● I am currently a Ph.D. candidate (2019.03-Present, software and communications engineering) in the Faculty of Information Technology, University of Jyväskylä, Finland, supervised by Prof. Lauri Kettunen, Prof. Zheng Chang, Prof. Fengyu Cong, and Prof. Tapani Ristaniemi. I am a member of SPWC lab and ASAP lab.

● I received my master’s degree in the School of Biomedical Engineering from Dalian University of Technology in 2018, supervised by Associate Prof. Liping Qi.

● I obtained my bachelor’s degree in the School of Biomedical Engineering from Dalian University of Technology in 2015.

Research

My research intersets mainly include developing deep learning-based approaches in automatic sleep stage classification tasks (e.g., class imbalance problem, model interpretability, rapid sleep stage classification, etc) from single-channel electroencephalogram (EEG) data, which mainly concerned on:

1. EEG/EMG, etc.
2. Time-frequency analysis: Wavelet transform, short-time Fourier transform (STFT), etc.
3. Deep learning methods: Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Transformer, etc.
4. Model interpretability: Layer-wise Relevance Propagation,etc.
5. Class imbalance problem: Data augmentation, etc

Publications

Journal

1. Dongdong Zhou, Jian Wang, Guoqiang Hu, Jiacheng Zhang, Fan Li, Rui Yan, Lauri Kettunen, Zheng Chang, Qi Xu, and Fengyu Cong (2022). SingleChannelNet: A model for automatic sleep stage classification with raw single-channel EEG. Biomedical Signal Processing and Control, 75, 103592. Paper, Code
2. Dongdong Zhou, Qi Xu, Jian Wang, Hongming Xu, Lauri Kettunen, Zheng Chang, and Fengyu Cong (2022). Alleviating Class Imbalance Problem in Automatic Sleep Stage Classification. IEEE Transactions on Instrumentation and Measurement, 71, 1-12. Paper
3. Rui Yan, Fan Li, Dongdong Zhou, Tapani Ristaniemi and Fengyu Cong (2021). Automatic sleep scoring: A deep learning architecture for multi-modality time series, Journal of Neuroscience Methods, 348, 108971. Paper
4. Liping Qi, Shuo Guan, Dongdong Zhou, Fengshan Gao and Liqing Liu (2021). The influence of muscle fiber type on slow component of oxygen uptake kinetics, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 235(2), 471-478. Paper
5. Liping Qi, Xiaochi Ma, Dongdong Zhou, Shuo Guan, Fengshan Gao and Peixin Cong (2019). Wavelet and principal component analysis of electromyographic activity and slow component of oxygen uptake during heavy and severe cycling exercise, Applied Physiology, Nutrition, and Metabolism. 45(2): 187-192. Paper

Conference

1. Qi Xu, Dongdong Zhou, Jian Wang, Jiangrong Shen, Lauri Kettunen, and Fengyu Cong (2022). Convolutional Neural Network Based Sleep Stage Classification with Class Imbalance, In 2022 International Joint Conference on Neural Networks (IJCNN 2022). 1-6. Co first author. Paper.
2. Dongdong Zhou, Qi Xu, Jian Wang, Jiacheng Zhang, Guoqiang Hu, Lauri Kettunen, Zheng Chang, and Fengyu Cong (2021). LightSleepNet: A Lightweight Deep Model for Rapid Sleep Stage Classification with Spectrograms, In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 43-46. Paper
3. Rui Yan, Fan Li, Dongdong Zhou, Tapani Ristaniemi and Fengyu Cong (2020). A Deep Learning Model for Automatic Sleep Scoring using Multimodality Time Series, In 28th European Signal Processing Conference (EUSIPCO), 1090-1094. Paper

Manuscripts in Progress

1. Dongdong Zhou, Qi Xu, Jiacheng Zhang, Lei Wu, Lauri Kettunen, Zheng Chang, Hongming Xu, and Fengyu Cong. Interpretable Sleep Stage Classification Based on Layer-wise Relevance Propagation. Submitted to IEEE Transactions on Cognitive and Developmental Systems.

Honors and Awards

• Chinese Government Scholarship, from China Scholarship Council, 2019.02 ∼2023.01 (1350Euros/month).
• Short Term Grants, from University of Jyväskylä, 2023.01 ∼2023.03 (1900Euros/month).

Journal Reviewer

• IEEE Journal of Biomedical and Health Informatics.
• IEEE Transactions on Neural Systems and Rehabilitation Engineering.
• Signal, Image and Video Processing.

For more info

More info about me can be found in CV.