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Koorosh Aslansefat

Mr Koorosh Aslansefat

Research Associate

Faculty and Department

  • Faculty of Science and Engineering
  • School of Computer Science

Qualifications

  • PhD (University of Hull)

Summary

Koorosh Aslansefat was born in Tehran, Iran, in 1989. He received 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

View more outputs

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, 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

Project

Funder

Grant

Started

Status

Project

The Alan Turing Institute - Post-Doctoral Enrichment Awards

Funder

The Alan Turing Institute

Grant

£2,000.00

Started

1 March 2022

Status

Complete

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.

Awards and prizes

IET Leslie H. Paddle Award for an Outstanding Researcher

2020

Koorosh has won a prestigious award and “IET Leslie H. Paddle Scholarship of £5,000 from the Institution of Engineering and Technology (IET). The award is in recognition of his outstanding research on his thesis with the title DREAM: Data-driven Reliability-centered Evolutionary and Automated Maintenance for Offshore Wind Farms, where is and is exploring intelligent data-driven optimization of asset maintenance in Offshore Wind Farms.

Top Peer Review Awards in Computer Science, Engineering, and Cross-Field from Publons

2019

Scholarship role

Studentship Award from EDF Energy R&D UK for project entitled: DREAM (Data-driven Reliability-centred Evolutionary Automated Maintenance for Offshore Wind Farms)

2018

Fellowship, Grant No. 723764 for the H2020 project entitled: GO0D MAN (aGent Oriented Zero Defect Multi-stage mANufacturing)

2017

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