My name is Koorosh Aslansefat. I am an assitant professor at School of Computer Science, University of Hull.

Biography

Koorosh Aslansefat is an Assistant Professor of Computer Science and a member of the Dependable Intelligent System Group (DEIS) in the University of Hull. He received the M.Sc. degree in control engineering from Shahid Beheshti University, Tehran, Iran, in 2014. He got a fellowship with Grant No. 723764 for the EU H2020 project entitled: GO0D MAN (aGent Oriented Zero Defect Multi-stage mANufacturing) from 2016 to 2018. In 2018, he got a Studentship Award from EDF Energy R&D UK to do a PhD at the University of Hull and have an industrial collaboration with EDF Energy for a project entitled: DREAM (Data-driven Reliability-centred Evolutionary Automated Maintenance for Offshore Wind Farms). In his PhD career, he managed to get the IET Leslie H. Paddle Award for being an Outstanding Researcher for his research works on Real-time dependability evaluation and the DREAM project. In 2021, he became a Research Associate and as a named researcher got a fellowship with Grant No. 101017258 for another EU H2020 project entitled: (SESAME) Secure and Safe Multi-Robot Systems. In this position, he managed to get an Post-Doctoral Enrichment Award from the Alan Turing Institute for his innovative research on safety evaluation of machine learning known as SafeML. Koorosh Aslansefat is internationally renowned for innovative research on engineering of dependable systems that includes real-time dependability analysis of complex systems and safety assurance of machine learning algorithms. His main research interests are in artificial intelligence safety and explainability, Markov modelling, performance assessment, optimization, stochastic modelling, and runtime dependability evaluation.

Kaggle

You can find my profile at Kaggle.

⚗️ Current Research Projects

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SafeML SafeNN SafeDrones HDFT
AI safety, machine learning safety, deep learning safety, SafeML, SafeAI, SafeDL Neural Network Safety Dependability reliability explainability interpretability, AI safety Drones Safety, UAV Safety, UAV reliability, flying cars dependability</td> Dynamic Fault Tree