BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Operations Research Graduate Program - ECPv6.16.3//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Operations Research Graduate Program X-ORIGINAL-URL:https://or.ncsu.edu X-WR-CALDESC:Events for Operations Research Graduate Program REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20210314T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20211107T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20220313T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20221106T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20230312T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20231105T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20240310T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20241103T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20230911T163000 DTEND;TZID=America/New_York:20230911T174500 DTSTAMP:20260626T171833 CREATED:20260129T195910Z LAST-MODIFIED:20260129T195910Z UID:10000084-1694449800-1694454300@or.ncsu.edu SUMMARY:OR Seminar: April Yu DESCRIPTION:Join us in welcoming April Yu\, an Assistant Professor in the ISE department here at NC State\, as she shares her research. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/92584004020?pwd=S3ovcmJQU2h5MElEYTdleW1oVVp5dz09 \nMeeting ID: 925 8400 4020\nPasscode: 503038 \nTitle\nUsing Modeling and Optimization to Improve Healthcare Systems \nAbstract\nDecision-making in healthcare systems plays a crucial role in many contexts\, from disease prevention\, control\, and treatment to hospital operations. Vaccines can prevent life-threatening diseases effectively. The increasing number of available vaccines and complex dosage regimens make recommending personalized childhood immunization schedules difficult. We develop a discrete optimization model to solve both de novo (for all children\, starting at birth) and catch-up (for children who are behind on one or more vaccinations) scheduling problems\, given the child’s age and immunization history. The model is the first in the literature to solve both types of scheduling problems and provide vaccine selection decisions to achieve a balanced combination of higher protection against diseases and fewer clinic visits. \nIn the context of hospital operations\, for example\, where physicians need to balance different responsibilities\, we consider a two-stage service system with two types of servers\, namely subordinates (e.g.\, residents) who perform the first-stage service and supervisors (e.g.\, attending physicians) who have their own responsibilities in addition to collaborating with the subordinates on the second-stage service. Rewards are earned when first- or second-stage service is completed and when supervisors finish one of their own responsibilities. Costs are incurred when impatient customers abandon without completing the second-stage service. We introduce a Markov decision process (MDP) formulation\, prove that one of two policies will maximize the long-run average profit\, and show that the optimality condition is a simple threshold on the system parameters. \nBiography\nApril Yu is an assistant professor at the Department of Industrial & Systems Engineering\, North Carolina State University. She received her Ph.D. and M.S. in Operations Research from the School of Industrial & Systems Engineering\, Georgia Tech. Her research interests focus on stochastic modeling and optimization. Her recent works address a wide range of real-world problems\, from healthcare systems to supply chain management. URL:https://or.ncsu.edu/event/or-seminar-april-yu-09-11-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/or-seminar-series-default-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230821T163000 DTEND;TZID=America/New_York:20230823T180000 DTSTAMP:20260626T171833 CREATED:20260129T201411Z LAST-MODIFIED:20260129T204704Z UID:10000087-1692635400-1692813600@or.ncsu.edu SUMMARY:OR Seminar: Meet and Greet DESCRIPTION:Join Maria Mayorga\, Operations Research Program Director\, and the OR staff and students for a meet-and-greet event. This gathering offers an opportunity to connect with faculty\, students\, and staff as a way to kick off the new semester while enjoying Goodberry’s Frozen Custard. We hope you’ll make the most of this event\, forge new connections\, and leave inspired to explore the boundless possibilities of Operations Research. URL:https://or.ncsu.edu/event/or-seminar-meet-and-greet-08-21-2023/ LOCATION:Angel Plaza\, 915 Partners Way\, 2nd Floor Entrance\, Raleigh\, North Carolina\, 27606 CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/or-seminar-meet-and-greet-08-21-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230505T090000 DTEND;TZID=America/New_York:20230505T110000 DTSTAMP:20260626T171833 CREATED:20260129T204928Z LAST-MODIFIED:20260129T204928Z UID:10000088-1683277200-1683284400@or.ncsu.edu SUMMARY:Spring 2023 Graduation Ceremony DESCRIPTION:The ISE\, OR and MEM Spring 2023 Graduation Ceremony begins at 9 am with a reception right after the service. The ceremony will be live-streamed (http://go.ncsu.edu/isegraduation) starting at 10:45 am for friends and families to enjoy. URL:https://or.ncsu.edu/event/spring-2023-graduation-ceremony/ LOCATION:McKimmon Center\, 1101 Gorman Street\, Raleigh\, 27606\, United States CATEGORIES:OR Program Events ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2025/08/graduation-ceremony-default-feature-image-08-2025-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230424T163000 DTEND;TZID=America/New_York:20230424T174500 DTSTAMP:20260626T171833 CREATED:20260129T205318Z LAST-MODIFIED:20260211T150557Z UID:10000089-1682353800-1682358300@or.ncsu.edu SUMMARY:OR Seminar: Hardi Desai DESCRIPTION:Join us in welcoming Hardi Desai\, a Machine Learning Developer in the AI Center of Excellence at SAS\, as she shares her AI research. \nDid You Miss It?\nWatch it Now\nPasscode: 9*^+XHnC \nTitle\nSolving Real-World Challenges using Artificial Intelligence at SAS \nAbstract\nArtificial intelligence (AI) and edge analytics have been buzzwords for a while now. With an exponential increase in the computation power over the last decade\, the combination of the two\, which essentially allows organizations to run AI workloads at the Edge\, is no longer just a buzzword — it’s happening right now with real\, productive use cases. In this session\, Desai will discuss such challenges in real-world use cases along with the analytical solutions developed by SAS. URL:https://or.ncsu.edu/event/or-seminar-hardi-desai-04-24-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-hardi-desai-04-24-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230417T163000 DTEND;TZID=America/New_York:20230417T174500 DTSTAMP:20260626T171833 CREATED:20260129T205934Z LAST-MODIFIED:20260129T205934Z UID:10000090-1681749000-1681753500@or.ncsu.edu SUMMARY:OR Seminar: John Hopkins Applied Physics Lab DESCRIPTION:Join us in welcoming to the OR Program Çağlar Çağlayan\, Donald Richardson\, Breanna Swan and Jamie Yannayon from the John Hopkins Applied Physics Lab. \nDid you Miss it?\nWatch it Now!