Chen Zhenghua

Chen Zhenghua

Scientist at I2R, A*STAR, Singapore

Publications (Google Scholar Profile)

Book & Book Chapter

  1. Generalization with Deep Learning: for improvement on Sensing Capability
    Zhenghua Chen, Min Wu, and Xiaoli Li,
    World Scientific, 2021.
  2. Deep Learning for Human Activity Recognition
    Xiaoli Li, Min Wu, Zhenghua Chen, and Le Zhang,
    Springer, 2021.
  3. Deep Learning for Building Occupancy Estimation Using Environmental Sensors
    Zhenghua Chen, Chaoyang Jiang, Mustafa K. Masood, Yeng Chai Soh, Min Wu, Xiaoli Li,
    In “Deep Learning: Algorithms and Applications”, pp. 335-357. Springer, Cham, 2020.

Journal Publications (* represents Corresponding Author)

Year 2024

  1. Wei Cui, Keyu Wu, Min Wu, Xiaoli Li, and Zhenghua Chen*. “WiCAU: Comprehensive Partial Adaptation with Uncertainty-aware for WiFi-based Cross-environment Activity Recognition” IEEE Transactions on Instrumentation & Measurement, accepted, to appear (2024).
  2. Yuecong Xu, Jianfei Yang, Haozhi Cao, Min Wu, Xiaoli Li, Lihua Xie, and Zhenghua Chen*. “Leveraging Endo- and Exo-Temporal Regularization for Black-box Video Domain Adaptation” TMLR, accepted, to appear (2024).
  3. Xiaoyao Zheng, Xingwang Li, Zhenghua Chen, Liping Sun, Qingying Yu, Liangmin Guo, and Yonglong Luo. “Enhanced Self-Attention Mechanism for Long and Short Term Sequential Recommendation Models”, IEEE Transactions on Emerging Topics in Computational Intelligence, accepted, to appear (2024).
  4. Cunyi Yin, Xiren Miao, Jing Chen, Hao Jiang, Jianfei Yang, Yunjiao Zhou, Min Wu, and Zhenghua Chen. “PowerSkel: A Device-Free Framework Using CSI Signal for Human Skeleton Estimation in Power Station” IEEE Internet of Things Journal, accepted, to appear (2024).

