Feng Ju and his team at ASU's Manufacturing and Service Automation Lab are developing data tools to advance factory operations and minimize production disruptions. Photographer: Connor McKee/ASU

Manufacturing and Service Automation Lab

Feng Ju, PhD

Associate Professor and Program Chair of Industrial Engineering
School of Computing and Augmented Intelligence

Senior Global Futures Scientist
Julie Ann Wrigley Global Futures Laboratory

Office: BYENG 318
Email: fengju AT asu DOT edu                       


Research Interests

  • Stochastic modeling and optimization of production systems, semiconductor manufacturing, and healthcare delivery systems
  • Real-time monitoring and control of additive manufacturing
  • Logistics and Supply Chain

Education Background

  • PhD, Industrial and Systems Engineering, University of Wisconsin Madison
  • MS, Electrical and Computer Engineering, University of Wisconsin Madison
  • Visiting Scholar, Robotics Institute, Carnegie Mellon University
  • BS, Electrical and Computer Engineering, Shanghai Jiaotong University

Selected Honors and Awards

  • Best Student Paper Finalist Award, IEEE Conference on Automation Science and Engineering (CASE), 2023
  • Best Paper Award, IISE Transactions, 2021
  • Best Healthcare Paper Award Finalist, IEEE Conference on Automation Science and Engineering (CASE), 2021
  • Dr. Hamed K. Eldin Outstanding Early Career IE in Academia Award, 2021
  • Outstanding Faculty Advisor Award, IISE Western Region, 2020
  • SME Outstanding Young Manufacturing Engineer Award, 2020
  • Best Student Paper Award, IEEE Conference on Automation Science and Engineering (CASE), 2019
  • Faculty Residency Award, Mayo-ASU Alliance for Health Care, 2019
  • Runner-up Award, NIST RAMP competition, 2018
  • Best Student Paper Award Finalist, IEEE Conference on Automation Science and Engineering (CASE), 2017
  • Best Student Paper Award Finalist, IFAC Symposium on Information Control Problems in Manufacturing (INCOM), 2015
  • Most Popular Article, IEEE Transactions on Automation Science and Engineering (TASE), 2013
  • Best Paper Award, IFAC Conference on Manufacturing Modeling, Management and Control (MIM), 2013

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