\nPassword: q6mD2=P% \nTitle\nOR/ML and Systems Engineering at JHU/APL \nAbstract\nJHU APL is a division of Johns Hopkins University. The Lab is the nation’s largest and oldest university-affiliated research center (UARC)\, with 8\,000 + staff members. As a UARC JHU APL operates in the public’s interest rather than stakeholders and provides independent and objective advice to the government. The Lab serves as a bridge between academia\, industry\, and government by employing expertise in using technology and applied systems engineering to create operational capabilities. The presentation will highlight various projects within the Health and Human Systems group at JHU/APL. The group’s mission is to engineer health and human-machine systems to improve resilience to health threats\, transform complex sociotechnical systems\, and revolutionize operational care delivery. \nBiographies\n\ncaglar.caglayan@jhuapl.edu\nÇağlar Çağlayan joined JHU/APL in 2020. He is an operations research scientist\, focusing on the use and development of optimization\, simulation\, and machine learning approaches for clinical decision-making problems. He received his master’s degree from North Carolina State University and doctoral degree from the Georgia Institute of Technology. Before joining the lab\, he worked at the University of Maryland School of Business as a research associate and at Clemson University Department of Industrial Engineering as an assistant professor. \n\ndonald.richardson@jhuapl.edu\nDonald Ricardson is an Operations Researcher and Supervisor at the Johns Hopkins University Applied Physics Laboratory. His work focuses on applying predictive modeling\, optimization\, and simulation in the healthcare setting. Donald received his Ph.D. and Master’s degrees from the University of Michigan’s Industrial and Operations Engineering Department. \n\nbreanna.swan@jhuapl.edu\nBreanna is an industrial engineer in the Health and Human-Machine Systems group at JHU-APL. She holds a Ph.D. in Industrial and Systems Engineering with a Statistics minor from North Carolina State University\, an M.S. in Mathematics from UW-Milwaukee\, and a B.S. in mathematical physics. Her research interests include integrating techniques like predictive modeling\, decision theory\, simulation\, optimization\, bioinformatics and more to develop frameworks that improve health and wellbeing through data-driven decision support tools. \n\njamie.yannayon@jhuapl.edu\nJamie Yannayon is a health systems engineer and public health analyst supporting analysis efforts for military medicine spanning mission-level medical planning\, medical capability development\, operational medical logistics\, casualty modeling\, medical quality and safety\, and health research portfolio planning. She leads integration of APL’s technical efforts in the field with military medicine sponsors and subject matter experts\, with field experience working at military treatment facilities (MTFs) and military bases in the U.S. and Japan\, as well as at Defense Health Headquarters (DHHQ). Jamie received a B.S. in Industrial and Systems Engineering from NC State University and a Master of Public Health (MPH) from Johns Hopkins Bloomberg School of Public Health. URL:https://or.ncsu.edu/event/or-seminar-john-hopkins-applied-physics-lab-04-17-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-john-hopkins-apl-04-17-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230410T163000 DTEND;TZID=America/New_York:20230410T174500 DTSTAMP:20260626T171833 CREATED:20260129T210308Z LAST-MODIFIED:20260211T150717Z UID:10000091-1681144200-1681148700@or.ncsu.edu SUMMARY:OR Seminar: Ben Rachunok DESCRIPTION:Join us in welcoming the OR Program’s own faculty member\, Ben Rachunok\, as he shares his research linking stainability and resilience. \nDid you miss it?\nWatch it Now\nPassword: u^.fN=v3 \nTitle\nApplying Operations Research Methods to Link Sustainability and Resilience \nAbstract\nResilience is often conceptualized as the ability for socio-ecological systems to bounce back after disturbance. Resilience with sustainability is a relatively new idea conceptualized as bouncing forward to better (more just and sustainable) future states of environmental\, social\, and economic conditions. Operationalizing the idea of sustainability with resilience has thus far been challenging owing to the numerous ways that communities and systems change in the face of natural hazards and climate change. This talk will first provide an overview of the importance of operationalizing sustainability and resilience together and will then present two methods aiming to bridge this gap. The first is a series of data processing steps to extract disaster-related information from social media data\, the second will describe Contrastive Community Networks (CCNs)\, a method for quantifying how sustainable resilience after disruptions based on unsupervised clustering techniques. I will show through a case study how CCNs can be used to identify risk factors within a community that catalyze or inhibit sustainable resilience\, and contrast this with current\, recovery-focused resilience methods. \nbiography\nBen Rachunok is Assistant Professor in the Industrial & Systems Department of North Carolina State University. Prior to joining NC State he was a postdoc in the Civil and Environmental Engineering Department at Stanford University\, and was a fellow of the 2021 cohort of the Rising Environmental Leaders Program at the Stanford Woods Institute for the Environment. Ben was formerly an R&D Intern at the Center for Computing Research at Sandia National Labs. He received his BS in Industrial & Systems Engineering from North Carolina State University\, and holds a Ph.D. in Industrial Engineering from Purdue University. He is a member of INFORMS\, IISE and is a council member in Society for Risk Analysis. URL:https://or.ncsu.edu/event/or-seminar-ben-rachunok-04-10-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-ben-rachunok-04-12-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230403T163000 DTEND;TZID=America/New_York:20230403T174500 DTSTAMP:20260626T171833 CREATED:20260129T210708Z LAST-MODIFIED:20260129T210708Z UID:10000092-1680539400-1680543900@or.ncsu.edu SUMMARY:OR Seminar: Jordan Kern DESCRIPTION:Join us in welcoming Jordan Kern\, an NC State assistant professor in the Department of Forestry and Environmental Resources\, as he shares his energy systems research. \nDid You Miss It?\nWatch it NOW! \nTitle\nAdvancing the optimal design and management of low carbon energy systems in a time of emerging vulnerabilities \nAbstract\nBulk electric power systems are highly interconnected\, continental in scale\, and operated as synchronous machines that must constantly balance (in both space and time) the movement and consumption of electricity with production from different generators. As an aging\, complex system\, the power grid routinely experiences failures (often caused by extreme weather) that can lead to losses of life and economic damages. The grid is also\, arguably\, the single most important component of large-scale efforts to “de-carbonize” the U.S. economy. This is likely to involve grid expansion and a rapid scale-up of renewable energy capacity like solar and wind\, which will more firmly link system dynamics (including reliability) to weather fluctuations. Yet\, robustly characterizing power systems’ performance is a significant challenge\, due to: a) system complexity and scale; b) multi-scale\, multi-variate uncertainties; and c) a general lack of open source modeling options that adequately balance simulation speed and model accuracy. This talk will discuss our group’s development and application of new computational tools to inform optimal design and management of robust\, low-to-zero carbon grids through stochastic simulation of system dynamics and analysis of capital investment and short-term grid operations. \nBiography\nJordan Kern is an Assistant Professor of Coupled Natural-Human Systems at North Carolina State University\, where he has a primary appointment in the Department of Forestry and Environmental Resources and graduate faculty appointments in Operations Research\, and Civil\, Construction\, and Environmental Engineering. His group’s research tries to advance optimal design and management of low-to-zero carbon energy systems\, with a special focus on: 1) building high resolution models of real-world energy systems; 2) simulating system dynamics under uncertainty and stress; and 3) informing optimal decision making around capital investment and short term operations. His group’s research has been featured frequently in the national media (e.g. NPR\, LA Times\, Vox\, TIME)\, and since 2016 his group has received $3.16 million in extramurally funded research awards (part of $43 million in total collaborative funds). In 2022\, he received the National Science Foundation’s (NSF) CAREER award for his proposal titled\, “Navigating a Two-Front Challenge for the Power Grid: Extreme Weather and the Race to Decarbonization.” URL:https://or.ncsu.edu/event/or-seminar-jordan-kern-04-03-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-jordan-kern-04-03-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230327T163000 DTEND;TZID=America/New_York:20230327T174500 DTSTAMP:20260626T171833 CREATED:20260129T211126Z LAST-MODIFIED:20260211T150836Z UID:10000093-1679934600-1679939100@or.ncsu.edu SUMMARY:OR Seminar: Katya Scheinberg DESCRIPTION:Join us in welcoming Katya Scheinberg\, a professor in the Operations Research and Information Engineering Department at Cornell University\, as she discusses her research. \nDid You Miss It?