Year 2023

  1. Yucheng Wang, Min Wu, Ruibing Jin, Xiaoli Li, Lihua Xie, and Zhenghua Chen*. “Local-Global Correlation Fusion based Graph Neural Network for Remaining Useful Life Prediction” IEEE Transactions on Neural Networks and Learning Systems, accepted, to appear (2023).
  2. Qing Xu, Keyu Wu, Min Wu, Kezhi Mao, Xiaoli Li, and Zhenghua Chen*.. “Reinforced Knowledge Distillation for Time Series Regression” IEEE Transactions on Artificial Intelligence, accepted, to appear (2023).
  3. Wenjun Sun, Ruqiang Yan, Ruibing Jin, Rui Zhao and Zhenghua Chen. “Federated Model Alignment via Data-Free Knowledge Distillation for Machine Fault Diagnosis” IEEE Transactions on Instrumentation and Measurement, accepted, to appear (2023).
  4. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, and Cuntai Guan. “Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification.” IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted, to appear (2023).
  5. Xu Yuecong, Cao Haozhi, Yin Jianxiong, Zhenghua Chen, Li Xiaoli, Li Zhengguo, Xu Qianwen, Yang Jianfei. “Going Deeper into Recognizing Actions in Dark Environments: A Comprehensive Benchmark Study” International Journal of Computer Vision, accepted, to appear (2023).
  6. Wenjun Sun, Ruqiang Yan, Ruibing Jin, Jiawen Xu, Yuan Yang, and Zhenghua Chen. “LiteFormer: a lightweight and efficient Transformer for rotating machine fault diagnosis” IEEE Transactions on Reliability, accepted, to appear (2023).
  7. Qing Xu, Min Wu, Xiaoli Li, Kezhi Mao, and Zhenghua Chen*,. “Contrastive Distillation with Regularized Knowledge for Deep Model Compression on Sensor-based Human Activity Recognition.” IEEE Transactions on Industrial Cyber-Physical Systems, accepted, to appear (2023).
  8. Hongxiang Gao, Xingyao Wang, Zhenghua Chen*, Min Wu, Jianqing Li, and Chengyu Liu. “ECG-CL: A Comprehensive Electrocardiogram Interpretation Method Based on Continual Learning.” IEEE Journal of Biomedical and Health Informatics, accepted, to appear (2023).
  9. Shijia Liu, Zhenghua Chen, Min Wu, Hao Wang, Bin Xing and Liangyin Chen. “Generalizing Wireless Cross-Multiple-Factor Gesture Recognition to Unseen Domains.” IEEE Transactions on Mobile Computing, accepted, to appear (2023).
  10. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, and Xiaoli Li. “CoTMix: Contrastive Domain Adaptation for Time-Series via Temporal Mixup.” IEEE Transactions on Artificial Intelligence, accepted, to appear (2023).
  11. Shijia Liu, Zhenghua Chen, Min Wu, Chang Liu, and Liangyin Chen. “WiSR: Wireless Domain Generalization Based on Style Randomization.” IEEE Transactions on Mobile Computing, accepted, to appear (2023).
  12. Zhenghua Chen, Min Wu, Alvin Chan, Xiaoli Li and Yew-Soon Ong. “A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges.” IEEE Computational Intelligence Magazine, accepted, to appear (2023).
  13. Mohamed Ragab, Emadeldeen Eldele, Chuan-Sheng Foo, Zhenghua Chen*, Min Wu, Chee-Keong Kwoh, and Xiaoli Li. “ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data.” ACM Transactions on Knowledge Discovery from Data, accepted, to appear (2023).
  14. Yuecong Xu, Jianfei Yang, Haozhi Cao, Keyu Wu, Min Wu, Zhengguo Li and Zhenghua Chen*. “Multi-Source Video Domain Adaptation with Temporal Attentive Moment Alignment Network.” IEEE Transactions on Circuits and Systems for Video Technology, accepted, to appear (2023).
  15. Yucheng Wang, Min Wu, Xiaoli Li, Lihua Xie and Zhenghua Chen*. “Multivariate Time Series Representation Learning via Hierarchical Correlation Pooling Boosted Graph Neural Network.” IEEE Transactions on Artificial Intelligence, accepted, to appear (2023).
  16. Ruibing Jin, Duo Zhou, Min Wu, Xiaoli Li and Zhenghua Chen*. “An Adaptive and Dynamical Neural Network for Machine Remaining Useful Life Prediction.” IEEE Transactions on Industrial Informatics (2023).
  17. Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, and Zhenghua Chen. “Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling.” IEEE Transactions on Knowledge and Data Engineering, accepted, to appear (2023).
  18. Xinyu Liu, Xiren Miao, Hao Jiang, Jing Chen, Min Wu and Zhenghua Chen. “Tower Masking MIM: A Self-supervised Pretraining Method for Power Line Inspection.” IEEE Transactions on Industrial Informatics, accepted, to appear (2023).
  19. Emad Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, and Xiaoli Li, “Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, accepted, to appear (2023).
  20. Le Zhang, Wei Cui, Bing Li, Zhenghua Chen, Min Wu, Teo Sin Gee, “Privacy-Preserving Cross-Environment Human Activity Recognition.” IEEE Transactions on Cybernetics 53, no. 3 (2023): 1765-1775
  21. Xu Qing, Min Wu, Edwin Khoo, Zhenghua Chen*, and Xiaoli Li. “A Hybrid Ensemble Deep Learning Approach for Early Prediction of Battery Remaining Useful Life.” IEEE/CAA Journal of Automatica Sinica, 10, no. 1 (2023): 177-187
  22. Hongxiang Gao, Min Wu, Zhenghua Chen, Yuwen Li, Xingyao Wang, Shan An, Jianqing Li and Chengyu Liu, “SSA-ICL: Multi-domain Adaptive Attention with Intra-dataset Continual Learning for Facial Expression Recognition” Neural Networks 158 (2023): 228-238.

