Optimizing Excellence Fall 25

INDUSTRIAL AND SYSTEMS ENGINEERING UNIVERSITY OF MINNESOTA - TWIN CITIES

OPTIMIZING

OPTIMIZING

EXCELLENCE

EXCELLENCE CLOSING THE USERCENTRIC DESIGN LOOP

OPTIMIZING WHAT WE REVEAL: INFORMATION DESIGN IN OPERATIONS

SCALING UP THE CARSHARING COMMUNITY

PHILOSOPHY IN ENGINEERING

2025

Industrial and Systems Engineering DEPARTMENT HEAD

ARCHIS GHATE DIRECTOR OF GRADUATE STUDIES

KEVIN LEDER DIRECTOR OF MASTERS PROGRAMS

KRISHNAMURTHY IYER DIRECTOR OF UNDERGRADUATE STUDIES

LISA MILLER DIRECTOR OF FACULTY AND ACADEMIC AFFAIRS

JEAN-PHILIPPE RICHARD CHIEF OF STAFF

TARYN VERLEY

DEPARTMENT OF INDUSTRIAL AND SYSTEMS ENGINEERING

207 Church St. SE Minneapolis, MN 55455 isye@umn.edu (612) 624-1582 www.isye.umn.edu

FROM THE DEPARTMENT HEAD I joined the University of Minnesota as the Department Head of Industrial and Systems Engineering (ISyE) last year. ISyE is a young department, about a dozen years old. In this short time, we have built a vibrant community of renowned scholars, exceptional teachers, amazing students, and dedicated staff. ISyE is committed to supporting the wellbeing and professional growth of all its constituents.

Our faculty and students work on methodological problems in optimization and stochastic systems, with applications in manufacturing, healthcare, transportation and logistics, energy, and economics. You may find us working on treatment plans for cancer; matching algorithms for organ transplants; policies for housing allocation; optimizing power flow in energy grids; analyzing online markets; scheduling patient surgeries; and calculating pricing strategies.

Regardless of the particular problem, we aspire to discover the mathematical theories that explain its salient features.

ISyE is entering a new era of growth in research, education, and service.

In collaboration with the Department of Computer Science and Engineering, the School of Statistics, and the School of Mathematics, some ISyE courses are now a part of the required curriculum for a bachelor’s degree in Data Science. ISyE also recently launched an MS program in Data Science in Operations Research where we continue to maintain an emphasis on data, artificial intelligence, and machine learning. Our PhD student population is also increasing in numbers and prestige.

Our undergraduate students participate in hands-on projects sponsored by local organizations, which helps them find a career after graduation. They are recruited by well-known employers such as 3M, Accenture, Boeing, Boston Scientific, Deloitte, Hewlett-Packard, Pentair, and Target. We hope to further expand this employer-base by adding more technology, finance, and sharing economy companies into the mix. ISyE’s location in a metropolitan area is a big advantage - opportunities for collaboration are only a few steps away. We plan to leverage these to build new partnerships so that our work is informed by, and influences, industry practice.

As we grow, ISyE is working with its broader community to raise funds for undergraduate and graduate scholarships, promote further collaboration between the department and industry, and pursue innovations that impact the world we co-habit.

Please join us on this exciting journey!

ARCHIS GHATE DEPARTMENT HEAD

CONTENT

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WELCOME, DR. SWATI PADMANABHAN

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Current undergraduate and graduate students share their stories and accomplishments

ISyE welcomes its newest faculty member

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FACULTY RESEARCH

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ISyE faculty members share their research interests and their impact on the academic and local community

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DEPARMENT OUTREACH ISyE faculty organize workshops and conferences

STUDENT SUCCESS STORIES

ALUMNI REFLECTIONS ISyE graduates reflect on the impact of their ISyE experience

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DEPARTMENT INSIGHTS ISyE faculty and student contributions to the academic community, as well as donor and seminar speaker spotlights

WELCOME, DR. SWATI PADMANABHAN ISyE is pleased to welcome Dr. Swati Padmanabhan to our faculty.

She received a doctorate degree in Electrical Engineering from the University of Washington, Seattle, in 2023, and spent two years as a Postdoctoral Associate at MIT before joining the University of Minnesota.

Dr. Padmanabhan conducts research on algorithms for continuous optimization problems arising in machine learning and theoretical computer science. Her work uses techniques from convex analysis, algorithm design, and statistics to develop provably efficient algorithms addressing scalability, nonsmoothness, and nonconvexity.

She was drawn to the beautiful city of Minneapolis and the collegial and warm department culture at ISyE. She also finds it exciting and valuable that the department includes faculty with a variety of research interests.

During the fall semester, Dr. Padmanabhan taught the “Optimization for Machine Learning” course. Teaching gave her an exciting opportunity to personalize course material as well as engage with students.

“I really enjoyed creating new lectures, homework, and exams. I also found opportunities to incorporate my research, and it was fun to see students engaged in the material. I look forward to advising students on research in the coming years,” she explains.

Dr. Padmanabhan’s expertise in algorithms for continuous optimization problems, with applications to computer science, engineering, and operations research, will be central to our department’s technical strengths.

We know that she will thrive in our department’s collegial environment to conduct research, collaborate with likeminded scholars, and advise graduate students, as she strives to reach new levels of excellence in her professional life.

Welcome, Dr. Padmanabhan!

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FEATURED RESEARCH & DEPARTMENT OUTREACH

CLOSING THE USER-CENTRIC DESIGN LOOP For ISyE Assistant Professor Yiling Zhang, user-centric design lies at the heart of many systems as systems and users shape each other.

The interest in interdependency began during PhD while working on solar power systems and flexible schedule loads to meet demand and consumption. At this time, literature was focusing on a user’s naturally predicted demand. Zhang began to interconnect user behavior and the way a system is designed. Instead of designing systems around assumed user behavior, she began asking how system design could shape, and be shaped by user decisions.