\nWatch it NOW! \nTitle\nOverview of Adaptive Stochastic Optimization Methods \nAbstract\nRecently a variety of stochastic variants of adaptive methods have been developed and analyzed. These include stochastic step search\, trust region and cubicly regularized Newton methods. Such methods adapt the step size parameter and use it to dictate the accuracy required or stochastic approximations. The requirements on stochastic approximations are\, thus\, also adaptive and in principle can be biased and even inconsistent. The step size parameters in these methods can increase and decrease based on the perceived progress\, but unlike the deterministic case they are not bounded away from zero. This creates obstacles in complexity analysis of such methods. We will show how by viewing such algorithms as stochastic processes with martingale behavior we can derive bounds on expected complexity that also apply in high probability. We also show that it is possible to derive a lower bound on step size parameters in high probability for the methods in this general framework. We will discuss various stochastic settings\, where the framework easily applies\, such as expectation minimization\, black box and simulation optimization\, expectation minimization with corrupt samples\, etc. \nBiography\nKatya Scheinberg is a Professor and Director of Graduate Studies at the School of Operations Research and Information Engineering at Cornell University. Prior to joining Cornell she was the Harvey E. Wagner Endowed Chair Professor at the Industrial and Systems Engineering Department at Lehigh University. She attended Moscow University for her undergraduate studies and received her PhD degree from Columbia University. She worked at the IBM T.J. Watson Research Center as a research staff member for over a decade before joining Lehigh in 2010. \nKatya’s main research areas are related to developing practical algorithms (and their theoretical analysis) for various problems in continuous optimization\, such as convex optimization\, derivative free optimization\, machine learning\, quadratic programming\, etc. \nShe is an Informs Fellow\, a recipient of the Lagrange Prize from SIAM and MOS\, the Farkas Prize from Informs Optimization Society and the Outstanding Simulation Publication award from Informs Simulation Society. Katya is currently the editor-in-chief of Mathematics of Operations Research\, and co-editor of Mathematical Programming. She served as the Chair of SIAM Activity Group on Optimization from 2020 until 2022. URL:https://or.ncsu.edu/event/or-seminar-katya-scheinberg-03-27-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-katya-scheinberg-03-27-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230320T163000 DTEND;TZID=America/New_York:20230320T174500 DTSTAMP:20260626T171833 CREATED:20260129T212926Z LAST-MODIFIED:20260129T212947Z UID:10000095-1679329800-1679334300@or.ncsu.edu SUMMARY:OR Seminar: OR Ph.D. Students DESCRIPTION:Monday’s panel talk will be an open discussion\, in the spirit of an AMA (ask me anything)\, where you can ask your most pressing questions about how research is conducted at a high level. \nStudents early in their Ph.D. or thesis-based master’s program are often faced early on with long-term decisions and no clear answers: \n\nShould this person be my advisor?\nIs this a good topic to pursue?\nWhat are the possible sources of funding and their trade-offs?\nHow does the research process work?\nAnd many more\n\nThe objective of this seminar is to help make connections with experienced students who have been through it before so they can provide more than one perspective on how these decisions can be approached. Feel free to bring questions of your own. \nDid you miss it?\nWatch it Now! \nBiographies\nRuss Nelson is a US Army operations research/systems analyst (ORSA)\, former Army aviator\, and current Ph.D. candidate in the Operations Research Program at NC State. His previous roles have included assault helicopter company commander\, Army aviation doctrine developer\, and assistant professor in the Department of Mathematical Sciences at the United States Military Academy (USMA) at West Point. Prior to joining NC State\, he worked with statisticians in creating designs of experiments and conducting statistical analysis at the Army Evaluation Center in support of the Army Test and Evaluation Command. Upon graduation from NC State\, he will return to an assistant professor role at USMA. \nSatya Paramita is a Ph.D. Candidate in OR under the direction of Dr. Osman Ozaltin. She has been involved in several projects during her Ph.D.\, including health scoring system development and evaluation\, examination of medical surge during the COVID-19 pandemic and assessing the impact of law-enforcement drug seizures on overdose mortality. \nMargaret Tobey is a Ph.D. candidate in the OR program. She is advised by Dr. Mayorga and Dr. Ozaltin and expects to graduate this summer. The group collaborates with a counter-human trafficking nonprofit to develop risk prediction models that can assist in human trafficking investigations and serving victims. Methods include natural language processing\, interpretable machine learning models such as risk scoring systems\, and geospatial analysis. \nEkin Yalvac’s research focuses on the interface of operations and economics. He is currently working on the optimization of sustainable energy transfer and storage systems and the network design of autonomous delivery systems. URL:https://or.ncsu.edu/event/or-seminar-or-ph-d-students-03-20-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/or-seminar-series-default-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230306T163000 DTEND;TZID=America/New_York:20230306T174500 DTSTAMP:20260626T171833 CREATED:20260129T213834Z LAST-MODIFIED:20260129T213834Z UID:10000096-1678120200-1678124700@or.ncsu.edu SUMMARY:OR Seminar: Frank Curtis DESCRIPTION:Join us in welcoming Frank Curtis\, professor and director of graduate studies in industrial engineering at Lehigh University\, as he discusses his research. His research focuses on designing\, analyzing\, and implementing numerical methods for solving large-scale nonlinear optimization problems. \nDid you miss it?\nWatch it Now!\nPassword: &?%!Q6*7\n \nDownload the Presentation \nTitle\nStochastic Algorithms for Solving Constrained Optimization Problems \nAbstract\nI will present recent work by my research group on solving constrained continuous optimization problems with stochastic algorithms. I will provide an overview of a suite of sequential quadratic optimization (commonly known as SQP) algorithms that we have proposed\, analyzed\, and tested for which we have convergence-in-expectation and worst-case complexity guarantees. I will also discuss recent work on the design and analysis of a stochastic interior-point method\, which\, as far as we are aware\, is the first of its kind. Our algorithms are motivated by various applications\, including fair and domain-informed machine learning. \nBiography\nFrank E. Curtis is a professor in the Department of Industrial and Systems Engineering at Lehigh University. His research focuses on the design\, analysis\, and implementation of algorithms for solving large-scale optimization problems. He received an Early Career Award from the ASCR program of the U.S. Department of Energy and has received funding from various programs of the U.S. National Science Foundation as well as from the Office of Naval Research. He received\, along with Leon Bottou (Facebook AI) and Jorge Nocedal (Northwestern)\, the 2021 SIAM/MOS Lagrange Prize in Continuous Optimization. He was awarded\, with James V. Burke (Washington)\, Adrian Lewis (Cornell)\, and Michael Overton (NYU)\, the 2018 INFORMS Computing Society Prize. He currently serves as Area Editor for Continuous Optimization for Mathematics of Operations Research and as an Associate Editor for Mathematical Programming\, SIAM Journal on Optimization\, IMA Journal of Numerical Analysis\, and Mathematical Programming Computation. URL:https://or.ncsu.edu/event/or-seminar-frank-curtis-03-06-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-frank-curtis-03-06-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230227T163000 DTEND;TZID=America/New_York:20230227T174500 DTSTAMP:20260626T171833 CREATED:20260129T214141Z LAST-MODIFIED:20260129T214141Z UID:10000097-1677515400-1677519900@or.ncsu.edu SUMMARY:OR Seminar: Russ Nelson DESCRIPTION:Join us in welcoming our own Russ Nelson\, OR Ph.D. student\, as he will discuss operations research applications in US Army. \nDid you miss it?