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Yu Sun

Associate Dean and Director of Data Analytics in the College of Technology at Western Governors University

Dr. Yu Sun serves as the Associate Dean and Director of Data Analytics in the College of Technology at Western Governors University (WGU). As an academic leader, scholar, and educator, Dr. Sun brings extensive experience across data analytics, leadership studies, online learning innovation, and workforce development. She holds dual doctorates in Management Science Engineering and Applied Mathematics, as well as an M.S. in Applied Statistics, grounding her leadership in deep quantitative expertise and analytical rigor.

Prior to joining WGU, Dr. Sun was a Leadership Studies professor and Graduate Program Director, where she led academic programs, supported faculty development, and strengthened student success through evidence-based instructional and advising practices. Her leadership work spans accreditation, strategic planning, curriculum design, and building industry-engaged learning pathways.

Dr. Sun is an active scholar with more than 50 peer-reviewed publications, including journal articles, book chapters, and conference presentations in the fields of leadership, education, analytics, and organizational development. She has contributed to edited scholarly volumes, served as a reviewer for academic journals, and sits on editorial boards supporting research in leadership and education. Her academic work focuses on themes of leadership development, psychological safety, cross-cultural leadership, and technology-enabled learning.

Dr. Sun has provided leadership development, team coaching, and organizational training to school districts, nonprofits, and workforce organizations across Texas. She also contributes to Houston’s community ecosystem through the LeadForward Collaborative, a nonprofit dedicated to youth leadership, civic engagement, and workforce readiness.

At WGU, Dr. Sun oversees the direction, rigor, and growth of the Data Analytics programs, ensuring alignment with emerging technologies, employer needs, and the principles of competency-based education. She is passionate about expanding access to tech careers and empowering diverse learners to develop data-driven, future-ready skills.

Areas of Expertise:

  • Data Analytics & Applied Statistics
  • Management Science & Decision Modeling
  • Leadership Development & Executive Coaching
  • Online, Competency-Based Education
  • Curriculum, Assessment & Accreditation
  • Workforce-Aligned Program Innovation
  • Cross-Cultural & Inclusive Leadership
  • Organizational Strategy & Academic Operations

Education:

  • Ph.D., Applied Mathematics, Wayne State University
  • Ph.D., Management Science Engineering, Donghua University 
  • M.S., Applied Statistics, Wayne State University 
  • B.A., Math Education, Qingdao University

Professional & Scholarly Interests:

  • Data-informed leadership and institutional decision-making
  • Inclusive leadership, psychological safety, and team culture
  • Applied analytics for workforce and organizational effectiveness
  • AI/ML applications in learning design and student success
  • Graduate and doctoral education innovation
  • Strengthening pathways between higher education and industry

Areas of Expertise:

  • Data Analytics & Applied Statistics
  • Management Science & Decision Modeling
  • Leadership Development & Executive Coaching
  • Online, Competency-Based Education
  • Curriculum, Assessment & Accreditation
  • Workforce-Aligned Program Innovation
  • Cross-Cultural & Inclusive Leadership
  • Organizational Strategy & Academic Operations

Education:

  • Ph.D., Applied Mathematics, Wayne State University
  • Ph.D., Management Science Engineering, Donghua University 
  • M.S., Applied Statistics, Wayne State University 
  • B.A., Math Education, Qingdao University

Professional & Scholarly Interests:

  • Data-informed leadership and institutional decision-making
  • Inclusive leadership, psychological safety, and team culture
  • Applied analytics for workforce and organizational effectiveness
  • AI/ML applications in learning design and student success
  • Graduate and doctoral education innovation
  • Strengthening pathways between higher education and industry

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