In the last 10 years, advancement and growth in options and technologies have changed how society looks at and interacts with a system. How best to consider and coordinate system and behavior factors in order to promote an optimal behavior by the user, however, is no easy task.

“I suppose you can see it as a chicken or the egg problem - what comes first? The system or the user's behavior on the system? Sometimes the system design just stops because it is seen as a linear process - first design, next implement, then operate,” Zhang explains.

“But I think we need to look at it in a different way. We need to close the loop. We need to see it as a cyclical, continuous loop.”

Zhang looks specifically at two systems to explore this user-centric idea - the transportation system and the energy system.

In a transportation system, users face an array of choices such as buses, trains, and lightrail, as well as shared bikes and scooters, rideshare, and carshare.

Each option influences not only the user experience, but also the design and performance of the system itself. The geographic location, availability, and usability all shape user decisions.

“We are looking at how we can coordinate all of these available modes so people benefit most from the system as a whole. We need to consider where shared mobility is located because that will also impact the way a user will choose a mode preference. If a user can’t find a carshare option then they won’t use it. Only relevant options then become available, and this behavior then influences the design of the system.”

The energy system reveals a similar relationship. With smart devices, flexible contracts, and variable pricing, electricity use is no longer a one-way interaction. Demand patterns shape system operations, and system incentives in turn shape user demand.

“A company can adjust demand to meet the needs of what they predict the user will use based on the time of year or past data. Or they can influence the way a consumer uses the system such as through contracts that charge more when the demand is higher thus resulting in less demand.But this all comes with a delicate balance of predicting convenience and flexibility. Human behavior is not always predictable, and a user-centric design must allow for that ambiguity.”

For Zhang and her fellow researchers, ISyE PhD students Yin Can, Zijian Wang, and ISyE Professor William Cooper - the challenge of finding a model that is complex enough to capture the interdependence of the system, but not be so complex that it becomes unsolvable is ever present. If the method is too complex and the model may not fit into the reality of the situation. If it is too specific, every system that is analyzed for interdependence would require that they start from the beginning every time.

“Deciding which type of model to use is important so that dynamics are appropriate. How to describe a user's behavior, as well as other specific parameters such as how to use electricity, can change the complexity of the problems. The decision model must allow for ambiguity because we may not know the human behavior reaction completely; there has to still be room to understand those thresholds.”

In the hopes of acquiring feedback from practitioners in the transportation and energy sector, Zhang has found enjoyment in the complexities and challenges of transforming traditional models into new methodological solutions in order to optimize system design with the confederation of user dependency.

“This work is all about creating a positive impact on services and resources available to consumers and companies in a positive way.”

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INDUSTRIAL AND SYSTEMS ENGINEERING

OPTIMIZING WHAT WE REVEAL: INFORMATION DESIGN IN OPERATIONS ISyE Associate Professor Krishnamurthy Iyer studies how platforms and service systems can share the right information to improve decisions, performance, and welfare.

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INDUSTRIAL AND SYSTEMS ENGINEERING

Information is a resource, and companies and social service systems use this resource to support user and consumer decision-making. ISyE Associate Professor Krishnamurthy Iyer studies how to share information in ways that improve overall welfare and outcomes.

In brick-and-mortar stores, consumers make decisions based on what they can physically see—quality, quantity, and other visible cues. Online platforms, by contrast—ridesharing, e-commerce, and even hospital systems—can decide how much information to reveal and how to present it. Signals such as whether an item is a “best seller” or “top choice,” or estimates of wait times for a service, can meaningfully shape the decisions users make.

“Online platforms control and consciously reveal what information they want their users to see, and this information is often all users have to rely on to make an active decision,” Iyer explains.

Wait time information, for instance, can be communicated in different ways: a point estimate, a range, or more abstract “signals” such as low versus high congestion. The format affects how users respond. At the same time, the information must remain truthful; otherwise, users will notice inconsistencies over time and adjust their behavior accordingly.

Many hospital systems, for example, have implemented dashboards that show patients potential wait times, helping them decide which care center to visit and when.

“Without such a dashboard in place, people decide on their own, and they may over-subscribe to services, which makes wait times increase. Through a dashboard, a hospital can provide information to influence behavior so people with less urgent needs can find an alternative location or choose to arrive at a less busy time. This can curb load on the hospital system, improving welfare for the hospital staff and patients.”

By combining theoretical tools from queueing theory, game theory, and economics, Iyer aims to characterize the “right” amount of information to provide in different operational settings.

“Game theory is one of my main research interests, and this particular research question is a practically informed application of game theoretic modeling. The challenge is that the novel models we create have to be realistic, and at the same time not overly complicated to allow for analysis.”

How does the information provided influence user behavior, particularly in service-system settings? And how much information is too much—or too little?

To study these questions, Iyer develops new models that capture realistic aspects of these systems. These include structural constraints on how information is shared (centralized vs. decentralized), as well as limitations on what is known and what is learned over time. And because people often deviate from perfectly rational decision-making, his models also account for behaviors such as ambiguity aversion.

As society continues to shift toward virtual-first platforms, decisions about what information to share —about product availability, service quality, or wait times—can influence both individual behavior and broader outcomes like system performance, welfare, and satisfaction.

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INDUSTRIAL AND SYSTEMS ENGINEERING

SCALING UP THE CARSHARING COMMUNITY As demand for carsharing grows in the Twin Cities, ISyE professor Martín Zubeldía partners with professors from the University of Michigan to help a local non-profit scale up everyday transportation to help the community.

PHOTO CREDIT: HOURCAR

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INDUSTRIAL AND SYSTEMS ENGINEERING

In an interdisciplinary, multi-institution team, ISyE Assistant Professor Martín Zubeldía is collaborating with professors from the University of Michigan, as well as the Minneapolis-based carsharing company HOURCAR. The team, led by University of Michigan Professor (and previous ISyE Department Head) Dr. Saif Benjaafar, also includes Dr. Elisabeth Gerber and Dr. Yafeng Yin to improve the EV Spot Network for HOURCAR.

demand is, and where they should expand,” Zubeldía explains.