\nhttps://ncsu.zoom.us/rec/share/Z0oe4FnsKG3GfKBC0V6A6RGCJb78AE16vrfjhP21Y9BP1WPD7aP7NU3SK2agorXa.-laXaMH90vvdqClc\nPassword: 1N=jWxP6 \nTitle\nOperations Research Applications in US Army Aviation Air Movement Operations \nAbstract\nAlthough lacking the same preeminent status of air assault planning\, air movement operations comprise a majority of Army utility and cargo helicopter combat aviation operations regarding the volume of customers and the endless appetite for rapid movement of troops across the battlespace. We propose an Army aviation air movement mission planning model to assist the mission planner by rapidly providing courses of action based on the commander's priorities. Features of the problem include priority demand\, multi-node refueling\, aircraft\, and passenger time windows\, maximum passenger transportation time\, the minimization of unsupported demand\, aircraft utilization\, and total flight time. The mathematical model is an extension of the dial-a-ride problem (DARP) that will coordinate air mission requests (AMRs) at the aviation task force level or lower to generate courses of action that optimize helicopter fleet resourcing and routing decisions against mission variables while supporting the optimal number of AMRs that sustain combat power over time. Additional work includes a heuristic improvement and analysis required to generate feasible solutions in near real-time. Furthermore\, we propose an Army aviation two-stage stochastic programming model to allocate utility helicopters across areas of operations separated task forces to minimize routing costs and the number of unsupported air movement AMRs by priority level. \nBiography\nRuss is a US Army operations research/systems analyst (ORSA)\, former Army aviator\, and current Ph.D. candidate in the Operations Research Program at NC State. His previous roles have included assault helicopter platoon leader and company commander\, Army aviation doctrine developer\, and assistant professor in the Department of Mathematical Sciences at the United States Military Academy (USMA) at West Point. Prior to joining NC State\, he worked with statisticians in creating designs of experiments and conducting statistical analysis at the Army Evaluation Center in support of the Army Test and Evaluation Command. Upon graduation from NC State\, he will return to an assistant professor role at USMA. URL:https://or.ncsu.edu/event/or-seminar-russ-nelson-02-27-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/grad-student-profile-russ-nelson-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230220T163000 DTEND;TZID=America/New_York:20230220T174500 DTSTAMP:20260626T171833 CREATED:20260129T214451Z LAST-MODIFIED:20260129T214643Z UID:10000098-1676910600-1676915100@or.ncsu.edu SUMMARY:OR Seminar: Raghu Pasupathy DESCRIPTION:Join us in welcoming Raghu Pasupathy\, professor of statistics at Purdue University\, as he discusses his research. \nMissed the Presentation?\nWatch the recording NOW\nPassword: p22CSfD$ \nTitle\nBatching as a General Statistical Inference Device \nAbstract\nConsider the following example problem settings: (i) estimate the 90th percentile time-dependent inventory level at multiple points in a large simulated supply chain; (ii) estimate the optimal glass cooling schedule as the solution to a stochastic optimization problem subject to PDE constraints relating to heat flow; and (iii) estimate the time-dependent expected number of infections in an epidemic that is modeled using an SDE. Each of (i) — (iii) constitutes a setting where a time series of data obtained through some means\, e.g.\, a simulation\, is “processed” in the service of estimating a parameter such as a percentile curve or the solution to an optimization problem. We consider statistical inference in such contexts\, whereby one seeks to quantify the error in an obtained estimator\, e.g.\, through a confidence region or a hypothesis test. \nHistorically\, inference within complicated computational contexts has been considered challenging because the parameter needing estimation is often not a mean\, and the input time series is non-normal and exhibits heavy dependence. We argue\, however\, that the remarkably simple idea of batching might provide a solution. Batching\, like the bootstrap\, is a resampling idea and works in three steps: (i) divide the input time series into overlapping batches; (ii) construct parameter estimates from each batch; and (iii) appropriately use the batch estimates after accounting for dependence\, to perform statistical inference. The resulting procedures are usually trivial to implement in software and\, as we show\, are provably correct and efficient. Batching ideas originated in the 1950s and have enjoyed steady development in the simulation community since the 1970s\, mostly within the problem of variance estimation. Our thesis is that batching ideas have much wider utility. Time permitting\, I will discuss batching’s relationship to the bootstrap and subsampling\, along with numerical examples. \nBiography\nRaghu Pasupathy is a Professor of Statistics at Purdue University. Prior to joining Purdue in 2014\, Paspathy spent nine years in the Industrial and Systems Engineering Department at Virginia Tech\, first as an assistant professor and then as an associate\nprofessor. Pasupathy’s research interests lie in the theoretical and computational aspects of stochastic optimization. Pasupathy has been associated with the simulation and optimization communities in various capacities over the previous two decades\, including serving as President of the INFORMS Simulation Society from 2018 — 2020 and\nas an editor for ACM TOMACS\, Operations Research\, INFORMS Journal on Computing\, IISE Transactions\, and Mathematical Programming. More information\, including downloadable papers and computational software\, can be obtained through his website at https://web.ics.purdue.edu/~pasupath/ URL:https://or.ncsu.edu/event/or-seminar-raghu-pasupathy-02-20-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-raghu-pasupathy-02-20-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230213T163000 DTEND;TZID=America/New_York:20230213T174500 DTSTAMP:20260626T171833 CREATED:20260129T215007Z LAST-MODIFIED:20260211T151131Z UID:10000099-1676305800-1676310300@or.ncsu.edu SUMMARY:OR Seminar: Katie Homar DESCRIPTION:Join us in welcoming NC State’s Katie Homar\, Director of Academic and Engineering Writing Support at the Graduate School\, as she discusses writing programs. \nZoom Meeting\nhttps://ncsu.zoom.us/j/91749207591?pwd=UnhkSldaQ290RG0rYitSVVZZK0lDUT09\nMeeting ID: 917 4920 7591\nPasscode: 303411 \nTitle\nGraduate School Engineering Writing Programs \nSession Description\nIn this session\, you will learn about opportunities to develop your academic and professional writing skills from the Graduate School. We will discuss the formats of our programming\, the benefits of participating\, and