Dr. Melinda Hollingshed is a Professor of Industrial and Systems Engineering and Industrial Management whose work focuses on Engineering Management, Project Management, Quality Engineering, Quality Management, Supply Chain Management, Operations Management, Process Improvement, Lean Manufacturing, Six Sigma Methods, and Systems Engineering. Her academic career includes extensive teaching across graduate and undergraduate engineering, operations, business, and project management courses, while also mentoring students through applied research, industry collaboration, and real-world process improvement initiatives.
Prior to academia, she spent more than a decade leading large-scale Lean and Six Sigma deployments within multinational manufacturing and distribution operations, developing cost-driven process optimization strategies, deploying continuous improvement systems, and driving operational performance enhancements at plant, regional, and national levels.
Her current research interests examine the integration of artificial intelligence in management with a focus on how AI can accelerate lean decision making, optimize operational planning, enhance supply chain resilience, reduce process variation, and enable predictive quality engineering strategies. She is particularly interested in the intersection of AI-supported human judgement, leadership adaptation to intelligent systems, and how AI can be used to transform organizational learning, waste reduction, and continuous improvement cultures in Industry 4.0 and 5.0 environments.
Dr. Hollingshed is an advocate for inclusive excellence in engineering pathways and has served in roles advancing student success, belonging, and early engagement in engineering programs.
Outside of professional work, she enjoys creating STEM learning experiences that reach underserved communities, designing Lean training resources, and traveling with her family.
Prior to academia, she spent more than a decade leading large-scale Lean and Six Sigma deployments within multinational manufacturing and distribution operations, developing cost-driven process optimization strategies, deploying continuous improvement systems, and driving operational performance enhancements at plant, regional, and national levels.
Her current research interests examine the integration of artificial intelligence in management with a focus on how AI can accelerate lean decision making, optimize operational planning, enhance supply chain resilience, reduce process variation, and enable predictive quality engineering strategies. She is particularly interested in the intersection of AI-supported human judgement, leadership adaptation to intelligent systems, and how AI can be used to transform organizational learning, waste reduction, and continuous improvement cultures in Industry 4.0 and 5.0 environments.
Dr. Hollingshed is an advocate for inclusive excellence in engineering pathways and has served in roles advancing student success, belonging, and early engagement in engineering programs.
Outside of professional work, she enjoys creating STEM learning experiences that reach underserved communities, designing Lean training resources, and traveling with her family.