Yuxuan Zhang

Doktorand|Doctoral Student


Yuxuan Zhang completed his Master's Degree in Embedded Systems Engineering from the University of Leeds, Leeds, UK, in 2019. He joined Mid Sweden University in 2021 as a Doctoral Student.


Yuxuan's current research focuses on the performance and optimization of deep learning/machine learning on low-power MCUs, with a particular focus on structural health monitoring applications.

Other information

ORCID: 0000-0002-8617-0435



Articles in journals

Zhang, Y. , Adin, V. , Bader, S. & Oelmann, B. (2023). Leveraging Acoustic Emission and Machine Learning for Concrete Materials Damage Classification on Embedded Devices. IEEE Transactions on Instrumentation and Measurement, vol. 72  

Conference papers

Adin, V. , Zhang, Y. , Oelmann, B. & Bader, S. (2023). Tiny Machine Learning for Damage Classification in Concrete Using Acoustic Emission Signals. In 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).  

Adin, V. , Zhang, Y. , Ando, B. , Oelmann, B. & Bader, S. (2023). Tiny Machine Learning for Real-Time Postural Stability Analysis. In 2023 IEEE Sensors Applications Symposium (SAS).  

Zhang, Y. , Bader, S. & Oelmann, B. (2022). A Lightweight Convolutional Neural Network Model for Concrete Damage Classification using Acoustic Emissions. In 2022 IEEE Sensors Applications Symposium, SAS 2022 - Proceedings.  

Licentiate theses, comprehensive summaries

Zhang, Y. (2024). Tiny Machine Learning for Structural Health Monitoring with Acoustic Emissions. Lic. (Comprehensive summary) Sundsvall : Mid Sweden University, 2024 (Mid Sweden University licentiate thesis : 204)  


Muthumala, U. , Zhang, Y. , Martinez Rau, L. & Bader, S. Comparison of Tiny Machine Learning Techniques for Embedded Acoustic Emission Analysis.

Zhang, Y. , Pullin, R. , Oelmann, B. & Bader, S. Data Augmentation of Acoustic Emission Signals for Real-time Fault Diagnosis based on Tiny Machine Learning.

The page was updated 5/14/2024