how you can get involved this semester. Previous program participants will also be available to share their experiences. \nBiography\nWith more than 10 years of experience in teaching writing\, Homar has a strong background in writing across disciplines\, rhetoric\, and teaching English to speakers of other languages (TESOL). In her current role with the Graduate School\, she designs and delivers writing-oriented professional development programming for graduate and postdoc trainees across disciplines. Prior to joining NC State\, Homar was a Brittain Postdoctoral Fellow at Georgia Institute of Technology’s Writing and Communication Program. She holds a Ph.D. in English and a TESOL certificate from the University of Pittsburgh. URL:https://or.ncsu.edu/event/or-seminar-katie-homar-02-13-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-katie-homar-02-13-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230206T163000 DTEND;TZID=America/New_York:20230206T174500 DTSTAMP:20260626T171833 CREATED:20260129T220011Z LAST-MODIFIED:20260129T220011Z UID:10000101-1675701000-1675705500@or.ncsu.edu SUMMARY:OR Seminar: Juan Borrero DESCRIPTION:Join us in welcoming Juan Borrero\, an assistant professor from the Industrial Engineering and Management Department at Oklahoma State University\, as he shares his research. \nZoom Meeting\nhttps://ncsu.zoom.us/j/91749207591?pwd=UnhkSldaQ290RG0rYitSVVZZK0lDUT09\nMeeting ID: 917 4920 7591\nPasscode: 303411 \nTitle\nA Robust Optimization Approach to Enhance Community Resilience under Tornado Hazards \nAbstract\nCatastrophic tornadoes cause severe damage and threaten the overall well-being of many communities across the US. Recent research has shown that the resilience of existing structures to tornadoes can be enhanced by implementing simple retrofitting strategies\, such as improving the cover and nailing patterns of roofs. Whereas at the federal level retrofitting is now seen as a valid tool to prepare for disasters\, agencies at the local level rarely consider retrofitting in their emergency preparedness plans. In this talk\, we consider a decision-maker (a local emergency management agency or a public-private consortium) who seeks to allocate resources in retrofitting and recovery strategies to minimize the population dislocation in an urban area due to an uncertain tornado. As tornado paths cannot be forecast reliably\, we model the problem using two-stage robust optimization: retrofitting decisions are made in the first stage\, and recovery decisions are made in the second stage after observing the tornado. We assume that tornado paths can be represented as line segments and that a location is affected by the tornado if it is sufficiently close to the line segment\, which results in a mixed-integer non-linear uncertainty set. To solve the problem\, we use a decomposition column-and-constraint generation algorithm that requires solving a challenging two-level optimization subproblem at each iteration. As this subproblem cannot be tackled by standard ‘dualize and combine’ techniques\, we design a decomposition branch and cut (DBC) algorithm that adds two types of constraints on the fly. Particularly\, the initial constraints of the master relaxation and the feasibility check of the DBC are constructed by exploiting the geometric properties of the uncertainty set. Numerical results are reported using real data from Joplin\, MO\, which show that there can be reductions of up to 20% in worst-case population dislocation by investing $15 million in retrofitting and recovery. The results also show that our approach can outperform random retrofitting policies by margins close to 20% and that the model does not suffer from over-conservativeness. Moreover\, we show that the population dislocation exhibits a considerable ‘diminishing returns’ behavior with respect to budget: beyond $15 million\, the reduction in population dislocation is not significant. \nBiography\nJuan S. Borrero is an Assistant Professor in the School of Industrial Engineering and Management at Oklahoma State University. He holds a B.Sc. in Mathematics and an M.Sc. in Industrial Engineering\, both from the University of Los Andes\, Bogota\, Colombia\, and holds a Ph.D. in Industrial Engineering from the University of Pittsburgh (2017). His research interests are mainly in the area of optimization under uncertainty. Methodologically\, his focus is on bilevel\, robust\, network and mixed-integer optimization\, probability\, and stochastic processes. From his doctorate onwards\, he has focused on sequential hierarchical decision-making problems with uncertainty and learning\, including applications such as smuggling interdiction\, defender-attacker problems\, and commit or defer problems. More recently\, he has worked in applications such as preparedness and response against tornado hazards\, UAV routing for intelligence\, surveillance\, and reconnaissance missions\, supply operations under uncertain rippled attacks\, and influence problems in social networks\, among others. His research has been funded by ONR\, AFOSR\, and by an NSF CAREER award. URL:https://or.ncsu.edu/event/or-seminar-juan-borrero-02-06-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-juan-borrero-02-06-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230130T163000 DTEND;TZID=America/New_York:20230130T174500 DTSTAMP:20260626T171833 CREATED:20260130T133823Z LAST-MODIFIED:20260211T151301Z UID:10000102-1675096200-1675100700@or.ncsu.edu SUMMARY:OR Seminar: Kevin Flores DESCRIPTION:Join us in welcoming Kevin Flores\, an assistant professor from the Mathematics Department here at NC State University\, as he discusses learning differential equation models from noisy biological data. \nZoom Meeting\nhttps://ncsu.zoom.us/j/91749207591?pwd=UnhkSldaQ290RG0rYitSVVZZK0lDUT09\nMeeting ID: 917 4920 7591\nPasscode: 303411 \nAbstract\nEquation learning aims to discover differential equations that describe the underlying dynamics of time series data. Biological systems have unique challenges in applying equation learning\, namely\, the observed data are sparsely measured and have high levels of proportional error noise. Moreover\, equation learning methods can suffer from the model specification problem in which the governing differential equation model must be specified a priori either explicitly or as a library of candidate terms. This poses a challenge for biological systems\, which are often described by nonlinear terms with unknown exponents. These issues help explain why equation learning has seen very few applications in real-world biological systems. In this talk\, I will discuss methods that were developed to overcome these challenges. The methodology is demonstrated on simulated data of biological transport from the Fisher-KPP equation\, experimental data of collective cell migration in scratch assays\, and agent-based model simulations of a birth-death-migration process on a 2-d lattice. \nBiography\nKevin Flores joined NC State in August 2015 as a Chancellor’s Faculty Excellence Program cluster hire in Precision Medicine. He is an associate professor in the Department of Mathematics and is a member of the Center for Research in Scientific Computation. Flores’ research focuses on mathematical modeling\, optimal experimental design and uncertainty quantification with applications to precision medicine\, systems and synthetic biology\, and environmental toxicology.