According to the company’s website, HOURCAR is a Twin Cities-based non-profit organization that “connects people to their communities with convenient, equitable, and sustainable multimodal transportation,” and with its EV Spot Network, HOURCAR provides “an all-electric, one-way, freefloating carshare service with over 170 shared vehicles making the air cleaner, the community closer, and the future even brighter.”

“These tools will help the company better determine where demand is, analyze loss of revenue, and provide feedback on where to expand, and how and when to move cars via incentive schemes. We are being very specific with variables, as well - geographical area and event considerations, as well as the impacts of different days and times.”

Together with Dr. Benjaafar, Zubeldía is leading modeling and data analysis for the project. With the assistance of ISyE PhD student Yishun Luo, the team is creating software tools that better model demand estimation based on real data and current policy considerations provided by HOURCAR.

Though the team has been collaborating on this project since 2023, it is the recipient of the 2025 National Science Foundation (NSF) CIVIC Innovation Challenge grant, which is awarded to projects that focus on innovative research and practical applications that directly impact and prioritize community and civil engagement.

The team’s project, “Data-Driven Analytics for Scaling Up Community Carshare: Bringing Affordable, Reliable, and Clean Carshare to More People”, focuses on HOURCAR’s estimated growth and its impact on 5 fundamental questions: What drives the demand for community carshare?

How should a community carshare go about balancing the needs for efficiency, access, and affordability?

What are the features of incentives that are effective in inducing greater carshare usage and mitigating the spatial and temporal mismatch between vehicle supply and demand?

Can community carsharing be effective in extending the reach of public transit?

What tradeoffs should be considered in making investments in fleet size versus charging infrastructure?

With the growing interest in carsharing as a form of transportation, the team believes there will be a positive impact on the current HOURCAR system as it prepares for significant growth. If successful, the outcomes of the project will prove to be cost-effective and extend the reach of public transportation, which greatly impacts users and the Minneapolis/St. Paul community. It also has the potential to serve as a blueprint for other cities that are looking to build stronger connections between resources, services, and the needs of their communities.

With plans to significantly grow over the next three years, HOURCAR is preparing for the road ahead.

“With the company's growth, Evies have an added challenge that they need to be charged and charging takes time. That brings extra logistics and infrastructure. We are helping them with developing statistical tools to better understand where the

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PHILOSOPHY IN ENGINEERING “It is human nature to look for better alternatives even after the problem is seemingly officially solved already. That nature of seeking never-ending improvements is the driving force to science and engineering. Without that, there would be no innovation. As researchers, we better understand the driving force underpinning all we do.”

Since the early 90s, ISyE Professor Shuzhong Zhang has found passion in the field of Optimization, and his research has evolved with the ever-changing landscape. He watched and became a part of the story of the growing field of optimization as he saw the advent of new and exciting models come to the forefront of research practices. And with new research landscapes on the horizon (such as quantum computing, which may change the field completely), Zhang is preparing to adapt accordingly, or perhaps even see existing tools become obsolete.

“In a time when I started my career, an optimization model with a few hundred variables was reasonable, and a few thousand was big. Now, there are billions and trillions of variables. Times have changed, especially with the growing interest in Artificial Intelligence. You have to adapt because the problem is different now. However, there are unchanging principles in a changing world. The challenge for a researcher is to understand the unchanging while adapting to an ever changing environment.”

Zhang is currently focusing his research on design algorithms to solve optimization models efficiently, as well as computing equilibrium solutions. For Zhang, these sorts of problems exist everywhere and all the time.

In collaboration with ISyE Professor Kevin Leder, for example, Zhang is working to optimize cancer treatment by observing and modeling how cancer cells respond and react to various treatment types, styles, and systems.

He is also working with researchers in the biomedical field to develop algorithms that help to more clearly identify which human protein-producing genes are

responsible for what particular diseases.

“We are working to connect dots and observe associations between expressions of genes and disease, and understand what genes are important for what diseases. We also have to filter out the noise of other gene markers to make sure we find the gene or genes that are actually responsible for the disease,” Zhang explains.

Though his focuses are technical and are about fine tuning parameters in order for the system to behave the way it was intended, he sees the true nature of his work as one that reflects his values. Thus, in all of years in academia, Zhang reflects that one aspect of his research has never changed – the human aspect.

“My research topics have changed a lot. But many things haven’t really changed at all. My tastes for research problems - what is interesting, important, and what reflects my values - that haven’t changed. To look for the right problems and ask the right questions, that is the most important quality in a researcher. It goes beyond technical strengths or

beyond being able to do complicated technical computations - not that those aren’t important - but these are less so than the quality and passion for what we do as researchers. After all, researchers define the meaning of research.”

Zhang’s empathetic approach to research and fellow researchers has always been a priority. Through his years as a researcher he has learned more about its impact on him, as well as on the academic departments where he had served. He explains that the researcher brings value to the research, and his time in academia has taught him to look deeper at the person behind the research.

“You shouldn't fully look at the outcome of someone’s work at face value - how many papers have they published or how many awards they have received. This can be misleading. In my opinion, the success of a researcher has to do with their drive and their tastes. Throughout my career I have learned to be able to tell someone’s quality beyond the paper value. By talking to and working with people, I have come to understand people. And for an academic unit to be successful, leaders must work with people, understand people, appreciate people, and be able to know someone’s quality before it has become apparent to all.”

As Zhang continues teaching, researching, and learning he is excited to be surprised of what the future holds for him.

