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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.”
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.