\nHe earned a Ph.D. in applied mathematics from the School of Life Sciences at Arizona State University. Previously\, he was a postdoctoral fellow in NC State’s Department of Mathematics. He was a postdoctoral associate in the School of Life Sciences at Arizona State University and a bioinformatician in the Division of Biomedical Statistics and Informatics at the Mayo Clinic. He currently serves as co-chair of the Methods for Biological Modeling subgroup for the Society for Mathematical Biology and as an Associate Editor for the journal Mathematical Biosciences and Engineering. URL:https://or.ncsu.edu/event/or-seminar-kevin-flores-01-30-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-kevin-flores-01-30-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20230109T163000 DTEND;TZID=America/New_York:20230109T174500 DTSTAMP:20260626T171833 CREATED:20260130T134429Z LAST-MODIFIED:20260130T134429Z UID:10000104-1673281800-1673286300@or.ncsu.edu SUMMARY:OR Seminar: Xiaoyan "X.Y." Han DESCRIPTION:Join us in welcoming Xiaoyan “X.Y.” Han\, a Ph.D. candidate from the Operations Research and Information Engineering Department at Cornell University. \nZoom Meeting\nhttps://ncsu.zoom.us/j/91749207591?pwd=UnhkSldaQ290RG0rYitSVVZZK0lDUT09\nMeeting ID: 917 4920 7591\nPasscode: 303411 \nAbstract\nOver the last decade\, research in machine learning and optimization emerged as a dominant concern in all fields of industrial and academic research\, with several key venues dominating the league tables for science-wide citation impact. From this milieu emerges a powerful research paradigm that is driven by the identification and analysis of pervasive phenomena discovered in realistic\, large-scale experiments. In many cases\, it delivers immediate improvements in key analytics algorithms affecting large communities of users; in other cases\, it delivers lasting insights about the behavior of such algorithms. \nIn this talk\, I discuss my own work under this emerging paradigm\, which has delivered both real-world solutions as well as intellectual insights: They include the discovery of the now-widely-studied Neural Collapse phenomenon in deep net training\, the Survey Descent method for nonsmooth optimization and collaborations with the Frick Art Reference Library in NYC and the Veolia North America Utilities company. \nBiography\nX.Y. Han is a Ph.D. candidate supervised by Adrian S. Lewis at Cornell ORIE; previously\, he earned an MS from Stanford Statistics—where he began still-ongoing research mentored by David L. Donoho—and a BSE from Princeton ORFE. He discovered the now-widely-studied Neural Collapse phenomenon in deep neural network training (with V. Papyan and D.L. Donoho). He invented the Survey Descent method for nonsmooth optimization (with A.S. Lewis)—while also maintaining real-world collaborations with the Frick Art Reference Library in NYC\, the USC Keck School of Medicine\, and the Veolia North America utility company. Recently\, his work on Neural Collapse won the ICLR 2022 Outstanding Paper Award\, and his work on Survey Descent was a finalist for the ICCOPT 2022 Best Paper Prize. URL:https://or.ncsu.edu/event/or-seminar-xiaoyan-xy-han-01-09-2023/ LOCATION:4290 Fitts-Woolard Hall\, 915 Partners Way\, Raleigh\, NC\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-xiaoyan-han-01-09-2023-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221215T133000 DTEND;TZID=America/New_York:20221215T160000 DTSTAMP:20260626T171833 CREATED:20260130T134721Z LAST-MODIFIED:20260130T134721Z UID:10000105-1671111000-1671120000@or.ncsu.edu SUMMARY:Fall 2022 Graduation Ceremony DESCRIPTION:The OR Fall 2022 Graduation Ceremony begins at 1:30 pm with a reception following the ceremony. The event will be live-streamed starting at 1:15 pm for friends and families to enjoy. URL:https://or.ncsu.edu/event/fall-2022-graduation-ceremony/ LOCATION:McKimmon Center\, 1101 Gorman Street\, Raleigh\, 27606\, United States CATEGORIES:OR Program Events ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2025/08/graduation-ceremony-default-feature-image-08-2025-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221205T163000 DTEND;TZID=America/New_York:20221205T174500 DTSTAMP:20260626T171833 CREATED:20260130T135703Z LAST-MODIFIED:20260130T135703Z UID:10000106-1670257800-1670262300@or.ncsu.edu SUMMARY:OR Seminar: Varun Khemani DESCRIPTION:Join us in welcoming Varun Khemani from the Operations Research and Advanced Analytics Group at American Airlines to the OR Department. \nDid you Miss it?\nWatch Varun Khemani’s presentation \nTitle\nOR/ML at American Airlines \nAbstract\nPositioned within the Information Technology organization\, the OR&AA team at American Airlines has a long history of being on the leading edge of analyt-ics in the airline domain. Nearly four decades ago we launched the revenue management revolution with our yield management strategy. Today our di-verse team of passionate analytics professionals supports decision making across the airline\, including pricing and revenue management\, fleet and net-work optimization\, crew and flight scheduling\, airport and maintenance opera-tions and customer/social media analytics. \nThis talk will provide an overview of some of the challenging projects that the team has successfully completed\, for example\, Network Schedule Evaluation System\, Crew Assignment\, Fleet Assignment Model\, Deep-Learning based RM Forecaster\, Enabling Predictive Maintenance Using Analytics\, Baggage Transfer Routing Optimization\, and Classifying Customers’ Tweets. \nBiography\nI have been working as a Predictive Maintenance Data Scientist in the Operations Research and Advanced Analytics (ORAA) group at American Airlines for the past few months. I work with a variety of business units to help develop data-driven solutions to optimize their business operations. I have a PhD in Reliability Engineering from University of Maryland and a Master’s in Industrial Engineering from North Carolina State University (Go Pack!) with a focus on Design of Experiments. Aside from classical Artificial Intelligence/Machine Learning techniques\, I have experience in stochastic optimization reliability\, functional safety and cybersecurity. URL:https://or.ncsu.edu/event/or-seminar-varun-khemani-12-05-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-varun-khemani-12-05-2022-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221128T163000 DTEND;TZID=America/New_York:20221128T174500 DTSTAMP:20260626T171833 CREATED:20260130T140312Z LAST-MODIFIED:20260130T140312Z UID:10000107-1669653000-1669657500@or.ncsu.edu SUMMARY:OR Seminar: Destenie Nock DESCRIPTION:Please join us in welcoming Destenie Nock\, an assistant professor in the Civil and Environmental Engineering Department at Carnegie Mellon. \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. \nDid You Miss It?\nWatch Destenie Nock’s presentation \nTitle\nEnergy Limiting Behavior a Hidden Form of Energy Poverty \nAbstract\nIncome-based energy poverty metrics miss people’s behavior patterns\, particularly those who reduce their energy consumption to limit financial stress. Using a residential electricity consumption dataset\, we determine the outdoor temperature at which households start using home cooling systems. Using this inflection temperature\, we calculate the relative energy poverty within a region\, which we define as the energy equity gap. In our study region\, we find that the energy equity gap between low and high-income groups ranges from 4.7°F to 7.5°F. In 2015-2016\, within our population of 4\,577 households\, we found 86 energy-poor and 214 energy-insecure\, meaning they are at risk of heat-related illness and death. In contrast\, traditional income-based energy poverty metric identified just 141 households as energy insecure. Only three households were defined as energy-poor or energy-insecure by both our temperature-based measure and the traditional income-based measure. This minimal overlap shows the value of considering consumer behavior when identifying energy poverty and energy insecurity. \nBiography\nDestenie Nock is a leader in energy justice\, energy justice\, and sustainable energy transition trade-off analysis. In her role as an Assistant Professor in Civil and Environmental Engineering (CEE) and Engineering and Public Policy (EPP)\, she creates optimization and decision analysis tools that evaluate the sustainability\, equity\, and reliability of power systems in the US and Sub-Saharan Africa. In another project\, she is creating a new measure of energy poverty to help utility companies identify energy-limiting behavior in low-income households\, a hidden form of energy poverty. Nock is also the CEO of Peoples Energy Analytics\, a