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Excellence in Ph.D. research recipients 2021

Every June, Ph.D. students in the Department of Industrial and Systems Engineering make 15-minute presentations to the faculty and their peers on their achievements and progress within the program (e.g., journal/conference publications, awards, teaching evaluations, coursework/grades, preliminary exams, qualifiers, etc.), with more emphasis on the current academic year. This is also an opportunity for students to learn more about the research and scholarly activities of their fellow doctoral candidates. Based on faculty feedback, a winner and runner-up are selected.

First place

Farnaz FallahiName: Farnaz Fallahi

Advisor: Dr. Murat Yildirim

Research topic/dissertation title:  Integrating Degradation Sensor Data to Operations and Pricing Problems in Electricity Market

Description of research/abstract: Industrial sensor data provides significant insights into the failure risks of generation assets. In traditional applications, these sensor-driven asset failure risks are used to generate alerts that initiate maintenance actions without considering their impact on operations and markets. My research focus is to develop frameworks and models that i) build a seamless integration between sensor data, operations, maintenance scheduling, and market behavior in power systems; and ii) enhance the value of sensor integration for improving various key performance metrics in power systems like reliability and resilience. The integration requires fundamental research on how the problem is formulated, the associated uncertainties modeled, and how the condition monitoring information is incorporated into the optimization module.

Description of achievements:

Publications

  • Fallahi F., Yildirim M., Lin J., Wang, C. "Predictive Multi-Microgrid Generation Maintenance: Formulation and Impact on Operations & Resilience", IEEE Transactions on Power Systems, 2021
  • Fallahi F., Yildirim M., Bakir I. "Chance-constrained Sensor-Driven Maintenance & Operations in Wind Farms", Working paper – Current research
  • Fallahi F., Yildirim M. "Prognostic-centered Maintenance Coordination in Deregulated Power Systems under Stochastic Operations, Degradations, and Unexpected Failures", Working paper – Current research
  • Faddah A., Fallahi F., Yildirim M. "A Condition-based  Stochastic Maintenance & Operations Scheduling Framework for Manufacturing Systems under Continuous Degradation Interactions" , Working paper – Current research
  • Altinpulluk D., Fallahi F., Feizollahi MJ., Yildirim M.  "Robust Maintenance and Operations Scheduling of Multi-Component Systems under Stochastic Degradation & Economic Dependency", Working paper – Current research
  • Feng Y., Papadopoulos P., Fallahi F., Yildirim M., Ezzat AA. "Stochastic Day-ahead Operations Scheduling of Microgrids in the Presence of Prediction Errors and Demand Response", Working paper – Current research

Side projects

  • "Condition-based Maintenance scheduling of multi-component systems considering stochastic degradation" Mentoring a master student in her thesis project, Industrial & Systems Engineering Department, Wayne State University
  • "Presumed Open Data: Data Science Challenge", In collaboration with Dr. Ahmed Aziz Ezzat and his two PhD students, Industrial & Systems Engineering Department, Rutgers University

Runner up:

Egbe-Etu E. EtuName: Egbe-Etu E. Etu

Advisor: Dr. Leslie Monplaisir / Dr. Celestine Aguwa

Dissertation title: Medical Surge Capability: Performance Modeling of Hospital Emergency Departments (EDs)

Description of research: Hospitals are faced with significant challenges during and after natural or human-caused disasters. Surge planning is a critical component of every healthcare facility's emergency plan and response system. The process of managing and allocating scarce resources, by tackling the vulnerability inherent to patients', means that defining improvement priorities is one of the main challenges faced by hospitals when responding to a medical surge event. The purpose of this research is to model and evaluate the operating performance of EDs during a medical surge scenario. We propose a framework to improve ED performance and resource utilization under medical surge by implementing a data-driven simulation and optimization modeling approach. The expected outcomes of the study are the multi-objective combination of metrics to optimize ED performance and studying the interactions between the different ED operations to improve service capacity.

