Ali Salamati
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Ali Salamati
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Bio and Research
Ali Salamati is a doctoral researcher in the Software and Computational Systems lab, Institute for Informatics at the Ludwig Maximilian University of Munich (LMU). He is a member of Hybrid Control Systems (HyConSys) Lab. He is a member of Niroo Research Institute as a project manager and researcher. He also has been with University of Tehran since 2016. He received his B.Sc. and M.Sc. degrees from Shiraz University, Shiraz, Iran and K.N.Toosi University of Technology (KNTU), Tehran, Iran, respectively. His main research fields include:
Application of data analysis techniques and learning methods in formal synthesis and verification;
Stochastic Systems;
Hybrid Systems;
Smart Energy Systems.
Book
Hamid D. Taghirad and A. Salamati, Fundamentals of Measurements in Instrumentation. K.N. Toosi University Publication,September 2013. (second edition has been published in 2015).
Journal Papers
A. Salamati, A. Lavaei, S. Soudjani, and M. Zamani, Data-driven verification and synthesis of stochastic systems through barrier certificates, submitted to Automatica, December 2022.
N. Noroozi, A. Salamati, and M. Zamani, Data-driven Safety Verification of Discrete-time Networks: A Compositional Approach, IEEE Control Systems Letters, December 2022.
A. Salamati, S. Soudjani, and M. Zamani, Data-driven verification of stochastic linear systems with signal temporal logic constraints, Automatica , Volume 131, September 2021.
T. Hosseinalizadeh, M. Salamati, A. Salamati, and Gevork B Gharehpetian, Improvement of Identification Procedure Using Hybrid Cuckoo Search Algorithm for Turbine-Governor and Excitation System, IEEE Transactions on Energy Conversion, 34(2), pp. 585-593, September 2018.
Conference Papers
A. Salamati, A. Lavaei, S.Soudjani, and M. Zamani, Data-driven Safety Verification of Stochastic Systems via Barrier Certificates, 7th IFAC Conference on Analysis and Design of Hybrid Systems, July 2021. (Best Repeatability Prize)
A. Salamati, S.Soudjani, and M. Zamani, Data-Driven Verification under Signal Temporal Logic Constraints, Volume 53, Issue 2, January 2020, Pages 69-74.
A. Salamati, M. Salamati, and Farzad Rajaei Salmasi, Experimental identification and verification for a comprehensive model of multi-shaft combined cycle power plant, IEEE-IAS 54th Industrial and Commercial Power Systems Technical Conference (I&CPS), pp. 1-8, May 2018.
M. Salamati, A. Salamati, M. Mahoor, and Farzad Rajaei Salmasi, Leveraging adaptive model predictive controller for active cell balancing in Li-ion battery, North American Power Symposium (NAPS), pp. 1-6, November 2017.
A. Salamati, H.D. Taghirad, and A. Chaibakhsh, Robust control of a steam turbine power based on a precise nonlinear model, 5th Conference on Thermal Power Plants (CTPP), pp. 12-18, February 2015.
Master Students
Mohamed Nabil Babai, “Deep Learning Explainability with Video Classification Task”, in cooperation with Institute for Human-Machine Communication at Technical University of Munich.