Research News
UC Berkeley IEOR-led Team Takes Second Place for Predictive Model Aiming to Improve Rail Safety
UC Berkeley IEOR PhD student Alberto Gennaro and his team are applying data-driven modeling to a problem that directly affects the safety and reliability of railroads: predicting when train wheels are likely to fail. Their project earned second place in the 2025 INFORMS Railway Applications Section Problem Solving Competition, which invites researchers and practioners to…
Read MoreUC Berkeley IEOR at the 2025 INFORMS Annual Meeting
UC Berkeley IEOR faculty, students, and alumni brought home several awards at the 2025 Institute for Operations Research and the Management Sciences (INFORMS) Annual Meeting. Below is a list of their accomplishments: Renato D.C. Monteiro, a UC Berkeley IEOR PhD alum (Class of 1988) and Coca-Cola Foundation Chair Professor in the H. Milton Stewart School…
Read MoreUC Berkeley IEOR professor and alum earn international prize for breakthroughs in optimization
UC Berkeley Professor Alper Atamturk and UC Berkeley alum Andrés Gómez have been awarded the 2025 INFORMS Computing Society Prize, an honor recognizing outstanding contributions at the intersection of computing with operations research. They share the award with their collaborator Shaoning Han. The team is recognized for a sequence of five papers introducing new mathematical…
Read MoreAre we truly on the verge of the humanoid robot revolution?
By Kara Manke In two new papers, UC Berkeley roboticist Ken Goldberg explains why robots are not gaining real-world skills as quickly as AI chatbots are gaining language fluency. August 27, 2025 AI chatbots have advanced rapidly over the past few years, so much so that people are now using them as personal assistants, customer service representatives and even…
Read MoreUC Berkeley Researchers Win Top Honors at World’s Leading Robotics Conference
A team of researchers from UC Berkeley has received the Best Paper Award on Robot Learning at the 2025 IEEE International Conference on Robotics and Automation (ICRA), considered the world’s premier conference in robotics and automation. The event was held in Atlanta 19-23 May. The award went to UC Berkeley IEOR Professor Ken Goldberg, his…
Read MoreUC 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…
Read MoreAssistant Professor Chiwei Yan Awarded NSF EAGER Grant to Advance Research on Autonomous Mobility
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…
Read MoreBerkeley IEOR Researchers Named Finalists at American Control Conference
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…
Read MoreBerkeley IEOR PhD students Win Best Theoretical Paper Award
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…
Read MoreTraining Smarter AI: New Research Integrates Human and Machine Feedback
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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