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Sara Masoud

Sara Masoud

Assistant Professor, Industrial and Systems Engineering

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Sara Masoud

Biography

Dr. Sara Masoud is an assistant professor of industrial and systems engineering at Wayne State University. She received her doctorate in systems and industrial engineering and master’s in statistics from the University of Arizona in 2019. She received her bachelor’s degree in industrial and systems engineering from Sharif University of Technology, Iran, in 2014. Her research focuses on mixed reality, virtual reality, augmented reality and dynamic, data-driven application systems by utilizing applied machine learning, simulation and optimization models in agro-industry, transportation, health care and manufacturing. She is a member of the Institute of Industrial and Systems Engineers (IISE) and Institute of Operation Research and Management Sciences. In 2019, she received the IISE Annual Meeting Best Paper Award in the Data Analytics and Information Systems track.

Publications

  • Kamali Mohammadzadeh, A., Allen, C. L., & Masoud, S. (2023, June). VR Driven Unsupervised Classification for Context Aware Human Robot Collaboration. In International Conference on Flexible Automation and Intelligent Manufacturing (pp. 3-11). Cham: Springer Nature Switzerland.
  • Eghbali-Zarch M., Zabihi S.Z., and Masoud, S., (2023) A novel fuzzy SECA model based on fuzzy standard deviation and correlation coefficients for resilient-sustainable supplier selection, Expert Systems with Aplications, 120653.
  • Zhang, R., Masoud, S., and Masoud, N. (2023). Impact of Autonomous Vehicles on the Car-Following Behavior of Human Drivers., Journal of Transportation Engineering, Part A: Systems, 149(3).
  • Masoud, S., Zhu, M., Djuric, A., and Rickli, J., (2022) Robotics Laboratory during COVID-19 — Challenges and Future Directions, International Journal of Modern Engineering, 14 Download
  • Jahanmahin, R., Masoud, S., Rickli, J., & Djuric, A. (2022). Human-robot interactions in manufacturing: A survey of human behavior modeling. Robotics and Computer-Integrated Manufacturing, 78, 102404.
  • Emakhu, J., Monplaisir, L., Aguwa, C., Arslanturk, S., Masoud, S., Nassereddine, H., ... & Miller, J. B. (2022). Acute coronary syndrome prediction in emergency care: A machine learning approach. Computer Methods and Programs in Biomedicine, 107080.
  • Eghbali-Zarch, M., Tavakkoli-Moghaddam, R., Esfahanian, F., & Masoud, S. (2022). Prioritizing the glucose-lowering medicines for type 2 diabetes by an extended fuzzy decision-making approach with target-based attributes. Medical & Biological Engineering & Computing, 60(8), 2423-2444.
  • Etu, E. E., Monplaisir, L., Masoud, S., Arslanturk, S., Emakhu, J., Tenebe, I., ... & Krupp, S. (2022, June). A Comparison of Univariate and Multivariate Forecasting Models Predicting Emergency Department Patient Arrivals during the COVID-19 Pandemic. In Healthcare (Vol. 10, No. 6, p. 1120). MDPI.
  • Etu, E. E., Monplaisir, L., Arslanturk, S., Masoud, S., Aguwa, C., Markevych, I., & Miller, J. (2022). Prediction of Length of Stay in the Emergency Department for COVID-19 Patients: A Machine Learning Approach. IEEE Access, 10, 42243-42251.
  • Etu, E. E., Monplaisir, L., Aguwa, C., Arslanturk, S., Masoud, S., Markevych, I., & Miller, J. (2022). Identifying indicators influencing emergency department performance during a medical surge: A consensus-based modified fuzzy Delphi approach. PloS one, 17(4), e0265101.
  • Chowdhury, B. D. B., Masoud, S., Son, Y. J., Kubota, C., & Tronstad, R. (2021). A Dynamic HMM-based Real-time Location Tracking System Utilizing UHF Passive RFID. IEEE Journal of Radio Frequency Identification.
  • Masoud, S., Mariscal, N., Huang, Y., & Zhu, M. (2021). A Sensor-based Data Driven Framework to Investigate PM2.5 in the Greater Detroit Area. IEEE Sensors Journal. 
  • Masoud, S., Kim, S., Son, Y.J. (2020). Mitigating the Risk of Hazardous Materials Transportation: A Hierarchical Approach, Computers & Industrial Engineering, 148, 106735.
  • Chowdhury, B. D. B., Masoud, S., Son, Y. J., Kubota, C., & Tronstad, R. (2020). A dynamic data driven indoor localisation framework based on ultra high frequency passive RFID system, International Journal of Sensor Networks, 34 (3), 172-187.
  • Masoud, S., Chowdhury, B. D. B., Son, Y. J., Kubota, C., & Tronstad, R. (2019). Simulation based optimization of resource allocation and facility layout for vegetable grafting operations. Computers and Electronics in Agriculture, 163, 104845.
  • Masoud, S., Son, Y. J., Kubota, C., & Tronstad, R. (2018). “Evaluation of Simulation based Optimization in Grafting Labor Allocation.” Applied Engineering in Agriculture, 34(3): 479-489.
  • Kubota, C., Meng, C., Masoud, S., Son, Y. J., & Tronstad, R. (2018). “Advanced Technologies for Large Scale Plant Factories – Integration of Industrial and Systems Engineering Approach in Controlled Environment Crop Production.” Artificial Light-type Plant Factory, (pp. 354-362), Ed. Masakazu Anpo, Hirokazu FukudaTeruo Wada: Elsevier

