Runbo Jiang

Runbo Jiang is a Machine Learning Engineer at Berkeley Lab, focusing on enhancing data visualization and accelerating materials discovery through advanced techniques. With prior experience as a Machine Learning Engineering Intern at Moveworks, Runbo Jiang implemented algorithms to evaluate conversation policies and achieved a notable conversion rate improvement. As a Doctoral Researcher at Carnegie Mellon University, significant contributions included developing algorithms for synchrotron x-ray image analysis and employing natural language processing to mine materials literature. Currently serving as a Research Scientist at Meta, Runbo Jiang specializes in feed relevance engineering for Threads. Academic qualifications include a PhD in Materials Science and Engineering, an MS from Carnegie Mellon University, and a BE in Materials Engineering from Jiangsu University.