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Hao Zheng is part of a Multi-University Project Awarded a $1M NSF Grant

USF Department of Computer Science and Engineering Associate Professor Hao Zheng is part of a multi-university, collaborative project awarded a $1M National Science Foundation (NSF) grant to carry on fundamental research for the project entitled “FET: Medium: Collaborative Research: An Efficient Framework for the Stochastic Verification of Computation and Communication Systems Using Emerging Technologies.”

Hao Zheng

USF Department of Computer Science and Engineering Associate Professor Hao Zheng is part of a multi-university, collaborative project awarded a $1M National Science Foundation (NSF) grant to carry on fundamental research for the project entitled “FET: Medium: Collaborative Research: An Efficient Framework for the Stochastic Verification of Computation and Communication Systems Using Emerging Technologies.”  

This multi-university, collaborative project totaling $1M includes The University of Utah, Utah State University and The University of South Florida. Zheng will work with Professor Chris Myers, Assistant Professor Zhen Zhang, and Associate Professor Chris Winstead in this four-year collaboration.

According to Zheng, “The goal of this research is to develop scalable and efficient methods and algorithms for verification and analysis of designs created using emerging technologies such as synthetic biology. These designs are often created with unreliable components, and operate in noisy environments. Therefore, the behavior of these designs is typically stochastic, and they often have large or even infinite state space. Stochastic verification techniques have demonstrated significant potential in quantitatively analyzing such designs. Unfortunately, they are generally computationally intractable for large and complex designs. This project will address that challenge by developing an automated stochastic verification framework that integrates an approximate stochastic model checking approach and counterexample-guided rare-event simulation to improve the analysis accuracy and efficiency."

The project’s duration is from July 2019 to June 2023.