“What I work on next has to be a meaningful project and meaningful insight has to be gained. I know many people in academia are driven by fame or success, but I don’t have that need. I value working with good people where we can collaborate on interesting problems, lift people up and be lifted up. I want to continue to look at the problems that are crucial for society.”

Though he loves to work with his math and computing background to improve and prove theorems and bounds, Zhang will continue to dream of problems that go beyond what can fit in research proposals.

“To me philosophical dreaming is important, as I will always have an interest and motivation in humanity. Can we see the big picture of changes coming our way? What are the reasons and what are beyond reasoning? If we take away the philosophical nature of research, then our intelligence probably won't stand a chance with artificial intelligence!”

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DEPARTMENT OUTREACH

A VISION IN QUALITY Since his arrival to the department in fall 2024, ISyE Assistant Professor Shancong Mou has continued to impress with his work and collaborative efforts that make an impact on his field of research, as well as the department.

One such example took place in Honolulu, Hawaii in October 2025 - the 3rd workshop on Vision-based InduStrial InspectiON (VISION’25), which is co-hosted with the International Conference on Computer Vision (ICCV).

With previous workshops taking place in Vancouver, Canada and Milan, Italy, the workshop website explains that the workshop is designed and organized to “provide a platform for the exchange of scholarly innovations and emerging practical challenges in Vision-based Industrial Inspection. . . . this workshop aims to bring together researchers from the interdisciplinary research communities related to computer vision-based inspection; and connect researchers and industry practitioners to synergize recent research progress and current needs in industrial practice.”

Mou not only serves as Chair and organizer of the VISION’25 workshop, but is also its co-founder for the VISION workshop series.

“It all started when I was still in graduate school.

Through an industry collaboration between Apple and my advisor’s lab, we realized there was very limited communication between industry and academia around this research area. We felt that a workshop could help bridge this gap. At the time, I was just a grad student working on this topic, and, encouraged by my advisor Prof. Shi and Dr. Meng Cao from Apple, I worked with several Apple researchers and Prof. Shi to co-organize the first workshop.” Mou reflects.

He continues to see a need for collaboration between

industry and academia, so to have the workshop take place every year, Mou works with his fellow organizers to coordinate the paper review process and content of the workshop.

Since the advent of this conference, Mou has had greater opportunities to share his work, as well as grow his network. However, “volunteering to build a platform for a space where researchers and industry can come together is really important and rewarding,” he explains.

Workshop Keynote presenters include researchers from Texas A&M, Hong Kong University of Science and Technology, Apple, Roboflow, and Medtronic.

Additionally, a panel discussion, submitted paper talks, and a poster session all provide a wide range of ideas and research presented by established companies and startups, and various academic institutions.

“My research is related to industrial AI, and I am highly motivated by these real problems. It is also a great opportunity to meet industry professionals and learn about the important problems that they have and care about to the broader research community.”

Mou has continued to make a great impact on the department through his consistent outreach, but he has also found great reward as the Chair and cofounder of VISION.

A CONTINUOUS IMPACT: ISYE HOSTS MIP 2025 With 130 registered participants, including 56 students, coming from four continents and 13 countries, ISyE at the University of Minnesota Twin Cities hosted its third conference during the 2024-2025 year. The 2025 Mixed Integer Programming Workshop (MIP 2025) was held June 2–6, 2025, marking its return to Minneapolis after twenty years.

algorithms and techniques.”

MIP 2025 featured a single track of 19 invited experts representing academia, national laboratory, and industry research, and covered a broad range of recent advances from theoretical, computational, and applied topics. Additionally, this impactful workshop featured a summer school preceding the main event; the traditional student poster session; a special session for the 4th edition of the MIP computational competition; and contributed flash talks.

“The conference was created and always meant to be a forum where young researchers would have a place to present their research and help shape the community.

Presenters and committees are predominantly early career professors or researchers who are starting out in the discipline, so they gain exposure and have a direct impact on future direction of the community,” Richard reflects.

Mixed Integer Programming (MIP) is a class of mathematical optimization problems that involve finding a solution that minimizes costs or maximizes efficiency subject to constraints, where the decision variables include a mixture of continuous values and integer-restricted values.

“MIP is important in a number of real-world applications where you have to make a decision of whether to do or not do something,” explains Jean-Philippe Richard, local committee chair and ISyE professor.

“When you make decisions about certain things like building a plant or serving a customer, those decisions are not fractions; they are inherently discrete – you you either do it or you don’t do it. You want the variables to only come out as an integer. MIP is all about solving these types of decision problems better with special

The workshop was held under the auspices of the Mixed Integer Programming Society, a section of the Mathematical Optimization Society (MOS) that promotes continuity of the MIP community and events within it.

Richard explains that ISyE at the University of Minnesota was chosen to host the 2025 conference because of its welcoming community and the distinguished reputation the department has in the field of Optimization, and the department was excited by the opportunity.

“ISyE was honored to host this international group of researchers, using the opportunity to showcase the intellectual vibrancy of our department and the beauty of our campus.”

MIP 2025 was kept affordable with the support of academic, industry, and federal sponsors that are listed on our website, including grants for student travel expenses from the National Science Foundation, Air Force Office of Scientific Research, and Office of Naval Research. MIP 2025 was a great success for the MIP Society, attendees, and the department.

STUDENT SUCCESS STORIES

SNOWBALLING INNOVATION: IISE AT THE UNIVERSITY OF MINNESOTA TWIN CITIES The Institute of Industrial and Systems Engineers (IISE) at the University of Minnesota Twin Cities, a Campus Life Program supported

by ISyE, is a student-led community that provides ISyE undergraduates with professional and academic development opportunities.

Through technical workshops, networking experiences, and industry events, students connect with leaders to create a collaborative culture of growth and real-world insight.

The chapter is excited to host the North Central IISE Regional Conference in Minneapolis in 2027 under the theme Snowballing Innovation.