data-driven company that uses energy analytics to identify energy poverty in vulnerable households. She is also the CSO of DevvStream. Before her current position at CMU\, Nock received her Ph.D. in Industrial Engineering and Operations Research from the University of Massachusetts Amherst. She earned an MSc in Leadership for Sustainable Development at Queen’s University of Belfast and two BS degrees in Electrical Engineering and Applied Math at North Carolina A&T State University. She is the creator of the Black Electricity Blog site\, which posts articles about graduate and undergraduate advice\, and research updates in energy and sustainability. URL:https://or.ncsu.edu/event/or-seminar-destenie-nock-11-28-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-destenie-nock-11-28-2026-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221121T163000 DTEND;TZID=America/New_York:20221121T174500 DTSTAMP:20260626T171833 CREATED:20260130T140607Z LAST-MODIFIED:20260211T151605Z UID:10000108-1669048200-1669052700@or.ncsu.edu SUMMARY:OR Seminar: Gabriel Zayas-Cabán DESCRIPTION:Evaluation of a Split Flow Model for the Emergency Department\nDon’t miss Gabriel Zayas-Cabán\, from the University of Wisconsin-Madison\, as he discusses evaluating an emergency department split flow model. \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. \nDid You Miss It?\nWatch Gabriel Zayas-Caban’s presentation \nTitle\nEvaluation of a Split Flow Model for the Emergency Department \nAbstract\nSplit flow models\, in which a physician rather than a nurse performs triage\, are increasingly being used in hospital emergency departments (EDs) to improve patient flow. Before deciding whether such interventions should be adopted\, it is important to understand how split flows causally impact patient flow and outcomes. We employ causal inference methodology to estimate average causal effects of a split flow model on time to be roomed\, time to disposition after being roomed\, admission decisions\, and ED revisits at a large tertiary teaching hospital that uses a split flow model during certain hours each day. We propose a regression discontinuity (RD) design to identify average causal effects\, which we formalize with causal diagrams. Using electronic health records data (n = 21\,570)\, we estimate that split flow increases average time to be roomed by about 4.6 minutes (95% CI: [2.9\,6.2] minutes) but decreases average time to disposition by 14.4 minutes (95% CI: [4.1\,24.7] minutes)\, leading to an overall reduction in length of stay. Split flow is also found to decrease admission rates by 5.9% (95% CI: [2.3%\, 9.4%]) but not at the expense of a significant change in revisit rates. Lastly\, we find that the split flow model is especially effective at reducing length of stay during low congestion levels\, which mediation analysis partly attributes to early task initiation by the physician assigned to triage. \nBiography\nDr. Zayas-Caban is the Jane R. and Jack G. Mandula Assistant Professor in the Industrial and Systems Engineering Department at the University of Wisconsin-Madison. He also holds an affiliate appointment with the Berbee Walsh Department of Emergency Medicine in the School of Medicine and Public Health. His research is in operations research with an emphasis on healthcare delivery. His recent focus is on emergency department admission decisions and care transitions. He also has some recent work on evaluating the impact of diverting non-violent offenders to substance use disorder treatment. Before coming to Wisconsin\, Gabriel was a President’s Postdoctoral Fellow at the University of Michigan and completed his Ph.D. at Cornell University’s Center for Applied Mathematics\, advised by Professor Mark E. Lewis. He received his B.A. in Mathematics from the University of South Florida.\n  \nDownload Gabriel Zayas-Cabán’s Abstract and Biography URL:https://or.ncsu.edu/event/or-seminar-gabriel-zayas-caban-11-21-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-gabriel-zayas-caban-11-21-2022-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221114T163000 DTEND;TZID=America/New_York:20221114T174500 DTSTAMP:20260626T171834 CREATED:20260130T140920Z LAST-MODIFIED:20260130T141036Z UID:10000109-1668443400-1668447900@or.ncsu.edu SUMMARY:OR Seminar: Donald Warsing DESCRIPTION:Don’t miss Don Warsing\, a professor from NC State’s Poole College of Management. He will be discussing his research on multi-objective optimization of testing protocols to screen for COVID-19. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/93958805097?pwd=azltMmloZlp6dzRLWjBtOUtUdU1pdz09\nMeeting ID: 939 5880 5097\nPasscode: 547206 \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. URL:https://or.ncsu.edu/event/or-seminar-donald-warsing-11-14-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-don-warsing-11-14-2022-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221107T163000 DTEND;TZID=America/New_York:20221107T174500 DTSTAMP:20260626T171834 CREATED:20260130T141358Z LAST-MODIFIED:20260130T141358Z UID:10000110-1667838600-1667843100@or.ncsu.edu SUMMARY:OR Seminar: Nabaruna Karmarkar DESCRIPTION:Please welcome back ISE alumna Nabaruna Karmarkar\, a senior operations research specialist from the SAS Analytics Center of Excellence. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/93958805097?pwd=azltMmloZlp6dzRLWjBtOUtUdU1pdz09\nMeeting ID: 939 5880 5097\nPasscode: 547206 \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. URL:https://or.ncsu.edu/event/or-seminar-nabaruna-karmarkar-11-07-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-nabaruna-karmakar-11-07-2022-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221024T163000 DTEND;TZID=America/New_York:20221024T174500 DTSTAMP:20260626T171834 CREATED:20260130T142118Z LAST-MODIFIED:20260130T142118Z UID:10000112-1666629000-1666633500@or.ncsu.edu SUMMARY:OR Seminar: Minh Tang DESCRIPTION:Please join us in welcoming Minh Tang\, assistant professor from the NC State’s Statistics Department\, as he discusses deviation analysis of randomized singular value decomposition (SVD) and its applications to high-dimensional statistics. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/93958805097?pwd=azltMmloZlp6dzRLWjBtOUtUdU1pdz09\nMeeting ID: 939 5880 5097\nPasscode: 547206 \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. \nAbstract\nRandomized singular value decomposition (RSVD) is a class of computationally efficient algorithms for computing the truncated SVD of large data matrices. Given a symmetric matrix M\, the prototypical RSVD algorithm approximates the k leading singular vectors of M by computing the SVD of M g G Insert Formula M^{g} G; here g is a positive integer and G is a Gaussian sketching matrix. In this talk\, we present statistical properties of RSVD under a general "signal-plus-noise" framework\, i.e.\, the observed matrix is assumed to be an additive perturbation of some true but unknown signal matrix. We first derive upper bounds for the spectral norm and two-to-infinity norm between the approximate singular vectors of the observed matrix and the true singular vectors of the signal matrix. These upper bounds depend on the signal-to-noise ratio (SNR) and the number of power iterations g. A phase transition phenomenon is observed in which a smaller SNR requires larger values of g to guarantee convergence of the spectral and two-to-infinity norms. Finally\, we derive normal approximations for the row-wise fluctuations of the approximate singular vectors and entrywise fluctuations of the observed matrix when projected onto these vectors. We illustrate our results by deriving nearly-optimal performance guarantees for RSVD when applied to three statistical inference problems\, namely\, community detection in networks\, matrix completion\, and PCA with missing data. \nBiography\nMinh Tang received a BS degree from Assumption University (Thailand) in 2001\, an MS degree from the University of Wisconsin Milwaukee in 2004 and a Ph.D. degree from Indiana University Bloomington in 2010\, all in computer science. He was