Papers and Conferences

  • Etu, E., Monplaisir, L., Aguwa C., Arslanturk S., Masoud, S., Markevych, I., Miller J., (2020, August ), A Comparison of TFD & MFD in Identification of Metrics for ED Performance Associated with Medical Surges, Proceedings of the 5th International Conference on Industrial Engineering and Operations Management, Submitted.
  • Masoud, S., Meng, C., Chowdhury, B., Son, Y. J., & Tronstad, R. (2020). “GRANDES: An Online Decision Support Tool for Grafting Nurseries.” In proceedings of II International Symposium on Vegetable Grafting, Accepted.
  • Masoud, S., Kim, S., & Son, Y. J. (2015, January). “Integrated Dual Toll Pricing with Network Design for Hazardous Materials Transportation.” In IIE Annual Conference. Proceedings (p. 2556). Institute of Industrial and Systems Engineers (IISE).
  • Masoud, S., Masoud, N., & Son, Y. J. (2016, January). “Impact of Traffic Conditions and Carpool Lane Availability on Peer-to-Peer Ridesharing Demand.” In IIE Annual Conference. Proceedings (p. 2067). Institute of Industrial and Systems Engineers (IISE).
  • Masoud, S., Chodhury, B., Son, Y. J., Kubota, C., & Tronstad, R. (2018, January). “A Dynamic Modeling Framework for Human Hand Gesture Task Recognition.” In IIE Annual Conference. Proceedings (p. 563). Institute of Industrial and Systems Engineers (IISE).

Awards and Honors

  • Best Track Paper Award in the Healthcare Category, 5th North American Industrial Engineering & Operations Management Conference in Detroit, MI, 2020
  • IISE Best Paper Award 1st Place, Data Analytics and Information Systems Track, Orlando, FL, 2019
  • Achievement Award, Outstanding Research Assistant, 1st Place, University of Arizona, 2019
  • IISE Best Paper Award Finalist, Data Analytics and Information Systems Track, Orlando, FL, 2018

Patents

  • Masoud, S., Son, Y. J., Tronstad, R. E., & Kubota, C. (2023)."Systems and methods for simulation-based resource and layout optimization,  US Application number 17939924 
  • Masoud, S., Son, Y. J., Tronstad, R. E., & Kubota, C. (2019). "Systems and methods for simulation-based resource and layout optimization." U.S. Patent Application No. 16/418,883.

 

Education

  • Ph.D. Systems and Industrial Engineering, University of Arizona, 2019.
  • M.S. Statistics, University of Arizona, 2019.
  • B.Sc. Industrial Engineering, Sharif University of Technology, Iran, 2014.

Research Interests

  • Data Analytics
  • Virtual Reality/ Augmented Reality/ Mixed Reality
  • Dynamic data driven systems
  • Machine Learning
  • Simulation (Agent-based, Discrete Event, System Dynamics)
  • Operations Research
  • Large Scale Optimization
  • Smart Manufacturing
  • Ride-sharing Systems
  • Autonomous/ Connected Vehicles
  • Logistics  

Laboratory Web Site

Link :  http://smartimmersivemodeling.com/

Courses taught by Sara Masoud

Winter Term 2025 (future)

Fall Term 2024

Winter Term 2024

Spring-Summer Term 2023

Winter Term 2023

Fall Term 2022

Winter Term 2022

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