Berkeley IEOR Honors Professor Alper Atamturk for His Leadership as Department Chair

AlperAtamturk

The Department of Industrial Engineering and Operations Research at UC Berkeley (Berkeley IEOR) extends its gratitude to Professor Alper Atamturk for his exemplary leadership and dedicated service as department chair from January 1, 2021, to June 30, 2025. Over his 4.5-year tenure, Professor Atamturk guided the department through a period marked by both extraordinary challenges…

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Professor Shmuel Oren Named 2025 IFORS Fellow

Oren Shmuel IEOR

The Department of Industrial Engineering & Operations Research congratulates Professor Shmuel Oren on being named a 2025 Fellow of the International Federation of Operational Research Societies (IFORS). One of the highest international honors in the field, the IFORS Fellows Award recognizes distinguished individuals for their contributions to international operational research and its global communities. Professor…

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UC Berkeley Researchers Offer a Smarter Way to Price With Stability and Impact in Mind

UC Berkeley Researchers Offer a Smarter Way to Price—With Stability and Impact in Mind

With inflation, tariffs, and shifting consumer habits, setting the right price has never been more complicated or more crucial. But new research from UC Berkeley’s Department of Industrial Engineering and Operations Research suggests that simplicity might be the key to navigating today’s complex markets. In a recent study, Associate Professor Javad Lavaei, Professor Emeritus Max…

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Assistant Professor Chiwei Yan Awarded NSF EAGER Grant to Advance Research on Autonomous Mobility

Chiwei Yan Headshot

Berkeley IEOR Assistant Professor Chiwei Yan has been awarded a National Science Foundation (NSF) Early-concept Grant for Exploratory Research (EAGER) to support his project, State-Aware Demand Control to Facilitate Shared Use of Autonomous Mobility. The project explores new models and algorithms to promote ride-pooling and shared use in emerging autonomous mobility systems. By leveraging real-time…

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Berkeley IEOR Researchers Named Finalists at American Control Conference

IEOR Professor and PhD student (1080 x 1080 px)

Berkeley lEOR PhD student Jihun Kim and Professor Javad Lavaei have been named finalists at the American Control Conference (ACC), a premier annual gathering of researchers and practitioners advancing the field of control systems engineering. Their paper, “Prevailing Against Adversarial Noncentral Disturbances: Exact Recovery of Linear Systems with the l1-Norm Estimator,” is among the top…

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Zeyu Zheng Receives Peter D. Welch Early Career Award

Zeyu Zheng headshot

Zeyu Zheng has been honored with the inaugural Peter D. Welch Early Career Award by the INFORMS Simulation Society (I-SIM). This award recognizes early-career researchers for their exceptional contributions to the field of simulation. Zheng received the award at the December 2024 Winter Simulation Conference, where he and his co-authors also won the Best Theoretical…

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Ancient Wisdom: Exploring the Intersection of AI, Art, and Nature

Tiffany Shlain and Ken Goldberg's Ancient Wisdom, installation view 2024, photo by Stefanie Atkinson Schwartz, Courtesy of Skirball Cultural Center

The cover of the winter 2025 edition of Berkeley IEOR Magazine showcases artwork from Ancient Wisdom: Trees, Time, and Technology, an exhibition by Ken Goldberg and Tiffany Shlain currently on view at the Skirball Museum in Los Angeles through March 2, 2025. Part of the Getty Museum’s city-wide Pacific Standard Time quadrennial, the exhibit examines…

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Berkeley IEOR PhD students Win Best Theoretical Paper Award

Photo of Haoting Zhang, the paper's first author, receiving the award plaque during the conference.

Berkeley IEOR PhD students Haoting Zhang, Jinghai He, and recent alum Jingxu Xu (PhD ’24) were honored with the Best Theoretical Paper Award at the 2024 Winter Simulation Conference held in Orlando, Florida. Their award-winning paper, Enhancing Language Models with Both Human and Artificial Intelligence Feedback Data, explores innovative methods to improve AI performance through…

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Training Smarter AI: New Research Integrates Human and Machine Feedback

Abstract representation of artificial intelligence featuring

AI models rely heavily on feedback to refine their outputs and meet user needs. While human feedback is highly effective, it is often expensive, time-intensive, and limited by data privacy constraints. For example, training an AI system to detect early signs of cancer in medical scans relies on radiologists to verify predictions and provide annotations.…

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