Shahin Honarvar

Multi-dimensional robotics systems are vulnerable to errors and the programmer must deal with dynamic controllers (motion primitives) that influence the physical state, component geometric restrictions, and concurrency invariants. As a result, their reliability is difficult to determine. My PhD project focuses on developing model-based verification methods to ensure that concurrent robotics systems are stable and safe. 

I am enthusiastic about effective research solutions to the verification of artificial intelligence. People’s current misconceptions about AI have eroded confidence in its capabilities, yet people need to trust that the technology will be accurate, safe and contribute to the advancement of society. Joining the STAI CDT allows me to share my expertise, creativity and efforts to improve trust in AI. The STAI CDT differs significantly from most PhD programmes. It adds to the excitement of the PhD journey since there are a reasonable number of seminars and lectures to attend, and a student can interact with researchers and other students from a variety of AI topics. Additionally, the CDT staff provide outstanding assistance and support to students. 

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Undergraduate Qualification: BSc Computer Science (First Class Honours) University of Leicester 

Masters Qualification: MSc Data Analytics (Distinction Level) University of Warwick 

Work Experience: Teaching assistant of Mathematics Fundamentals, School of Informatics, University of Leicester (During my undergraduate degree) 

Publications: 1) Property-based Testing of Quantum Programs in Q#. Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops, 2020. https://doi.org/10.1145/3387940.3391459, 2) Poster: Property-based Testing of Quantum Programs in Q#. In “15th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2020)”