IOE students recognized by the Society for Risk Analysis
Two U-M IOE graduate students were recently recognized by the Society for Risk Analysis (SRA) with student merit awards.
Two U-M IOE graduate students were recently recognized by the Society for Risk Analysis (SRA) with student merit awards.
Two U-M Industrial and Operations Engineering PhD students, Julia Coxen and Elnaz Kabir, recently received student merit awards from specialty groups within the Society for Risk Analysis (SRA).
Coxen received the Applied Risk Management Specialty Group Student Merit Award. The student merit award is chosen from amongst the students presenting at the SRA Annual Meeting in the Applied Risk Management domain.
In her risk analysis research, Coxen worked with U-M IOE Professor Seth Guikema and U-M Law Professor Bridgette Carr to explore risk management in the human trafficking domain.
“We have been driven to address the pressing need for research in the human trafficking domain and I am thrilled SRA recognizes the importance as well,” Coxen said. “Big thanks to Professor Guikema from IOE and Professor Carr from the Law School for their expertise and guidance.”
Elnaz Kabir received the Foundational Issues in Risk Analysis Specialty Group Student Merit Award. The award recognizes excellence in the area of foundational issues of risk analysis. Kabir’s winning paper focused on assessing the ISA Tree Risk Assessment Approach using econometrics analysis.
In her risk analysis research, Kabir worked with Guikema and University of Florida Professor Andrew Koeser to evaluate the accuracy of ISA risk factors in tree risk assessment and study the associations between tree characteristics and its failing risk using econometrics analysis.
“I am extremely honored to receive this student merit award and sincerely grateful for this recognition and the work of the award committee,” Kabir said. “Also, thank you to Professor Guikema and Professor Koeser for their guidance in this research.”
Julia Coxen is a current U-M IOE PhD student as well as an active duty Lieutenant Colonel and recently finished battalion command in Virginia with the US Army Special Operations. Her research interests include critical infrastructure planning, machine learning, network analysis and optimization.
Elnaz Kabir is a U-M IOE PhD candidate. Her research is interdisciplinary and grounded in predictive analytics, data-driven decision making, and risk analysis. Her focus is to use statistical learning theories, and optimization techniques to better understand and solve important problems related to power outages caused by weather events. Since fallen trees and branches caused by extreme storms are one of the main reasons for power outages, one of Kabir’s research interests is to study the potential predictability of tree failure before storms.
U-M IOE undergraduate student, Nolan Feeny, together with PhD student, Anna White, were also recognized by SRA through a Best Poster award for research conducted with Guikema.