Logic List Mailing Archive

PhD student position in efficient model abstraction, Logan UT (U.S.A.)

A PhD position is available (fully funded for 4 years with the
possibility of extension) at the Electrical and Computer Engineering
Department of Utah State University. The expected starting date is early
January 2020. PhD application information is available at:
https://engineering.usu.edu/ece/files/pdfs/ece-graduate-program-application-info.pdf

Abstract:
Synthetic biology and nanotechnology place increasing demands on design
methodologies to ensure dependable and robust operation. Consisting of
noisy and unreliable components, these complex systems have large and
often infinite state spaces that include extremely rare error states.
Probabilistic model checking techniques have demonstrated significant
potential in quantitatively analyzing such system models under extremely
low probability. Unfortunately, they generally require enumerating the
model's state space, which is computationally intractable or impossible.
Therefore, addressing these design challenges in emerging technologies
requires enhancing the applicability of probabilistic model checking.
Motivated by this problem, this project investigates an automated
probabilistic verification framework that integrates approximate
probabilistic model checking and counterexample-guided rare-event
simulation to improve the analysis accuracy and efficiency.

This multi-institution collaborative project focuses on verifying
infinite-state continuous-time Markov chain (CTMC) models with
rare-event properties. It addresses the scalability problem by first
applying property-guided and on-the-fly state truncation techniques to
prune unlikely states to obtain finite state representations that are
amenable to probabilistic model checking. In the case of false or
indeterminate verification results, probabilistic counterexamples are
generated and utilized to improve the accuracy of the state reductions.
Furthermore, it mines these critical counterexamples as automated
guidance to improve the quality and efficiency for rare-event
probabilistic simulations. This verification framework will be
integrated within existing state-of-the-art probabilistic model checking
tools (e.g., the PRISM model checking tool), and benchmarked on a wide
range of real-world case studies in synthetic biology and nanotechnology.

========================================

Project description:

The PhD position at Utah State University will be advancing and developing 
efficient model abstraction and state space truncation techniques for the 
infinite-state CTMC models. In particular, we are interested in 
investigating:

- Model abstraction techniques on chemical reaction networks for
synthetic biology

- Approximation techniques for state space truncation and abstraction

- Property-guided state space pruning techniques

========================================


Qualifications:

Applicants must have a bachelor's degree in Computer Science, Computer
Engineering, or a related field. A master's degree is preferred. The
successful candidate is expected to demonstrate strong background and
interest in formal methods and algorithms, and preferably basic
knowledge of probability and random process. He/She should be confident
in independently developing academic software tools. Good writing and
presentation skills in English are important as well. Knowledge of
synthetic biology is preferred, but not required.
========================================


Contact:

For questions about this position, please contact:

Dr. Zhen Zhang, zhen.zhang@usu.edu,
https://engineering.usu.edu/ece/faculty-sites/zhen-zhang/index
========================================


ECE Department at USU:

The place of employment is the Electrical and Computer Engineering
Department at Utah State University. The university is located in Logan,
Utah, 88 miles (about 142 km) north of Salt Lake City. The mission of
the Department of Electrical and Computer Engineering is to serve
society through excellence in learning, discovery, and outreach. We
provide undergraduate and graduate students an education in electrical
and computer engineering, and we aspire to instill in them attitudes,
values, and visions that will prepare them for lifetimes of continued
learning and leadership in their chosen careers. Through research, the
department strives to generate and disseminate new knowledge and
technology for the benefit of the State of Utah, the nation, and beyond.
The detailed graduate program description can be found at:
https://engineering.usu.edu/ece/students/graduate/index.
========================================


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