Sajad Shahsavari
 Doctoral Researcher


sajad.s.shahsavari@utu.fi



Työhuone: B6018


ORCID-tunniste: https://orcid.org/0000-0003-3754-1743

Asiantuntijuusalueet
Data processing; Statistical machine learning; Deep learning; Reinforcement learning; Software engineering

Biografia

Sajad Shahsavari is a Ph.D. student at University of Turku, Finland, and works as a researcher at Computational Engineering and Analysis (COMEA) research group in Turku University of Applied Sciences. His research interests include deep neural networks, time-series prediction, reinforcement learning and data analysis. He received his B.Sc. degree in Computer Engineering from Amirkabir University of Technology, Tehran, Iran in 2014 and his M.Sc. degree in Artificial Intelligence from Sharif University of Technology, Tehran, Iran in 2017.



Tutkimus




Julkaisut
  • A Coupled Battery State-of-Charge and Voltage Model for Optimal Control Applications  (2023)  
    • Proceedings : Design, Automation, and Test in Europe Conference and Exhibition
    2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Karami Masoomeh, Shahsavari Sajad, Immonen Eero, Haghbayan Hashem, Plosila Juha
    (    Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))


  • An Extension of the Kinetic Battery Model for Optimal Control Applications  (2023)  
    • Proceedings of the IEEE International Symposium on Industrial Electronics
    2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE) Karami Masoomeh, Shahsavari Sajad, Immonen Eero, Haghbayan Mohammad-Hashem, Plosila Juha
    (    Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))


  • Capacity loss estimation for li-ion batteries based on a semi-empirical model  (2021)  
    • Proceedings: European Conference for Modelling and Simulation
    Proceedings of the 35th ECMS International Conference on Modelling and Simulation ECMS 2021 Rabah Mohammed, Immonen Eero, Shahsavari Sajad, Haghbayan Mohammad-Hashem, Murashko Kirill, Immonen Paula
    (    Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))


  • MCX - An open-source framework for digital twins  (2021)  
    • Proceedings: European Conference for Modelling and Simulation
    Proceedings of the 35th ECMS International Conference on Modelling and Simulation ECMS 2021 Shahsavari Sajad, Immonen Eero, Rabah Mohammed, Haghbayan Mohammad-Hashem, Plosila Juha
    (    Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))


  • Remote Run-Time Failure Detection and Recovery Control For Quadcopters   (2021)  
    • Journal of integrated design and process science
     Shahsavari Sajad, Rabah Mohammed, Immonen Eero, Haghbayan Mohammad-Hashem, Plosila Juha
    (    Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))



Last updated on 2024-06-03 at 11:20