals, he has contributed to contemporary discussions on leadership, innovation, knowledge renewal, and workplace dynamics.[1][3]

Keywords

Paradox Mindset; Organizational Learning; Artificial Intelligence; Employee Engagement; Mentoring; Knowledge Management; Leadership; Innovation; Adaptive Performance; Workplace Psychology.

Introduction

The growing complexity of modern organizations has increased scholarly interest in paradox theory, organizational behavior, and technology-enabled workplace transformation. Jun Yin’s research addresses these themes by examining how individuals and organizations navigate tensions, embrace learning, and adapt to emerging technological developments such as generative artificial intelligence.[4]

Research Profile

Jun Yin serves as Assistant Professor at Shenzhen University. His academic training includes doctoral studies in management at Hokkaido University, graduate education at the University of Leeds, and undergraduate studies at Lanzhou University. His interdisciplinary research integrates management theory, psychology, leadership studies, and organizational development.[1]

Research Contributions

His research contributions include advancing understanding of paradox mindset in organizations, explaining mechanisms that influence employee engagement and unlearning, examining leadership behaviors that foster adaptive capabilities, and investigating the organizational implications of artificial intelligence adoption. These studies contribute to both theoretical development and practical management applications.[4][5]

Publications

Selected publications include studies on generative AI stressors and employee adaptive performance, AI-enabled knowledge renewal, paradox mindset and workplace unlearning, paradoxical leadership, mentoring effectiveness, and employee engagement. These works have appeared in journals such as Journal of Knowledge Management, Asia Pacific Journal of Human Resources, Current Psychology, and Leadership & Organization Development Journal.[3][4][5]

Research Impact

According to Scopus author metrics, Jun Yin has accumulated 81 citations across 8 indexed publications and holds an h-index of 4. These indicators reflect measurable scholarly visibility and engagement within the fields of management and organizational studies.[2]

Award Suitability

Jun Yin’s body of work demonstrates sustained engagement with contemporary organizational challenges, including leadership, innovation, learning processes, and AI-driven workplace transformation. His publication record, citation performance, and international academic background support consideration for recognition within research excellence and management scholarship categories.[1][2]

Conclusion

The academic profile of Jun Yin highlights a developing research portfolio focused on organizational behavior, management theory, and emerging workplace technologies. His contributions continue to expand scholarly understanding of paradox mindset, employee adaptation, and organizational learning within evolving business environments.[1][3]

References

  1. ORCID. (2026). Jun Yin (0000-0003-4799-4025) researcher profile. 

    https://orcid.org/0000-0003-4799-4025

  2. Elsevier. (2026). Scopus author details: Jun Yin, Author ID 57222541034. 

    https://www.scopus.com/authid/detail.uri?authorId=57222541034

  3. Yin, J., & Wang, Y. (2026). The Paradoxical Effects of Generative Artificial Intelligence Induced Stressors on Employee Adaptive Performance.https://doi.org/10.1111/1744-7941.70074
  4. Yin, J., & Hoang, K. D. (2025). AI-enabled knowledge renewal: the role of leaders’ AI attitudes and unlearning in enhancing employees’ creative.https://doi.org/10.1108/JKM-02-2025-0209
  5. Yin, J. (2023). Effects of the paradox mindset on work engagement: The mediating role of seeking challenges and individual .

    https://doi.org/10.1007/s12144-021-01597-8