Koorosh Aslansefat

Koorosh Aslansefat

Research Assistant

Faculty and Department

  • Faculty of Science and Engineering
  • Department of Computer Science and Technology

Qualifications

  • BSc
  • MSc
  • PhD (University of Hull)

Summary

Koorosh Aslansefat was born in Tehran, Iran, in 1989. He received the B.Sc. degree in marine electronic and communication engineering from Chabahar Maritime University, Chabahar, Iran, in 2011, and the M.Sc. degree in control engineering from Shahid Beheshti University, Tehran, Iran, in 2014. He is currently pursuing the Ph.D. degree with the University of Hull, Hull, U.K., working on data-driven reliability-centered evolutionary and automated maintenance for offshore wind farms. His main research interests are in artificial intelligence safety and explainability, Markov modeling, performance assessment, optimization, and stochastic modeling.

701026 - Real-Time Dependable Systems

Recent outputs

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Book Chapter

A conceptual framework to incorporate complex basic events in HiP-HOPS

Kabir, S., Aslansefat, K., Sorokos, I., Papadopoulos, Y., & Gheraibia, Y. (2019). A conceptual framework to incorporate complex basic events in HiP-HOPS. In Y. Papadopoulos, K. Aslansefat, P. Katsaros, & M. Bozzano (Eds.), Model-Based Safety and Assessment. IMBSA 2019 (109-124). Cham: Springer Verlag. https://doi.org/10.1007/978-3-030-32872-6_8

Journal Article

Towards Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems

Aslansefat, K., Kabir, S., Abdullatif, A., Vasudevan Nair, V., & Papadopoulos, Y. (in press). Towards Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems. Computer,

SafeML: Safety Monitoring of Machine Learning Classifiers Through Statistical Difference Measures

Aslansefat, K., Sorokos, I., Whiting, D., Tavakoli Kolagari, R., & Papadopoulos, Y. (2020). SafeML: Safety Monitoring of Machine Learning Classifiers Through Statistical Difference Measures. Lecture notes in computer science, 12297, 197-211. https://doi.org/10.1007/978-3-030-58920-2_13

A Hybrid Modular Approach for Dynamic Fault Tree Analysis

Kabir, S., Aslansefat, K., Sorokos, I., Papadopoulos, Y., & Konur, S. (2020). A Hybrid Modular Approach for Dynamic Fault Tree Analysis. IEEE access : practical innovations, open solutions, 8, 97175-97188. https://doi.org/10.1109/ACCESS.2020.2996643

A runtime safety analysis concept for open adaptive systems

Kabir, S., Sorokos, I., Aslansefat, K., Papadopoulos, Y., Gheraibia, Y., Reich, J., …Wei, R. (2019). A runtime safety analysis concept for open adaptive systems. Lecture notes in computer science, 11842, 332-346. https://doi.org/10.1007/978-3-030-32872-6_22

Research interests

• Artificial Intelligence Safety and Explainability

• Performance Assessment

• Data-driven Fault Detection, Diagnosis, and Prognosis

• Dependability Evaluation and Improvement

• Optimization and Evolutionary Algorithms

• Probabilistic Modelling (In particular Markov Modelling)

• Offshore Wind Turbines

• Safety Evaluation of Multi-Robot Systems

Postgraduate supervision

SafeML: Exploring techniques for safety monitoring of machine learning classifiers.

SafeDrones: Reliability/Safety Modelling and Evaluation of Multicopters (Multi-rotor Drones) and Electric powered Vertical TakeOff and Landing (eVTOL) Aircrafts.