Summary
Zeliang Zhang is a PhD candidate in Computer Science at the University of Rochester with 13 years of engineering experience focused on high-performance computing and trustworthy AI. He has repeatedly interned as a Research Scientist at Microsoft, working on efficient training and inference for large language and reasoning models and on high-performance DFT computation libraries like cuPySCF. Zeliang blends deep systems-level optimization skills with applied AI research, routinely moving ideas from prototype code to performance-focused implementations. Based in Rochester, he maintains an academic presence (Google Scholar) and a technical portfolio on his personal website, signaling a strong bridge between rigorous research and practical engineering impact. An understated strength is his sustained ability to iterate across multiple Microsoft research projects, indicating adaptability and a track record of delivering measurable performance improvements.
13 years of coding experience