Mehran Alidoost Nia has a PhD in Software Engineering from University of Tehran, and is a researcher in DRTS (Dependable/Distributed Real-Time Systems) Lab at University of Tehran. His research interests include Cyber-Physical Systems, Self-Adaptive and Autonomous Systems, Formal Verification and Information Security. His research in PhD program was about probabilistic analysis of self-adaptive and autonomous systems entitled "Runtime Probabilistic Analysis of Self-Adaptive Systems via Formal Approximation Techniques", that was supervised by Mehdi Kargahi (University of Tehran) and Alessandro Abate (University of Oxford). He is also a Programme Fellow at the University of York, and collaborating on Assuring Autonomy International Programme (AAIP) under supervision of Radu Calinescu since 2020.
MehranAlidoost Nia, et al. Radu Calinescu, Mehdi Kargahi and Alessandro Abate ACM Transactions on Autonomous and Adaptive Systems 2022
Resilient monitoring in self-adaptive systems through behavioral parameter estimation
MehranAlidoost Nia, et al. Mehdi Kargahi and Alessandro Abate Journal of Systems Architecture 2021
Self-Adaptation with Imperfect Monitoring in Solar Energy Harvesting Systems
MehranAlidoost Nia, et al. Mehdi Kargahi and Alessandro Abate RTEST ’2020
Probabilistic approximation of runtime quantitative verification in self-adaptive systems
MehranAlidoost Nia, et al. Mehdi Kargahi and Fathiyeh Faghih Microprocessors and Microsystems 2020
A Model-Driven Approach to Runtime Verification of Self-Adaptive Systems
MehranAlidoost Nia SPLV ’2020 Contributed Talk
Detecting new generations of threats using attribute-based attack graphs
MehranAlidoost Nia, et al. Behnam Bahrak, Mehdi Kargahi and Benjamin Fabian IET Information Security 2019
Probabilistic analysis of self-stabilizing systems: A case study on a mutual exclusion algorithm
MehranAlidoost Nia, et al. Fathiyeh Faghih RTEST ’2018
You can be familiar with my recent projects:
Safe-RQV
A Safe Runtime Approximation Framework for Autonomous Systems
RWV-Incomplete
A Random Walk-Based Pattern-Matching Simulator for Verification of Incomplete Markov Models with Applications in Autonomous Energy-Harvesting Systems.
RAPS
Random-Walk Anonymous Pattern Simulator