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Zhong Shao

Zhong Shao, PhD

Faculty Member

Center for Neurocomputation and Machine Intelligence

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Programming languages for trustworthy AI systems

Zhong Shao's primary research interests encompass programming languages, formal methods, operating systems, and computer security. Within these fields, he is a strong proponent of certified software and firmly believes that certified programming, accompanied by formal proofs, presents the most promising approach to constructing truly reliable software and effectively managing the increasing complexity of future AI systems. In his laboratory, Shao and his team have recently dedicated their efforts to constructing cyber-physical systems that boast robust security guarantees, including self-driving cars and crewless ground/aerial vehicles. Additionally, they have explored real-time machine learning for embedded systems and delved into the realm of the Internet of Things. Notably, their work focuses on system design, algorithmic techniques, and formal methods aimed at constructing secure, dependable, and accountable AI systems.

Methods

Topics

Research Contributions

Adore: atomic distributed objects with certified reconfiguration

Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation (2022)

Layered and object-based game semantics

Proceedings of the ACM on Programming Languages (2022)

DeepSEA: A language for certified system software

Proceedings of the ACM on Programming Languages (2019)

Building certified concurrent OS kernels

Communications of the ACM (2019)