The conference will host peer organizations from 17 top engineering schools for a twoday program of site visits, hands-on workshops, networking, and professional development. The conference anticipates about 120 attendees – a mix of underclassmen seeking internships and seniors preparing for full-time roles – creating a concentrated talent pipeline and a regional forum for sharing modern ISyE practice. For students, alumni, faculty, families and the ISyE department, the conference is a defining moment to showcase the University of Minnesota's strengths in applied analytics, operations, and human-centered engineering while building lasting relationships across the Midwest ISyE community.

Sponsorship is the catalyst that turns this vision into a high-impact experience for everyone involved. Companies gain meaningful visibility and access to emerging engineers through options such as a headlining information session, a seat on a Q&A panel, a curated resumé book, case-competition promotion, facility tours near campus, and networking during the event. Sponsorship also supports a tax-deductible educational event, which allows IISE to invest in richer programming and reduce participation barriers for all anticipated student attendees.

IISE functions as a University talent engine and relationship bridge. IISE programs and the 2027 Regional Conference convert learning into internships and roles, deepen employer partnerships through sponsored workshops and tours, and showcase the University and Department’s strengths to peer schools and industry.

When IISE grows, the University’s impact grows in reputation, readiness, and results.

Learn more about the conference and sponsorship opportunities at z.umn.edu/IISE_2027 or scan the QR Code.

THE WARMTH OF A DEPARTMENT: A STUDENT PERSPECTIVE

By Ting-Tsen Lin, ISyE PhD Student

“You’re in Minnesota? It must be very cold there!”

“Yes, very cold. The coldest day I’ve experienced so far was -29°C.” This is probably the question I’ve been asked the most since coming to the U.S. Coldness seems to have become Minnesota’s trademark. Yet, in this place where it snows for nearly half the year, I’ve come to experience support and warmth.

I joined the ISyE PhD program in Fall 2023. Before that, I completed my undergraduate and master degrees in mathematics, and my research focused on optimization theory. I was drawn to ISyE because it has strong theoretical research and uses mathematical tools to address real-world problems. What ultimately made me choose ISyE, though, was the atmosphere I felt during the interview process. Faculty mentioned that the department had just moved into a shared space that makes it easy for people to see each other and talk. I also spoke with senior students and felt the department is very supportive. For me, doing a PhD is not only about the research topic; it is also about being in a place where people are willing to talk, exchange ideas, and grow together.

My research focuses on organ transplantation systems. I currently work with two faculty members. With Professor Saumya Sinha, I study how novel organ preservation technologies affect the overall transplant system. Our work begins with building mathematical models and then using them to understand system behavior and trade-offs.

Coming from a mathematics background, I tended to focus on the model’s structure and solvability. In this project, however, Sinha has consistently brought our discussions back to a fundamental question: what insight can we extract from the model? At one point I had a long list of stakeholder questions I hoped the model could address.

Professor Sinha encouraged me to step back and ask what those questions had in common and what core aspects of the system we were really trying to understand. Through this process, I began to adjust how I think about modeling, and started to see models not only as objects to be formulated and analyzed, but also as tools for thinking about how the system works.

And to think it all began at a department pizza party at the beginning of my second semester. The event was casual; people walked around with pizza and chatted in groups. I asked her what research directions she was planning to explore next. She mentioned several ideas and said she was looking for students to work with. I took the chance to introduce myself and told her I was interested in her work. Instead of asking me to commit to a large project right away, she suggested we start by reading papers together and gradually develop a research topic from there.

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My collaborations didn’t stop there. Working with Professor Nick Arnosti and my classmate Zijian Wang has shaped my thinking from another angle. Together, we study a dynamic patient-matching problem. The project began in Professor Arnosti’s class, “Engineering the Allocation of Public Resources,” and later developed into a formal research project. At first, we focused on mathematical generalizations, such as relaxing assumptions and checking whether results still hold. Through discussions with Arnosti, I started to see how these results could be interpreted as policy implications, such as how different allocation rules might affect patients’ welfare. This experience has helped me connect theoretical analysis with questions that matter for real-world allocation systems.

Together these projects have helped me connect my theoretical background with practical questions and develop a broader perspective on how operations research can inform real-world systems.

Looking back, my experiences in ISyE reflect what I appreciate most about the department: students are given opportunities to grow, and they are supported while doing so. Professors are always open to discussing research ideas, and students naturally share experiences and resources with each other. This makes the environment warm and supportive.

When people think of Minnesota, the first thing that comes to mind is usually “cold,” but during my time in ISyE, what I’ve felt more often is “warm.” Whether it’s professors’ patience during research discussions, classmates learning and exploring together, the laughter at Wednesday Tea Times, or the enthusiasm everyone shows in organizing events, these are the things that have added warmth to my ISyE journey.

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OPTIMIZING STUDENT SUCCESS “We are pleased to announce that your paper, “Natural Hypergradient Decent: Algorithm Design, Convergence Analysis and Parallel Implementation,” has been selected for the finalist of INFORMS Quality, Statistics, and Reliability (QSR) Best Student Paper Award, and the final competition will take place at the INFORMS Annual Meeting, where finalists will present their papers at the "QSR Best Student Paper Competition" session.

ISyE 3rd-year PhD student Deyi Kong received this exciting news in September 2025—for her first research paper, and her first time attending the INFORMS conference.

Out of 39 submissions for the Best Student Paper Award, and a rigorous double-blinded review process, Kong became one of four finalists to be selected for the award. Her paper was chosen alongside the other finalists from Massachusetts Institute of Technology, Georgia Tech, and University of Washington.

As a finalist, Kong explains that “a student paper has to have good insight and innovation. The idea of the paper must be relevant, meaningful, and have a practical impact on QSR applications. The work should have innovative ideas, theoretical justification and experimental research that proves what was developed actually works.”