a postdoctoral fellow and subsequently research faculty in the Department of Applied Mathematics and Statistics at Johns Hopkins University. He is currently an assistant professor in the Department of Statistics at North Carolina State University. His research interests include dimensionality reduction and statistical inference for high-dimensional and graph-valued data. URL:https://or.ncsu.edu/event/or-seminar-minh-tang-10-24-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-minh-tang-10-24-2022-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221003T163000 DTEND;TZID=America/New_York:20221003T174500 DTSTAMP:20260626T171834 CREATED:20260130T142310Z LAST-MODIFIED:20260211T151813Z UID:10000113-1664814600-1664819100@or.ncsu.edu SUMMARY:OR Seminar: INFORMS Practice Talks DESCRIPTION:Come out and show your love for the OR and ISE Ph.D. students\, Erik Rosenstrom (OR)\, Srinivasan Balan (ISE)\, Annisa Marlin Masbar Rus (ISE) and Margaret Tobey (OR). They are practicing their talks for the upcoming INFORMS Annual Conference. \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/93958805097?pwd=azltMmloZlp6dzRLWjBtOUtUdU1pdz09\nMeeting ID: 939 5880 5097\nPasscode: 547206\n  \nAbstracts\nErik Rosenstrom | Ph.D. Student\, Operations Research\nCatching Diabetic Retinopathy Early with Machine Learning\nDiabetic retinopathy (DR) is a complication of diabetes that can become vision-threatening (VTDR) and cause blindness. In the US\, an estimated 899\,000 diabetic adults have VTDR despite it being preventable with timely treatment. VTDR is difficult to catch due to the slow progression and dependence on patients’ care-seeking behavior. Here we address these challenges by leveraging 20+ years of electronic health records to construct and extend ensemble classifiers to (i) identify patients that will develop VTDR within the next year and (ii) identify those that will develop DR in the next year. We can achieve high recall (>75%) for both classification tasks. This classifier can personalize care coordination to improve utilization and timing without additional patient actions. \nSrinivasan Balan | Ph.D. Student\, Industrial and Systems Engineering\nExperimental Evaluation of Chance-Constrained Models for a Capacitated Stochastic Production Inventory System\nWe consider the problem of planning releases to a capacitated production-inventory system governed by queuing behavior and stochastic demand. We use a non-linear clearing function to represent the queuing behavior of the production system and a shortfall-based chance-constrained (CC) model to obtain scalable approximate solutions. We use a dynamic adaptive decision rule to implement the results of the CC models and evaluate their performance using simulation. \nAnnisa Marlin Masbar Rus | Ph.D. Student\, Industrial and Systems Engineering\nA Comparative Communication Analysis of Two U.S. Hospital Systems’ COVID-19 Communications Using Topic Modeling\nAlthough understanding initial internal communication to manage the COVID-19 pandemic within healthcare systems is important for effective operational strategies\, little is known regarding the themes within hospital-level communications. This study used structural topic modeling (STM) to analyze the internal communications of two healthcare systems from 2/2020 to 5/2021. The analysis also captured the influence of the hospital systems on communication content. COVID-19 communication topics were characterized using STM and their cross-healthcare systems variation to be compared. Variation was found in the main topics discussed across the healthcare systems in responding to the pandemic throughout the specified timeline. \nMargaret Tobey | Ph.D. Student\, Operations Research\nInterpretable Models for the Automated Detection of Human Trafficking in Illicit Massage Businesses\nIllicit massage businesses (IMBs) profit illegally from the labor and sexual exploitation of victim workers. To detect human trafficking in this area\, we combine data from multiple internet sources and train interpretable prediction models to identify human trafficking risk factors and assess each business’s risk level. URL:https://or.ncsu.edu/event/or-seminar-informs-practice-talks-10-03-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/or-seminar-series-default-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20220926T163000 DTEND;TZID=America/New_York:20220926T174500 DTSTAMP:20260626T171834 CREATED:20260130T142610Z LAST-MODIFIED:20260130T142610Z UID:10000114-1664209800-1664214300@or.ncsu.edu SUMMARY:OR Seminar: Vincent Yu DESCRIPTION:Please welcome Vincent Yu\, a postdoctoral research scholar in the Department of Business Management at NC State\, as he discusses the effects of CSR performance and price on consumer purchasing Decisions. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/93958805097?pwd=azltMmloZlp6dzRLWjBtOUtUdU1pdz09\nMeeting ID: 939 5880 5097\nPasscode: 547206 \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. URL:https://or.ncsu.edu/event/or-seminar-vincent-yu-09-26-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-vincent-yu-09-26-2022-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20220919T163000 DTEND;TZID=America/New_York:20220919T174500 DTSTAMP:20260626T171834 CREATED:20260130T142908Z LAST-MODIFIED:20260211T152021Z UID:10000115-1663605000-1663609500@or.ncsu.edu SUMMARY:OR Seminar: Beth Ashmore and Moira Downey DESCRIPTION:Please welcome Moira Downey and Beth Ashmore from the NC State Libraries as they host a data publication workshop. They will show you how to prepare your research data for public use. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/93958805097?pwd=azltMmloZlp6dzRLWjBtOUtUdU1pdz09\nMeeting ID: 939 5880 5097\nPasscode: 547206 \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. URL:https://or.ncsu.edu/event/or-seminar-beth-ashmore-and-moira-downey-09-19-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-moira-downey-beth-ashmore-09-19-2022-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20220912T163000 DTEND;TZID=America/New_York:20220912T174500 DTSTAMP:20260626T171834 CREATED:20260130T143351Z LAST-MODIFIED:20260130T143351Z UID:10000116-1663000200-1663004700@or.ncsu.edu SUMMARY:OR Seminar: Daniela Jones DESCRIPTION:Please welcome OR faculty member Daniela S. Jones\, an assistant professor of Biological and Agricultural Engineering at NC State\, as she discusses using agriculture analytics to decarbonize our food and energy needs. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/93958805097?pwd=azltMmloZlp6dzRLWjBtOUtUdU1pdz09\nMeeting ID: 939 5880 5097\nPasscode: 547206 \nTitle\nAgriculture Analytics to Decarbonize our Food and Energy Needs \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. URL:https://or.ncsu.edu/event/or-seminar-daniela-jones-09-12-2022/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2026/01/seminar-series-daniela-jones-09-12-2022-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20220829T163000 DTEND;TZID=America/New_York:20220829T174500 DTSTAMP:20260626T171834 CREATED:20260130T143559Z LAST-MODIFIED:20260130T143559Z UID:10000117-1661790600-1661795100@or.ncsu.edu SUMMARY:OR Seminar: New Student Orientation DESCRIPTION:Welcome new Operations Research students. Don’t miss out on the introduction to the program and an overview of the requirements for new students with Dr. Maria Mayorga. \nJoin Zoom Meeting\nhttps://ncsu.zoom.us/j/93958805097?pwd=azltMmloZlp6dzRLWjBtOUtUdU1pdz09\nMeeting ID: 939 5880 5097\nPasscode: 547206 \nOR PRO TIP: All OR 601/801 students must attend in person. Others are welcome to join in person or can join by Zoom. URL:https://or.ncsu.edu/event/or-seminar-new-student-orientation/ LOCATION:2321 Fitts-Woolard Hall\, 915 Partners Way Fitts-Woolard Hall\, Room 2321\, Raleigh\, North Carolina\, 27606\, United States CATEGORIES:OR Seminar Series ATTACH;FMTTYPE=image/jpeg:https://or.ncsu.edu/wp-content/uploads/sites/354/2023/07/mayorga-named-or-director-featured-image-01-2026-01.jpg ORGANIZER;CN="OR Program":MAILTO:operationsresearch@ncsu.edu END:VEVENT END:VCALENDAR