Year 2022

  1. Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen*, Min Wu, Chee-Keong Kwoh, and Xiaoli Li. “Self-supervised Autoregressive Domain Adaptation for Time Series Data.” IEEE Transactions on Neural Networks and Learning Systems, accepted, to appear (2022).
  2. Keyu Wu, Min Wu, Zhenghua Chen*, Ruibing Jin, Wei Cui, Zhiguang Cao and Xiaoli. “Reinforced Adaptation Network for Partial Domain Adaptation.” IEEE Transactions on Circuits and Systems for Video Technology, accepted, to appear (2022).
  3. Yubo Hou, Teo Sin Gee, Zhenghua Chen, Min Wu, Kwoh Chee-Keong, and Tram Truong-Huu, “Handling Labeled Data Insufficiency: Semi-supervised Learning with Self-Training Mixup Decision Tree for Classification of Network Attacking Traffic” IEEE Transactions on Dependable and Secure Computing, accepted, to appear (2022).
  4. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, and Cuntai Guan, “ADAST: Attentive Cross-Domain EEG-Based Sleep Staging Framework With Iterative Self-Training” IEEE Transactions on Emerging Topics in Computational Intelligence, accepted, to appear (2022).
  5. Devki Nandan Jha, Zhenghua Chen, Shudong Liu, Min Wu, Jiahan Zhang, Graham Morgan, Rajiv Ranjan, and Xiaoli Li, “A hybrid accuracy- and energy-aware human activity recognition model in IoT environment”, IEEE Transactions on Sustainable Computing, accepted, to appear (2022).
  6. Xinyu Liu, Xiren Miao, Hao Jiang, Jing Chen, and Zhenghua Chen, “Fault Diagnosis in Power Line Inspection Using Normalized Multihierarchy Embedding Matching.” IEEE Transactions on Instrumentation and Measurement, accepted, to appear (2022).
  7. Xinyu Liu, Xiren Miao, Hao Jiang, Jing Chen, and Zhenghua Chen, “Component Detection for Power Line Inspection Using a Graph-based Relation Guiding Network.” IEEE Transactions on Industrial Informatics, accepted, to appear (2022).
  8. Yuecong Xu, Haozhi Cao, Kezhi Mao, Zhenghua Chen, Lihua Xie, and, Jianfei Yang, “Aligning Correlation Information for Domain Adaptation in Action Recognition,” IEEE Transactions on Neural Networks and Learning Systems, accepted, to appear (2022).
  9. Ruibing Jin, Zhenghua Chen*, Keyu Wu, Min Wu, Xiaoli Li, and Ruqiang Yan. “Bi-LSTM-Based Two-Stream Network for Machine Remaining Useful Life Prediction.” IEEE Transactions on Instrumentation and Measurement, 71 (2022): 1-10.
  10. Ruibing Jin, Min Wu, Keyu Wu, Kaizhou Gao, Zhenghua Chen*, and Xiaoli Li. “Position Encoding based Convolutional Neural Networks for Machine Remaining Useful Life Prediction,” IEEE/CAA Journal of Automatica Sinica 9, no. 8 (2022): 1427-1439.
  11. Mohamed Ragab, Wenyu Zhang, Emadeldeen Eldele, Min Wu, Zhenghua Chen*, Chee-Keong Kwoh, Xiaoli Li, “Conditional Contrastive Domain Generalization for Fault Diagnosis,” IEEE Transactions on Instrumentation and Measurement, 71 (2022): 1-12.
  12. Wei Cui, Le Zhang, Bing Li, Zhenghua Chen, Min Wu, Xiaoli Li, and Jiawen Kang, “Semi-Supervised Deep Adversarial Forest for Cross-Environment Localization.” IEEE Transactions on Vehicular Technology 71, no. 9 (2022): 10215-10219
  13. Qing Xu, Zhenghua Chen*, Mohamed Ragab, Chao Wang, Min Wu, and Xiaoli Li, “Contrastive Adversarial Knowledge Distillation for Deep Model Compression in Time-Series Regression Tasks”, Neurocomputing 485 (2022): 242-251.
  14. Yaping Fu, Yushuang Hou, Zhenghua Chen, Xujin Pu, Kaizhou Gao, Ali Sadollah, “Modelling and Scheduling Integration of Distributed Production and Distribution Problems via Black Widow Optimization” Swarm and Evolutionary Computation 68 (2022): 101015.

