Runhua Xu is a research staff member in the group of AI Security & Privacy Solutions at IBM Research - Almaden based in San Jose, CA. Runhua's research interests cover a range of areas: privacy-preserving machine learning, secure computing, access control, applied cryptography, blockchain, security and privacy issues in cloud/edge computing. More specifically, his current research focuses on approaches to achieve privacy-preserving collaborative machine learning models by secure multi-party computing, etc., and efficient and generic approaches to achieve machine learning models over encrypted data. He also works on various issues such as public ledger techniques such as blockchain and smart contracts to build trustworthy, collaborative, and transparent third-party authority infrastructure for advanced cryptosystems.
He holds a Ph.D. degree in Information Security from School of Computing and Information, University of Pittsburgh in 2020. His doctoral dissertation focused on designing secure computation approaches for practical privacy-preserving machine learning. He also worked on addressing issues related to the trustworthiness and transparency of various entities in the privacy-preserving machine learning infrastructure. Prior to that, Runhua received his M.S. degree in Computer Science from Beihang University, China in 2014, and his B.E. in Software Engineering from Northwestern Polytechnical University, China in 2011.