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David Nembhard

Adjunct Professor

Introduction

Dr. Nembhard’s research, at the intersection of human factors, future work at the human-technology frontier, human-in-the-loop systems and simulations, and productivity and performance of systems considering individual human differences in behavior. Correspondingly, research contributions are in multiple fields including human factors, system optimization, risk assessment, human performance, and data analytics.

Current Positions

  • Professor, Industrial Engineering
  • Adjunct Professor, Business Analytics

Education

  • PhD in Industrial and Operations Engineering, University of Michigan
  • MS in Industrial and Operations Engineering, University of Michigan
  • MS in Systems Engineering, Case Western Reserve University
  • BSE in Systems Engineering, Case Western Reserve University

Professional Memberships

  • Institute for Operations Research and the Management Sciences (INFORMS), 1994

Selected Publications

  • Sun, Y. & Nembhard, D. (2022). Information Representation and the Mediating role of emotions on e-learning outcomes. International Journal of Human-Computer Interaction. pp. 1-12. DOI: https://doi.org/10.1080/10447318.2022.2096187.
  • Nembhard, D. & Sun, Y. (2019). A symbolic genetic programming approach for identifying models of learning-by-doing. Computers & Industrial Engineering. 131 pp. 524-533.
  • Kim, J. & Nembhard, D. (2019). Eye movement as a mediator of the relationships among time pressure, feedback, and learning performance. International Journal of Industrial Ergonomics. 70 pp. 116-123.
  • Macht, G. A., Nembhard, D., & Leicht, R. M. (2019). Operationalizing emotional intelligence for team performance. International Journal of Industrial Ergonomics. 71 pp. 57-63.
  • Mendez-Vazquez, Y. M. & Nembhard, D. (2019). Worker-cell assignment: The impact of organizational factors on performance in cellular manufacturing systems. Computers & Industrial Engineering. 127 pp. 1101-1114.
  • Kim, J. & Nembhard, D. (2019). The impact of procrastination on engineering students' academic performance. International Journal of Engineering Education. 35 (4) pp. 1008.
  • Kim, J. & Nembhard, D. (2018). Parametric empirical Bayes estimation of individual time-pressure reactivity. International Journal of Production Research. 56 (7) pp. 2452-2463.
  • Kim, J. & Nembhard, D. Modeling the Effects of Time pressure and Feedback on Eye movements and Learning Performance. In Proceedings of Human Factors and Ergonomics Society Annual Meeting 2018. 62 (1) pp. 671-675.
  • Nembhard, D. A. & Xiao, M. (2017). The Relation of Knowledge Intensity to Productivity Assessment Preferences and Cultural Differences In Organizational Culture and Behavior: Concepts, Methodologies, Tools, and Applications. pp. 1565-1583. IGI Global.
  • Olivella, J. & Nembhard, D. A. (2017). Cross-training policies for team cost and robustness. Computers & Industrial Engineering. 111 pp. 79-88.

Selected Presentations

  • "Teaching Efficiency and Effectiveness," Panelist at INFORMS Minority Issues Forum, Los Angeles, California, October 2021.

Selected Grants & Contracts

  • Nembhard, D. (Principal Investigator). FW-HTF-RM: Collaborative Research: Assistive Intelligence for Cooperative Robot and Inspector Survey of Infrastructure Systems (AI-CRISIS). National Science Foundation (NSF). Funded. May 2021 - August 2023.