In Her Words: Professor Xin Guo, UC Berkeley IEOR’s New Chair, on Growth, Community and Discovery
In a wide-ranging Q&A, the new chair of UC Berkeley IEOR discusses leadership, the evolving role of IEOR in today’s rapidly evolving landscape, and the opportunities ahead for the UC Berkeley community
Q: What does leadership mean to you in an academic context, especially within a field as dynamic as industrial engineering and operations research?
For me, leadership is service. A chair needs to create the environment for others to thrive. Positivity is part of that, which means creating space, freedom and support, whether in teaching assignments, research resources or simply removing constraints, so that faculty can invest their time where they excel. Our faculty are extraordinary. My role is simply to make their lives easier so they can focus on impactful research and teaching.
Q: You’ve said Berkeley shaped not just your IEOR training, but your broader approach to interdisciplinary work. In what ways?
Positivity does not mean ignoring reality. In Chinese, the word for crisis, weiji, combines two characters: danger and opportunity, which coexist. Even when we face danger, we also have opportunities. That framework helps me stay grounded and look for what can be built, not just what may be lost.
Q: What have your first months as chair taught you about the IEOR community?
What impresses me most is the depth of support across the department. I have seen board members, faculty, and staff at all levels and even students, who actively look for ways to contribute. Conversations with staff and colleagues show a genuine collaborative spirit and a shared commitment to strengthening the department. That collective goodwill has been striking and has made the transition into this role especially meaningful.
Q: What are your priorities for IEOR during your tenure, and where do you see the department’s biggest opportunities?
This is an extraordinary moment for IEOR. The landscape of AI, data and computation is changing at unprecedented speed, and our discipline sits at the center of that transformation. Optimization, stochastic modeling, game theory, robotics, AI for health, supply chains and large-scale algorithm design are now deeply interconnected. That convergence gives us an opportunity to strengthen IEOR’s identity and highlight how foundational our field is to today’s technologies.
A central priority for me is growth. We are one of the smallest IEOR departments in the country, yet the demand for our expertise continues to accelerate. Our Master of Analytics program is thriving, and enrollments in optimization, data-focused courses and engineering AI subjects are consistently exceeding capacity. To meet these needs, we must increase the number of faculty, expand course offerings, and create more opportunities for collaboration across research areas.
Finally, we must secure a physical home that matches the excellence of our program. Our faculty are currently spread across several buildings, and this fragmentation limits our ability to build community, host visitors and support students. I have visited the Isaac Newton Institute and Oxford’s mathematical institutes, spaces that signal importance, support collaboration and inspire the next generation. IEOR needs a central, modern home that reflects the department’s growing influence and gives students and faculty a true sense of belonging.
Right now, our faculty and students work across several locations, which can make it harder to build the synergy and connections that enrich research and learning. Creating a more unified home for IEOR would support continued growth and give our community a shared space that reflects our energy, ambition and expanding impact.
Q: How can alumni and students support this vision?
Our alumni and advisory board already contribute tremendously to IEOR’s success. Their support goes well beyond financial resources, although those are essential for expanding space, hiring faculty and strengthening programs. Equally important is the advocacy and visibility they provide. When alumni speak about the quality of IEOR, connect us with industry leaders or help communicate our needs to campus leadership, those efforts make a real difference.
For students, support comes through engagement; sharing experiences, participating in departmental activities and staying connected after graduation. Their perspectives help us understand where we are strong and where we can grow. Their continued involvement signals the impact of an IEOR education.
This partnership, both seen and unseen, is essential as we enter our next phase of growth. It reinforces the collaborative spirit that defines IEOR and helps us move forward together.
Q: IEOR has long influenced machine learning and data science. How do today’s advances reshape IEOR’s role?
That interest emerged when I briefly returned to energy.
While working with the chief economist at the Federal Energy Regulatory Commission, I saw that even when models were elegant, human decisions often diverged from classical rationality. Heuristics, biases and judgment errors shaped outcomes.
