Berkeley Industrial Engineering and Operations Research

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Berkeley Industrial Engineering and Operations Research The Berkeley IEOR department is one of the finest schools in the world and is ranked 2nd in the U.S

The Department of Industrial Engineering and Operations Research combines two closely related professions concerned with the efficient operation of complex systems. The industrial engineering profession involves the design, organization, implementation, and economic operation of integrated production and service systems using people, materials, and equipment. Areas of application include not only the basic manufacturing and high technology production processes essential to our economy, but also service organizations such as banks, health care facilities, libraries, and government agencies. Operations research emphasizes the basic understanding of the functioning of complex systems of technology and management through mathematical models for the purpose of predicting system behavior or optimizing system performance under economic and technological constraints. Our Faculty are world-renowned experts in many application areas, from semiconductor manufacturing to the design and deregulation of energy markets to supply chain management to robotics to discrete event simulation, and have made important advancements in the theory of operations research, in areas such as algorithm design, integer programming, non-linear programming, and stochastic modeling.

Welcome back to our series spotlighting the newest members of our Berkeley IEOR graduate community!Meet Samantha Chen, a...
10/28/2026

Welcome back to our series spotlighting the newest members of our Berkeley IEOR graduate community!

Meet Samantha Chen, a Master of Analytics student in the Class of 2027 with a background in statistics and an interest in improving financial decision-making.

What inspired Samantha to pursue graduate studies in IEOR?

“Using optimization to turn statistical insight into better decisions, from allocating capital to hedging risk. I want to learn to not just analyze financial systems, but engineer better ones.”

From leading a customer analytics project for PChome to working on derivatives analytics at Yuanta Securities, Samantha has explored how technical modeling can inform real-world business decisions.

Outside the classroom, she enjoys Texas Hold’em, where she puts her love of probability and reading people into practice! ♠️

Swipe through to get to know Samantha, and stay tuned as we introduce more of the students who make up our Berkeley IEOR community!

10/27/2026

BOO! Halloween is right around the corner, and our Ask Away with Anne host couldn’t be more excited to dress up with Katie Chang (IEOR/DS ’27)! 🎃✨

Being a senior at Berkeley IEOR might sound intimidating, but Katie faces it fearlessly. After four years of mastering supply chain frameworks and optimization theories, she feels fully prepared for what’s next. Backed by real-world internships and consulting experience, she’s stepping into the post-grad world with total confidence.

📽️ 💭Watch the full video to get inspired and see how she answers this question: “How have you seen yourself grow over the past 4 years? Have you become more experienced and confident in your technical abilities, or have you finally found an area of interest you’d like to pursue in the future of IEOR?”

Happy Halloween from Berkeley IEOR! 🎃

10/26/2026

We love the vision 💙💛

The Department of Industrial Engineering & Operations Research at UC Berkeley invites applications for a tenure-track as...
10/22/2026

The Department of Industrial Engineering & Operations Research at UC Berkeley invites applications for a tenure-track assistant professor position.

We welcome candidates conducting fundamental and applied research in stochastic modeling, machine learning, game theory, optimization, or operations management, with a demonstrated commitment to applications in risk management and financial technology (FinTech).

Applications from a wide range of academic backgrounds and all IEOR research areas will be considered, with an emphasis on FinTech applications, broadly defined.

Application deadline: December 1, 2026

View the full position description and apply through UC Berkeley’s AP Recruit website: https://bit.ly/4jRUmjh

Please share this opportunity with colleagues and others who may be interested.

Thinking about applying to the UC Berkeley IEOR PhD program but feeling a little intimidated? 👀 You might be worrying ab...
10/20/2026

Thinking about applying to the UC Berkeley IEOR PhD program but feeling a little intimidated? 👀 You might be worrying about things that aren't even true...

From misconceptions about required work experience to concerns about affording a PhD, there are plenty of myths that can make pursuing a doctoral degree seem out of reach.

So let's clear a few things up. Swipe through to see myths vs. the reality about applying to the UC Berkeley IEOR PhD program.

Learn more about how to apply: ieor.berkeley.edu/academics/phd/

Meet Megan Zhang, an MEng ’27 student from Fremont, California, who studied Industrial Engineering as an undergrad at Pe...
10/19/2026

Meet Megan Zhang, an MEng ’27 student from Fremont, California, who studied Industrial Engineering as an undergrad at Penn State.

What inspired Megan to pursue graduate studies in IEOR?

"My interest in pursuing graduate studies in IEOR was shaped by my undergraduate research on eye-tracking and clinical decision-making, where I investigated how healthcare providers' visual attention related to diagnostic confidence and accuracy."

At Berkeley, Megan is excited to explore optimization, machine learning, and decision analytics, particularly their applications in healthcare and supply chain systems.

Outside of academics, Megan enjoys going to the beach, exploring new places, and spending time with friends and family. 🌎 Her goal? To visit all seven continents before turning 30!

Swipe through to get to know Megan, and stay tuned as we introduce more of the students who make up our Berkeley IEOR community!

10/14/2026

At 15, Ysa Medina launched her jewelry brand, Le Petite Sprout. Now a fourth-year UC Berkeley IEOR student, she’s grown her business to $2.3 million in revenue, with 60,000+ orders and 40,000+ customers worldwide.

In this episode of Ask Away with Anne, Ysa shares why she chose industrial engineering and operations research and how she applies its mix of business and technical problem-solving to inventory management, demand forecasting, and day-to-day efficiency.

How does she balance running a business with a full Berkeley course load? Watch the full interview!

Welcome back to our series spotlighting the newest members of our Berkeley IEOR graduate community! Meet Ade Ajayi, a Ph...
10/13/2026

Welcome back to our series spotlighting the newest members of our Berkeley IEOR graduate community!

Meet Ade Ajayi, a PhD student from Nashville, Tennessee, who earned his B.S. in Industrial Engineering from Columbia University.

What inspired Ade to pursue graduate studies in IEOR?

"I was inspired to pursue graduate studies in IEOR because I’ve always known that I wanted to use mathematics and research to make an impact on the world. To me, IEOR is the best field to do that!"

Beyond his research, Ade enjoys hiking, Buddhist, running, playing the trumpet, and tinkering on projects—including building a drone from scratch! 🚁

Swipe through to get to know Ade, and stay tuned as we introduce more of the students who make up our Berkeley IEOR community!

If organizations increasingly use generative AI to build simulations, can those models reproduce not only the most likel...
10/12/2026

If organizations increasingly use generative AI to build simulations, can those models reproduce not only the most likely outcomes, but also the rare ones that may matter most?

UC Berkeley Researchers - IEOR Ph.D. students and co-first authors Haoyu Liu and Tingyu Zhu, working with Associate Professor Zeyu Zheng and collaborators - have developed a new diffusion model that helps plan for rare, high-stakes events.

Their method, called Score-based Heavy-Tailed Diffusion (SHD), replaces the standard noise process in diffusion models with a heavy-tailed distribution. Their approach helps simulations better capture rare and extreme outcomes that conventional models underestimate.

Read more: https://bit.ly/4hIKmap

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