Photo of Haoting Zhang, the paper's first author, receiving the award plaque during the conference.
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 the integration of human and machine feedback.

The Winter Simulation Conference is a leading global forum that highlights the transformative role of simulation in system design, innovation, and operations. The Best Theoretical Paper Award is given annually to one outstanding paper among all accepted theory-focused contributions, recognizing exceptional contributions to advancing simulation methodologies. This recognition underscores the impact of Zhang, He, and Xu’s research in the evolving fields of AI and simulation. You can learn more about their work here, and at the link below.

Learn more about this award-winning research paper

Training Smarter AI: New Research Integrates Human and Machine Feedback