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Bianniu reported on August 9 that according to foreign news reports,OpenAI Announced the appointment of Professor Zico Kolter of Carnegie Mellon University to the Board of Trustees.

Kolter will also join the board’s Safety and Assurance Committee, which is responsible for making recommendations for key safety decisions across all OpenAI projects.

“I’m thrilled to announce that I’m joining the OpenAI board,” said Kolter, who directs the machine learning department at Carnegie Mellon University’s School of Computer Science. “I look forward to sharing my perspective and expertise on AI safety and robustness to help guide the great work OpenAI is doing.”

Kolter’s work focuses on AI safety, alignment, and robustness of machine learning classifiers. His research and expertise span new deep network architectures, innovative approaches to understanding the impact of data on models, and automated methods for assessing the robustness of AI models, making him a valuable technical director for OpenAI governance.

Bret Taylor, chairman of the OpenAI board, said: Zico adds deep technical understanding and perspective on AI safety and robustness, which will help us ensure that general AI benefits all of humanity.

Kolter was a key figure for 12 years in CMU's Department of Computer Science, the Software and Social Systems Division, the Robotics Institute, the CyLab Security and Privacy Institute, and the College of Engineering's Department of Electrical and Computer Engineering. He received his Ph.D. in Computer Science from Stanford University in 2010, followed by a postdoctoral fellowship at MIT from 2010 to 2012.

During his career, he has made significant contributions to the field of machine learning, authoring many award-winning papers at prestigious conferences such as the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Artificial Intelligence and Statistics (AISTATS).

Kolter's research includes developing the first method for creating deep learning models with guaranteed robustness. He also pioneered the use ofNeural NetworksClassical optimization in layers is a technique for embedding hard constraints into AI models.

Most recently, in 2023, his team developed innovative methods for automatically evaluating the security of large language models, demonstrating the potential to bypass existing model protections through automated optimization techniques.

In addition to his academic pursuits, Kolter has worked closely with industry throughout his career, serving as Chief Data Scientist at C3.ai and currently as Chief Expert at Bosch and Chief Technical Advisor at Gray Swan, a startup focused on AI safety and security.