Description of achievements:

Funding awards

  • Etu, E.E. "Medical Surge Capability: Performance Modeling of Hospital Emergency Departments." Competitive Rumble Ph.D. Fellowship. (Award Amt: $50,000), 2020. 
  • Miller, J., Aguwa, C., Monplaisir, L., Etu, E.E. "Performance Evaluation of Hospital Emergency Departments during a Medical Surge." Blue Cross Blue Shield of Michigan Foundation & Henry Ford Hospital. (Award Amt: $10,000), 2020.
  • Etu, E.E. "Integration of Machine Learning into Benchmarking Process to Improve Healthcare Service Delivery: A Case Study of an Hospital Emergency Department." National Science Foundation Student Travel Grant, (Award Amt: $800), 2019

Journal/conference/symposium papers

  • Etu, E.E. Monplaisir, L. Arslanturk, S., Masoud, S., Aguwa, C., and Miller, J., (2021). ICU Admissions for COVID-19 Patients: A Machine Learning Driven Approach. Wayne State Graduate & Postdoctoral Research Symposium. Second Place Award
  • Etu, E.E. Monplaisir, L., Miller, J., et al., (2021). Forecasting Daily Patient Arrivals during COVID-19 in Emergency Departments: A Deep Learning Approach. Under review on 2021 ACEP Conference.
  • Etu, E.E., Monplaisir, L., Aguwa, C., Arslanturk, S., Miller, J., Masoud, S., and Markevych, I., (2021). Prediction of Length of Stay in the Emergency Department for COVID-19 Patients: A Machine Learning Approach. Second-stage review on PLOS ONE Journal
  • Etu, E.E., Monplaisir, L., Aguwa, C., Arslanturk, S., Miller, J., Masoud, S., and Markevych, I., (2020). Identifying Indicators Influencing Emergency Department Performance during a Medical Surge via Modified Fuzzy Delphi Method. Under review on Euro Journal on Decision Processes
  • Aguwa, C., Etu, E.E., Emakhu, J., Bueno, L., and Monplaisir, L., An Online STEM Summer Education Program: Helping Students Develop Interest in STEM. Proceedings of the 2020 Global Engineering Education Conference, A. Masud, H Parsaei, Eds. 2020.
  • Etu, E.E., Monplaisir, L., Aguwa, C., Arslanturk, S., Miller, J., Masoud, S., and Markevych, I., (2020). A Comparison of TFD & MFD in Identification of Metrics for ED Performance Associated with Medical Surges. Proceedings of the 5th North American Conference on Industrial Engineering and Operations Management, M.S. Ahmed, A. Ali, L. Monplaisir, W. Otieno, Eds. 2020. Best Paper Track Award – Healthcare Category
  • E. E. Etu (2020). "A Hybrid BP-DEA Approach to Assess the Efficiency of the Emergency Department in Normal Operating Conditions" – First Place Award, Doctoral Poster Presentation at the 10th Annual WSU Graduate & Postdoctoral Research Symposium, March 2020
  • E. E. Etu (2020). "A Hybrid BP-DEA Approach to Assess the Efficiency of EDs in Normal Operating Conditions" – Second Place Award, Doctoral Presentation at the 2019 ISE Research Symposium Poster Session, WSU, December 2019
  • E. E. Etu (2019). "The Impact of Machine Learning Algorithms on Benchmarking Process in Healthcare Service Delivery" – First Place Award, Graduate Research Poster Presentation at the 4th North American Conference on Industrial Engineering & Operations Management, Toronto, Canada, October 2019
  • Aguwa, C., Turgut, O., Monplaisir, L., Jordan, W. and Etu, E.E. (2019). Design for Reusability of Medical Equipment for Optimal Modularization Using an Endoscope as Case Study. Cogent Engineering, 6(1). DOI: 10.1080/23311916.2019.1636516. 
  • Tenebe, I.T., Emenike, C.P., Etu, E.E., et al. (2019). Assessment of Daily Intake of Arsenic and Associated Health Risks for Children. River Basin Management X, 234(193). DOI: 10.2495/RBM190191 

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