Kong’s paper, written with assistance from her advisor Professor Shancong Mou, focuses on the development of an algorithm for unconstrained bi-level optimization, with the inner problem focusing on large scale learning problems. This algorithm can be applied to many industrial settings.

This problem appears in many engineering and machine learning applications,” Kong says. “In manufacturing, for example, we often want to perform automatic inspection of products. However, we may not have enough real data to train a supervised model, so synthetic data generation has become a popular way to mitigate this issue. But how do we evaluate the quality of the synthetic data? This algorithm can be used to qualify the dataset so that we can move forward with the manufacturing process more effectively.”

The INFORMS Annual Meeting, which took place from October 26-29, 2025 in Atlanta, Georgia, was where Kong presented her work in front of her fellow finalists and judges, as well as other attendees. This presentation, which was the competition for all of the finalists, was roughly 17 minutes long. The presentation was followed by a Q&A session from attendees and judges.

Though Kong did not win the award, she is extremely proud of the work she has done, as well as deeply grateful to Professor Mou, Professor Zaiwei Chen (Edwardson School of Industrial Engineering, Purdue University) and Professor Shuzhong Zhang.

“They gave me guidance and advice throughout this process, which contributed to making this finalist recognition possible. I also feel very fortunate to learn from them.”

THE RETURN OF INFORMS AT THE UNIVERSITY OF MINNESOTA TWIN CITIES Graduate students of the Department of Industrial and Systems Engineering, along with Assistant Professor Martin Zubeldia and Graduate Program Coordinator Autumn Church, are working to revive the Institute for Operations Research and the Management Sciences (INFORMS) student chapter at the University of Minnesota Twin Cities.

By uniting students across engineering, data science, and business, the INFORMS student chapter at the University of Minnesota Twin Cities will strengthen the University's role as a leader in analytics and decision science education. Equally, the impact of revitalizing such an impactful student chapter will help bring the Department to the forefront of innovation and collaboration.

This Campus Life Program links University students to the global operations research and analytics community, and creates opportunities for research collaboration and professional development. For ISyE students, it is a platform to share ideas, develop leadership, and engage with a broader community focused on optimizing real-world systems.

If you are interested in learning more about the chapter, or wish to sponsor, mentor, or present under the INFORMS student chapter at the University of Minnesota Twin Cities, please email the group at informs@umn.edu.

The University of Minnesota Twin Cities program is affiliated with the global organization, INFORMS, the world’s largest professional association for analytics, operations research, and management science. Its members apply data, models, and computing to improve decisions in areas like healthcare, transportation, supply chains, finance, and sustainability. INFORMS brings together academics and practitioners to turn analysis into better decisions.

"INFORMS is a community where we learn, lead, and build solutions that matter."

As program leaders finalize the chapter relaunch, events and collaborations are already underway. With a focus on growing the chapter, the Chair and Vice Chair (ISyE PhD students Ting-Tsen Lin and Yishun Luo) are preparing academic programming, including faculty talks, student research spotlights, and practitioner panels, along with social events designed to connect students, researchers, and industry.

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A PLACE THAT FEELS LIKE HOME Graduating in March 2026 with her MS in Data Science in Operations Research (formally the MS in ISyE, Analytics track), ISyE student Yazhou Li knows her hard work and the department’s guidance have prepared her for the road ahead.

Receiving her undergraduate degree in Statistics in 2024 from East China Normal University, Li was drawn to the University of Minnesota and the ISyE program.

“I wanted to change my field of study from statistics to another field. At the time, I was interning at a manufacturing company, and that is where I learned about industrial engineering. I decided that was something I wanted to pursue, so I searched for universities with the best engineering program. The University of Minnesota was on that list.”

Her search showed her that ISyE offered unique coursework and provided a workload that not only respected her time, but also enhanced her academic interests.

“The required courses seemed interesting and rigorous, but I could also choose additional courses such as computer science and business analytics to help me learn more technical skills. I also would get more hands-on experience and practical application from the courses.”

As many ISyE students come to learn, however, the department is more than its coursework.

“When I got the offer, I reached out to current PhD students to learn more about the program. They were kind and introduced to me what the department atmosphere was like. I loved it!”

She knows she is graduating with good skills in optimization and predictive analysis, as well as in the additional courses she could take because of the program flexibility. In addition, her Capstone Project has given her the opportunity to work directly with a company to gain even better hands-on experience. She explains that her Capstone company sponsor, Daikin Applied, has been incredibly supportive, and the experience has equipped her to be successful.

She also remarks that the College of Science and Engineering’s Career Services has made a tremendous impact on her time at the University.

“They help me connect with ISyE alumni who helped with revising my resume and providing other suggestions, as well as practicing interviewing skills. I have also built connections with those alumni so they can help me find additional open positions.”

She will always value the connections she has made, and exclusively thanks ISyE professors Krishnamurthy Iyer and Shancong Mou have been especially kind, supportive, responsive, and helpful in her coursework.

“They really care about my future and my success.”

As Li completes her degree, as well as her data analytics internship with Symetra Insurance, she has been actively applying and interviewing for a permanent position in data analytics in Minnesota, a place that feels like home.

ALUMNI RELFECTIONS

These two courses really were my first taste of that world. I fell in love with optimization and simulation because I think those are two extremely powerful mathematical tools that are kind of opposites of each other, but are the bread and butter of operations research.”

FOLLOWING THE EXCITING PROBLEMS As a member of the second graduating class of ISyE undergraduates in 2016, ISyE alumnus Alex Stroh recalls the impact that ISyE had that helped him become the person he is today, both personally and professionally.

Along with Optimization and Simulation, ISyE gave Stroh the exposure to various fields of studies because of the flexibility of electives and the projects that were assigned to him during his undergraduate years.

Courses such as Engineering Economics, Project Management, and the Senior Design project would teach Stroh about delivery logistics, optimization tools, simulation tools, project management tools, and business intelligence.

