I am a Dean’s Professor, the inaugural director of the USC-Amazon Center for Trustworthy AI, and the director of the Information Theory and Machine Learning (vITAL) research lab at the Electrical and Computer Engineering Department and Computer Science Department of University of Southern California. I am also the co-founder of FedML AI, TensorOpera AI, and ChainOpera AI. I received my Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley in 2008. I do research in the areas of information theory, decentralized and federated machine learning, secure and privacy-preserving learning and computing, and blockchain systems.
As the inaugural director of the Center for Secure and Trusted Machine Learning, or Trusted AI, I am excited about our collaboration with Amazon at the USC Viterbi School of Engineering. This partnership is dedicated to revolutionizing machine learning by focusing on the development of robust, privacy-preserving solutions. By leveraging USC's academic expertise and Amazon's technological capabilities, we aim to address critical challenges in ML privacy, security, and trustworthiness, ensuring that our advancements lead to secure, practical applications in real-world scenarios.
FedML is a comprehensive open-source framework I helped create to facilitate the development, deployment, and management of federated learning (FL) applications. By enabling collaboration across multiple devices and data sources without compromising privacy, we address the challenges of distributed machine learning. Our platform supports a variety of FL paradigms, including horizontal, vertical, and federated transfer learning, making it versatile for diverse applications. As a co-founder and the CEO of FedML, I am dedicated to empowering researchers and developers to efficiently scale FL models, ensure data privacy, and optimize performance through decentralized computing.
.jpg)
TensorOpera provides the generative AI platform and foundation models to enable developers and enterprises to build and commercialize their own generative AI applications easily, scalably, and economically. Its flag product, TensorOpera AI, provides unique features in enterprise AI platforms, model deployment, model serving, AI agent APIs, launching training/Inference jobs on serverless/decentralized GPU cloud, experimental tracking for distributed training, federated learning, security, and privacy.
ChainOpera AI is a Layer-1 blockchain with a federated AI operating system (OS) that enables the co-creation and co-ownership of decentralized AI agents and applications. It blends AI and Web3 by letting developers, data providers, and compute contributors collaboratively build, train, and monetize AI models in a decentralized, transparent, and privacy-preserving way. Using blockchain’s immutable records and tokenized incentives, it ensures ownership, usage rights, and revenue distribution are verifiable on-chain, rewarding all participants fairly without relying on a central authority.
