Ruixiang (Ryan) Tang

Ruixiang (Ryan) Tang is an Assistant Professor in the Department of Computer Science at Rutgers University, where he leads a research group on Trustworthy Machine Learning. His work aims to infuse trust throughout the machine learning lifecycle by formalizing trustworthiness objectives such as robustness, interpretability, and safety, and developing principled algorithms with measurable guarantees and transparent failure modes. He also collaborates closely with biologists and health informaticians to translate trustworthy learning methods into high-impact problems in biology and medicine.

A central focus of his current research is addressing the new and complex trustworthiness challenges introduced by large foundation models. His long-term objective is to develop learning algorithms that improve reasoning reliability under distribution shift and adversarial manipulation, supported by theoretical frameworks that connect representation, optimization, and uncertainty to trust outcomes. By advancing the underlying reasoning mechanisms of these models, his group aims to make them more reliable, transparent, and resistant to misuse.