“I started at the University of Minnesota in 2012. I knew I wanted to do something math related, but was uncertain on what career path to take, but I knew I didn't want to do traditional engineering. I learned about industrial engineering for the first time at 19 years old when I was a freshman when I met ISYE professors Lisa Miller and John Carlsson. I wanted to maintain a higher level of math, so I ended up double majoring in ISyE and mathematics.”

He would also have three internship experiences during his time in the undergraduate program, as well as an opportunity to research with two ISyE faculty members.

These opportunities helped him gain additional real world experience, but more importantly, motivated him to pursue a graduate degree.

With the rigor of the double major, Stroh was introduced to the field of study called operations research. Two ISyE courses would provide a great impact on his understanding of operations research and his future in academia - Optimization and Simulation.

Stroh would follow in the footsteps of two of his influential ISyE professors, William Cooper and Lisa Miller. He would go on to obtain a Master of Science in Statistics and a PhD in Operations Research from Georgia Institute of Technology.

Stroh now finds himself at Target Corporation as a Lead Operations Research Scientist, and primarily works in designing strategic delivery networks for Target’s nextday delivery programs.

It all began, however, in ISyE. “ISyE is the foundation. I love my job every single day and I’m energized by it. I'm proud of the work I'm able to do at Target. I followed the problems that excited me and the people who energized me. It’s how I found myself in ISyE to begin with, and how I have found myself to be where I am now.”

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INDUSTRIAL AND SYSTEMS ENGINEERING

MOMENTS THAT LAST A LIFETIME Many undergraduate ISyE students enroll in the Integrated Degree Program (IDP). This 5-year program gives students the opportunity to obtain their Bachelor’s in ISyE, as well as their Masters of Science in Data Science in Operations Research (DSOR) (formally the MS in ISyE, Analytics track).

during the senior design project where I thought ‘Oh, that’s what Professor Miller meant. That’s why we need that!’.”

These moments and realizations now seep into her everyday career, and will continue to stick with her as she moves through industry.

Jessica Thorne is one such student. Graduating in December 2024, Thorne now works as an Analyst for Accenture, a global business and technology consulting firm. As an Analyst, Thorne works in a variety of capacities. One of these is project management where she prepares and facilitates meetings with her clients.

She also works within the Enterprise Resource Program (ERP), and most recently has been involved with testing security and integration points within the system.

Originally a Mechanical Engineering major, Thorne switched to ISyE because of its mix of math and process focus. The continued desire to expand that connection led her to the Master program.

“The truth is, I stumbled upon ISyE, and it worked out! It was a great experience! The undergraduate program skills can be applied to most industries. There is also a lot of flexibility with what class you can take in the MS program. The capstone project helped expand my project management and communication skills, and it was exciting to produce a product in the end.”

Her work with Accenture began as an internship during the Junior year of her undergraduate studies. This internship opportunity continued through 3 of the 5 years of her time in ISyE.

Through the expansion of her math, operations and process management, and technical skills, as well as the formed connections with peers and professors, the ISyE programs provided the technical critical thinking and supportive autonomy needed to participate in the world outside of academia.

“With each internship I did with Accenture I was on a different client account. The first internship allowed me to work with and learn more about coding and server infrastructure. The second, which was with a food manufacturer, focused more on process and industrial engineering. The last internship applied much more of the project management piece and Enterprise Resource Program implementation, which is most related to what I work on now.”

“I learned how to get to the truth of a project, and this department actually cared about me. It all makes a difference, it really does.”

Beyond the value of her internships, the ISyE programs provided many enlightening moments that led her to settle into the Analyst position; however, those moments did not seem clear until the undergraduate senior design project.

“We take all these classes that give us building blocks to prepare us for the time when we can actually talk to people at the plant and start to understand their specific process. I saw where ISyE fit into these spaces, but it was mostly theoretical. But there was a moment

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CONFERENCE PRESENTATIONS

Dr. Kathryn Wust

Michael Olabode, ISyE PhD Student

Healthcare Ergonomics and Patient Safety Conference - Dublin, Ireland June 2025 “Older Adults and ED Nurses’ Perception of Work System Barriers and Facilitators to Collaboration Through Perspective Taking”

2025 INFORMS Annual Meeting - Atlanta, GA October 2025 “Evaluating the Effectiveness of OPTN Regulation in Organ Transplantation”

Yishun Luo, ISyE PhD Student INFORMS Applied Probability Society Conference - Atlanta, GA June 2025 “Stability and Heavy-Traffic Delay Optimality of General Load Balancing Policies in Heterogeneous Service Systems”

Dr. Saumya Sinha 2024 INFORMS Annual Meeting - Seattle, WA October 2024 “Pay-for-Performance Incentives in Organ Transplantation” Discrete Optimization Talks - Virtual April 2025 “Lagrangian Relaxation and Duality for Multiobjective Integer Programming”

Ting-Tsen Lin, ISyE PhD Student 2025 INFORMS Annual Meeting - Atlanta, GA October 2025 “Evaluating the Impact of Novel Organ Preservation Technologies on Transplant Access”

Dr. Martin Zubeldia 2025 INFORMS Applied Probability Society Conference - Atlanta, GA July 2025 “Concentration of Stochastic Approximation Under Heavy-Tailed Markovian Noise”

Nhi Ngyuen, ISyE PhD Student 2025 INFORMS Annual Meeting - Atlanta, GA October 2025 “Inverse Optimization in Finite-State Semi-Markov Decision Processes”

IFIP Performance 2025 - Amsterdam, Netherlands November 2025 “Heavy-traffic Optimality of Skip-theLongest-Queues in Heterogeneous Service Systems”

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INDUSTRIAL AND SYSTEMS ENGINEERING

PUBLICATIONS Tongqing Chen and William L. Cooper, “Pricing a Product with Network Effects For Sale to a Fixed Population of Customers.”Naval Research Logistics, 2025.