When I joined Maryland, I worked with an economics postdoc to design behavioral experiments. It took years to publish our first paper, but it convinced me that you can’t fully understand markets without understanding how people actually make decisions. That lens now informs all my work.
Q: Some people see overlap between IEOR and data science. How do you distinguish them?
Data science focuses on understanding and modeling data. IEOR includes that scientific foundation, but it also brings an engineering perspective. We study how systems operate, how decisions are made and how to design algorithms that work reliably in complex, real-world environments.
Our faculty reflect that dual identity. We have researchers in robotics, stochastic control, optimization, supply chains, game theory and other areas at the intersection of modeling and implementation. Because IEOR spans both theory and engineering design, we can build the foundations and translate them into systems that scale. That breadth—science and engineering together—is what distinguishes IEOR.
Q: What research are you most excited about right now?
Several areas. One is reinforcement learning and multiagent reinforcement learning, which connect deeply to game theory. My collaborators and I developed a framework that translates complex dynamic, non-zero-sum games into more tractable control systems. Classical game theory has long understood zero-sum games, but general-sum games were far less manageable. This new approach opens possibilities in economics, engineering, robotics and resource allocation.
I also work on signature methods for nonstationary and anomalous data—tools rooted in topology and increasingly impactful in statistics and machine learning. They offer powerful ways to analyze irregular, nonstationary, and evolving data streams.
Another area I am passionate about is AI for health. Earlier work in cancer detection and eye disease diagnosis has expanded into medical record analysis, fraud detection and regulatory applications. The potential impact in healthcare is enormous.
I tend to shift research directions every few years. Lately, I am learning quantum computing simply because I do not yet understand it at all and would like to. Curiosity drives my research.
Q: What trends in IEOR research do you find most transformative?
AI’s impact on biological and medical sciences will be profound. New machine learning methods, especially generative models, allow us to identify patterns and unknowns that were previously inaccessible. This creates tremendous opportunity but also risk. The same models that help us understand protein folding can also generate harmful biological structures. Every advance has two sides. We must understand both.
Q: How do you prepare students for academic and industry careers?
I do not think about academia and industry as two separate tracks. In my experience, they strengthen each other. My time at Amazon opened my eyes to aspects of research I had not fully appreciated. It revealed new dimensions of applied work and helped me understand how to develop new theories to cope with real systems and decisions.
Academia, in turn, gives you the depth to understand those problems more fully. Theoretical foundations allow applied methods to work reliably and scale. When you remain open-minded, each side informs the other. That is what I try to pass on to students—the ability to move between perspectives and let those insights guide their work.
If students learn to approach problems with curiosity and flexibility, they will be well prepared for either path. The two are not in conflict; together, they create a richer way of thinking about research and practice.
Q: What do you find most rewarding about your work as a scholar and advisor?
It gives me a deep internal happiness. That kind of joy carries you through paper rejections, funding rejections—everything. Research is a mental puzzle, and I genuinely love solving puzzles with collaborators, especially students. They challenge me, surprise me and often bring insights which I would not reach on my own. Over time, these collaborations feel like an extended family. Students graduate, go off to do amazing things and often come back. Those long-term relationships are mutually sustaining.
Q: Do you intentionally cultivate that sense of community among your students?
I believe in fairness, care and hard work. Students are perceptive. They see how much effort you put in, and they respond in kind. I do not announce or advertise what I do for them; the trust builds naturally. Advising has a caring dimension for me, and that makes it fulfilling. When people feel supported, the bonds that form within a research group become very special.
Q: Looking ahead, what legacy do you hope to leave for the department and for the students who pass through it?
I am not thinking about legacy. Many chairs before me have done exceptional work, and they built the foundation we stand on today. I see my role as doing my part in that continuum. If I can help create a better research environment, support our faculty and make daily life a little easier, that is enough. I feel lucky to do work that I love, and that sense of happiness spills into everything else. It makes the challenges worthwhile. If the spirit of curiosity, care and dedication continues after me, the department will keep moving forward. That is all I hope for.