Mehrzad is a PhD student in Computer Science 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 data analytic for industrial networks. Her research lies on the areas of machine learning, on-line learning and statistic. In particular her research focuses on developing efficient algorithm and using machine learning methods to learn from sensor data, and predict probable imminent instrument failure.
Articles in journals
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. In Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017. (International Conference on Advanced Cloud and Big Data). pp. 337--342.
Lavassani, M. , Barac, F. , Gidlund, M. & Zhang, T. (2016). Handling Event-Triggered Traffic of Safety and Closed-Loop Control Systems in WSANs. In 14th IEEE International Conference on Industrial Informatics (INDIN'16).. pp. 631--636.
Xue, R. , Zhang, T. , Chen, D. , Le, J. & Lavassani, M. (2016). Sensor Time Series Association Rule Discovery Based on Modified Discretization Method. In 2016 FIRST IEEE INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND THE INTERNET (ICCCI 2016).. pp. 196--202.
Licentiate theses, monographs
Lavassani, M. (2018). Reliable Information Exchange in IIoT : Investigation into the Role of Data and Data-Driven Modelling. Lic. Sundsvall : Mid Sweden University, 2018 (Mid Sweden University licentiate thesis : 147)