S. Mou, R. Vemulapalli, S. Li, Y. Liu, C. Thomas, M. Cao, H. Bai, O. Tuzel, P. Huang, J. Shan, and J. Shi, “Synth4SegLearning Defect Data Synthesis for Defect Segmentation Using Bi-level Optimization.” IEEE Transactions on Automation Science and Engineering, 2025.

Krishnamurthy Iyer, Alec Sun, Haifeng Xu, and You Zu, “How to Sell a Service with Uncertain Outcomes.” 26th ACM Conference on Economics and Computation (EC), 2025.

Zaiwei Chen, Siva Theja Maguluri, and Martin Zubeldia, “Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise.” The Annals of Applied Probability, 2025.

Daan Rutten, Martin Zubeldia, and Debankur Mukherjee, “Distributed Speed Scaling in Large-Scale Service Systems.”

Operations Research, 2025.

Prakirt Jhunjhunwala, Martin Zubeldia, and Siva Theja Maguluri, “Join-the-Shortest Queue with Abandonment: Critically Loaded and Heavily Overloaded Regimes.” Mathematics of Operations Research, 2025.

Martin Zubeldia, Prakirt Jhunjhunwala, and Siva Theja Maguluri, “Matching Queues with Abandonments in Quantum Switches: Stability and Throughput Analysis.” Operations Research, 2025.

Sajad Khodadadian and Martin Zubeldia, “A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging.” NeurIPS Conference, 2025.

Yishun Luo and Martin Zubeldia, “Heavy-traffic Optimality of Skip-the-Longest-Queues in Heterogeneous Service Systems.” IFIP Performance Conference, 2025.

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INDUSTRIAL AND SYSTEMS ENGINEERING

AWARDS & GRANTS Dr. Shancong Mou

Dr. Martin Zubeldia

Sigma Xi Best Thesis Award Georgia Institute of Technology One of 10 recipients selected universitywide across all PhD disciplines that year.

CIVIC Innovation Challenge Grant NSF Total Funding: $700,000 The proposed research-centered pilot will support the deployment of datadriven analytics to improve the efficiency, availability, and affordability of the largest community carshare service in the nation and the development of fundamental knowledge about the science and engineering of community carshare.

Best Student Paper Award Physical and Engineering Sciences (SPES) and Quality and Productivity (Q&P) Section, American Statistical Association (ASA) "Physics-Informed Neural ODE with Heterogeneous Control Inputs (PINOHI) for Quality Prediction of Composite Adhesive Joints", by Yifeng Wang, Shancong Mou, Chuck Zhang and Jianjun Shi, published on IISE Transactions.

Dr. Kevin Leder Division of Mathematical Sciences Grant NSF Total Funding: $250,000 In this project, the investigators will develop new mathematical and statistical tools to analyze the large amounts of data generated by new sequencing technologies. These tools will help scientists understand the principles driving cancer progression and treatment response.

Deyi Kong, ISyE PhD Student Best Student Paper Award Finalist Quality, Statistics and Reliability Section, INFORMS "Natural Hypergradient Descent: Algorithm Design, Convergence Analysis and Parallel Implementation", by Deyi Kong, Zaiwei Chen, Shuzhong Zhang and Shancong Mou.

DONOR SPOTLIGHTS

(MARCH 2025-AUGUST 2025)

Up to $500 Target Danielle M. Abushanab Brent Kellum Bingnan L. Lu Bonnie Baumgartner Emma Ehling

Megan Bredehorst Sarah Kendrick Michelle Huang Ethan Del Sol Betty T. Huynh Pallavi Singhal Katie Erdmann

24

INDUSTRIAL AND SYSTEMS ENGINEERING

FALL 2024 & SPRING 2025 SEMINAR TALKS FALL 2024

SPRING 2025

September 18 Alberto Del Pia, University of Wisconsin, Madison "Minimizing Quadratics Over Integers"

February 19 Johann Gaebler, Harvard University "A Simple, Statistically Robust Test of Discrimination"

September 25 Erik Erickson, Hennepin County "Leveraging Data for the Public Good: Analytics at Hennepin County" October 2 Nicole Nelson, Abercrombie & Fitch Co. "Twenty Years of Data-driven Decision Making in Retail: Capabilities, Changes and Realities" October 9 Minshuo Chen, Northwestern University "Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data" October 16 Mor Harchol-Balter, Carnegie Mellon University "Queueing Solutions for Today's Data Center Jobs" October 30 Carol Parendo, Collins Aerospace "Ensuring Quality Products with Data" November 6 Peter Zhang, Carnegie Mellon University "Approximating Multiple Robust Optimization Solutions in One Pass via Proximal Point Methods" November 13 Bartolomeo Stellato, Princeton University "Data-Driven Algorithm Design and Verification for Parametric Convex Optimization" November 20 Jon Snyder, Hennepin Healthcare Research Institute "The U.S. Organ Transplant System: Taking a Systems Engineering Approach" December 4 Vahideh Manshadi, Yale University "Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement"

February 26 Zhengyuan Zhou, New York University "Optimal No-Regret Learning in Repeated First-Price Auctions" March 5 Bjorn Berg, University of Minnesota "Learning Health Systems Research: An Industrial Engineering Perspective and Examples" March 19 Miguel Lejeune, George Washington University "Distributionally Robust Maximization of Ratio Exceedance Probability" April 2 Jing Dong, Columbia University "Stochastic Gradient Descent with Adaptive Data" April 9 Yunzong Xu, University of Illinois "Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation" April 16 Maged Dessouky, University of Southern California "Models for Facilitating Ridesharing" April 23 Uday Shanbhag, University of Michigan "Smoothing-enabled Zeroth-order Schemes for Stochastic Optimization Problems: Addressing Stochasticity, Nonsmoothness, Nonconvexity, and Hierarchy"

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