Daniel Jiang

Daniel Jiang is a Member of Technical Staff at Anthropic, with previous experience as a PhD ML Intern at Zoox, focusing on real-time detection of out-of-distribution inputs in vision models. A former PhD Candidate at the University of Washington, Daniel developed algorithms at the intersection of contextual bandits and matrix factorization. Research experience includes benchmarking large language models at Google Research, applying machine learning to extreme classification models at Amazon, and enhancing A/B testing methodologies at Berkeley Artificial Intelligence Research. Daniel’s academic background includes a Bachelor's Degree with Honors in Computer Science from the University of California, Berkeley, and a Master's Degree in Computer Science from the University of Washington.