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Excellence in Ph.D. research recipients 2020

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

Suleyman YildirmName: Suleyman Yildirm

Advisor: Dr. Alper Murat / Dr. Murat Yildirim

Research topic/dissertation title:  Automated Discovery and Calibration of Discrete Event Simulation Models Using Machine Learning

Description of research/abstract: Unifying focus of his research is the discovery of discrete event simulation in complex systems using machine learning and artificial intelligence techniques. Currently, his research covers multiple areas including integration of process knowledge into change point detection in healthcare systems, automated discovery of process knowledge using deep learning, distributed and decomposed simulation strategies, and assessing sepsis treatment for ICU's through Machine Learning and Simulation. He is a 3rd year PhDStudent  in ISE, WSU. He obtained MS degree in Industrial and Systems Engineering at Georgia Institute of Technology, and MEng degree in Healthcare Systems Engineering in ISE at Lehigh University.

Description of achievements:

  • S Yildirim, AE Murat, M Yildirim, S Arslanturk. (2020). Process Knowledge Driven Change Point Detection for Automated Calibration of Discrete Event Simulation Models Using Machine Learning. IEEE Transactions on Systems, Man, and Cybernetics: Systems, submitted paper.

  • S Yildirim, AE Murat, M Yildirim. "Efficient Decomposition and Smart Sampling Methods using ML for Distributed Simulation Models", manuscript under preparation for submission to Journal of Simulation.

  • S Yildirim, AE Murat, M Yildirim. "Assessing Sepsis Treatment Procedure in Intensive Care Unit through Machine Learning and Simulation", Working Paper – Current Research.

  • S Yildirim, AE Murat, M Yildirim. Integrating Process Knowledge into Change Point Detection in Healthcare Systems. Conference Presentation, INFORMS 2019.

  • Best paper award - S Yildirim, AE Murat, M Yildirim. (2019). Change Point Detection Using Process Knowledge for Automated Parameter Estimation in Simulation Models. Annual Conference of Michigan Simulation User Group.

  • Best poster presentation award - S Yildirim, AE Murat. (2018). Automated Discovery of Process Knowledge Using Deep Learning and Optimization. ISE GRS 2018.

  • S Yildirim. (2016).  Simulating Patient-Centered Medical Home - Case of Mercy Care Atlanta, Mercy Clinics. Research Project. Georgia Institute of Technology.

  • S Yildirim, FM Zenginsoy.(2015). Bundling total knee arthroplasty; understanding cost from clinic through rehab by observing and documenting work activities and process inputs. Capstone Project and Poster Presentation. Lehigh University.

  • Graduate Scholarship Award for Study Abroad for Master and PhD Program, Turkish Ministry of National Education. 2012.

Runner Up:

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

Advisor: Dr. Leslie Monplaisir

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:

  • "Performance Evaluation of Hospital EDs during a Medical Surge". Blue Cross Blue Shield of Michigan Foundation Research Grant, April 2020 (Award Amt: $10,000)
  • Thomas C. Rumble Ph.D. Fellowship Award, April 2020 – WSU
  • 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 (2020). "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
  • C. Aguwa, O. Turgut, L. Monplaisir, W. Jordan & E. E. Etu (2019). "Design for Reusability of Medical Equipment for Optimal Modularization Using an Endoscope as Case Study". Cogent Engineering. DOI: 10.1080/23311916.2019.1636516.
  • E. E. Etu, C. Aguwa, L. Monplaisir, S. Arslanturk, & J. Miller (2019). "A Benchmarking Analysis to Improve Healthcare Service Delivery using DEA". 2019 Annual Institute of Industrial and Systems Engineering Conference Proceedings
  • E. E. Etu (2019). "Integration of Machine Learning into Benchmarking Process to Improve Healthcare Service Delivery: A Case Study of a Hospital ED." 2019 Annual Institute of Industrial and Systems Engineering Conference – Invited Speaker: Doctoral Colloquium
  • E. E. Etu, L. Monplaisir, C. Aguwa, S. Arslanturk, S. Masoud, I. Markevych, & J. Miller (2020). "Identifying Indicators Influencing Emergency Department Performance during a Medical Surge via Modified Fuzzy Delphi Method." Applied Soft Computing, Submitted and under review. IF: 5.472
  • E. E. Etu, L. Monplaisir, C. Aguwa, S. Arslanturk, S. Masoud, I. Markevych, & J. Miller (2020). "Identification of Critical Metrics Influencing ED Performance during a Medical Surge: A Modified Fuzzy Delphi Approach", 2020 American College of Emergency Physician Conference, Submitted and under review 
  • E. E. Etu, L. Monplaisir, C. Aguwa, S. Arslanturk, S. Masoud, I. Markevych, & J. Miller (2020). "A Comparison of TFD & MFD Approaches for ED Metrics Identification during a Medical Surge", 5thNorth American Conference on Industrial Engineering & Operations Management, Submitted and under review.

Runner Up:

Farnaz FallahiName: Farnaz Fallahi

Advisor: Dr. Murat Yildirim

Research topic/dissertation title: "Integrating Degradation Sensor Data to Operations and Pricing Problems in Power Systems"

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.

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, under review (2020).
  • Integrating Degradation Sensor Data to Electricity Markets, Presentation at INFORMS 2019.
  • Integrating Degradation Sensor Data to Electricity Markets, Poster at ISE Graduate Research Symposium, WSU, 2019.
  • "Condition-Based Maintenance Scheduling of Multi-Component Systems Considering Stochastic Degradation" (Mentoring a master student in her thesis project)
  • "Integrated Task Allocation and Charging Scheduling of Autonomous Mobile Robots Considering Battery Degradation", in collaboration with Dr. Marco Brocanelli, Computer Science Department, WSU.

Runner Up:

Zhenyu (Johnny) ZhouName: Zhenyu (Johnny) Zhou

Advisor:  Dr. Yanchao Liu

Research topic/dissertation title: Optimization models and algorithms for unmanned air traffic management – routing method and software implementation

Description of research/abstract: My research is to develop models and algorithms for building an automated UAV fleet routing system. Compared to using ground-based vehicles, UAVs are more energy-efficient and flexible for last-mile delivery tasks. UAV traffic management problems can be formulated as mixed-integer programming (MIP) or mixed-integer non-linear programming (MINLP) models. My work aims to apply decomposition methods and computational enhancements to make these models solvable in a practical scale. Now my method can speed up solutions for an optimal landing model by 500x with little loss of optimality and has been well tested in our UAV fleet routing system.

Description of achievements:

Publications

  • Zhenyu Zhou, Jun Chen and Yanchao Liu (2020). Optimal Fleet Landing: How to quickly land many drones in congested air traffic. IEEE Transactions on Intelligent Transportation Systems, under review.
  • Zhenyu Zhou (2019). Optimal Landing Algorithms for UAV Fleets. Presentation at INFORMS 2019
  • Zhenyu Zhou (2019). Develop the next-generation air traffic management system to enable safe and scalable drone operations. Poster at ISE GRS 2019

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