Mehrzad Lavassani

Mehrzad Lavassani

Doktorand|Doctoral Student

  • Tjänstetitel: Doktorand
  • Avdelning: Institutionen för informationssystem och –teknologi (IST)
  • E-postadress:
  • Besöksadress: Holmgatan 10
  • Rumsnummer: L424
  • Ort: Sundsvall
  • Forskningscentra: Sensible Things that Communicate
  • Anställd vid ämnet: Datateknik, Datavetenskap


Mehrzad is a PhD in student in Communication Systems and Network (CSN) Group at Mid Sweden University (MIUN). Previously she completed her Master’s degree in Computer Engineering in industrial wireless sensor networks at MIUN. The thesis was titled "A Deterministic MAC Protocol to Handle Emergency Traffic in IWSN".
She has a Bachelors degree in Information Technology from Iran University of Science and Technology.


Mehrzad is currently working on the integration of data analytics in various levels of industrial automation systems. Her research places in the overlapping areas of industrial wireless sensor networks, online learning and statistics.
In particular, her research focuses on developing efficient and autonomous data-driven algorithms to enhance reliability in industrial automation processes by real-time change detection and imminent fault prediction. The research utilizes learning and statistical methods to exploit sensor data and to model the stochastic behaviour of the underlying system autonomously.


Artiklar i tidskrifter

Lavassani, M. , Forsström, S. , Jennehag, U. & Zhang, T. (2018). Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT. Sensors, vol. 18: 5    


Lin, Y. , Lavassani, M. , Li, J. & Zhang, T. (2017). PixVid: Capturing Temporal Correlated Changes in Time Series. I Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017. (International Conference on Advanced Cloud and Big Data). S. 337--342.  

Lavassani, M. , Barac, F. , Gidlund, M. & Zhang, T. (2016). Handling Event-Triggered Traffic of Safety and Closed-Loop Control Systems in WSANs. I 14th IEEE International Conference on Industrial Informatics (INDIN'16).. S. 631--636.  

Xue, R. , Zhang, T. , Chen, D. , Le, J. & Lavassani, M. (2016). Sensor Time Series Association Rule Discovery Based on Modified Discretization Method. I 2016 FIRST IEEE INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND THE INTERNET (ICCCI 2016).. S. 196--202.


Lavassani, M. (2018). Reliable Information Exchange in IIoT : Investigation into the Role of Data and Data-Driven Modelling. Lic.-avh. Sundsvall : Mid Sweden University, 2018 (Mid Sweden University licentiate thesis : 147)