Year 2021

  1. Qing Xu, Zhenghua Chen*, Keyu Wu, Chao Wang, Min Wu, and Xiaoli Li, “KDnet-RUL: A Knowledge Distillation Framework to Compress Deep Neural Networks for Machine Remaining Useful Life Prediction,” IEEE Transactions on Industrial Electronics 69, no. 2 (2021): 2022-2032.
  2. Chaoyi Zhu, Zhenghua Chen*, Rui Zhao, Jinjiang Wang, and Ruqiang Yan, “Decoupled Feature-Temporal CNN: Explaining Deep Learning-Based Machine Health Monitoring”, IEEE Transactions on Instrumentation and Measurement 70 (2021): 1-13.
  3. Zhenghua Chen, Min Wu, Rui Zhao, Feri Guretno, Ruqiang Yan and Xiaoli Li, “Machine Remaining Useful Life Prediction via an Attention Based Deep Learning Approach,” IEEE Transactions on Industrial Electronics 68, no. 3 (2021): 2521-2531.
  4. Mohamed Ragab, Zhenghua Chen*, Min Wu, Haoliang Li, Chee-Keong Kwoh, Ruqian Yan, Xiaoli Li, “Adversarial Multiple-Target Domain Adaptation for Fault Classification”, IEEE Transactions on Instrumentation and Measurement 70 (2021): 1-11.
  5. Jie Ding, Changyun Wen, Guoqi Li, and Zhenghua Chen, “Key Nodes Selection in Controlling Complex Networks via Convex Optimization.” IEEE Transactions on Cybernetics 51, no. 1 (2021), 52-63.
  6. Emadeldeen Eldele, Zhenghua Chen, Chengyu Liu, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan, “An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG”, IEEE Transactions on Neural Systems and Rehabilitation Engineering 29 (2021): 809-818.
  7. Jiyan Wu, Min Wu, Zhenghua Chen, Xiaoli Li and Ruqiang Yan, “Degradation-Aware Remaining Useful Life Prediction With LSTM Autoencoder.” IEEE Transactions on Instrumentation and Measurement 70 (2021): 1-10.
  8. Mohamed Ragab, Zhenghua Chen*, Min Wu, Chee-Keong Kwoh, Ruqian Yan, Xiaoli Li, “Attention-Based Sequence to Sequence Model for Machine Remaining Useful Life Prediction,” Neurocomputing 466 (2021): 58-68.
  9. Wei Cui, Bing Li, Le Zhang, and Zhenghua Chen, “Device-free single-user activity recognition using diversified deep ensemble learning” Applied Soft Computing, 102 (2021): 107066.
  10. Yu Wang, Wei Cui, Nhu Khue Vuong, Zhenghua Chen, Yu Zhou, Min Wu, “Feature selection and domain adaptation for cross-machine product quality prediction” Journal of Intelligent Manufacturing (2021): 1-12.
  11. Zhiguang Cao, Tingbo Liao, Wen Song, Zhenghua Chen, and Chongshou Li, “Detecting the shuttlecock for a badminton robot: A YOLO based approach” Expert Systems with Applications 164 (2021): 113833.
  12. Jiyan Wu, Min Wu, Zhenghua Chen, Xiaoli Li and Ruqiang Yan, “A Joint Classification-Regression Method for Multi-Stage Remaining Useful Life Prediction.” Journal of Manufacturing Systems 58 (2021): 109-119.

Year 2020

  1. Mohamed Ragab, Zhenghua Chen*, Min Wu, Foo Chuan Sheng, Chee-Keong Kwoh, Ruqian Yan, Xiaoli Li, “Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction,” IEEE Transactions on Industrial Informatics 17, no. 8 (2020): 5239-5249.
  2. Zhenghua Chen, Yanbing Yang, Chaoyang Jiang, Jie Hao and Le Zhang, “Light Sensor Based Occupancy Estimation via Bayes Filter with Neural Networks,” IEEE Transactions on Industrial Electronics 67, no. 7 (2020), 5787-5797.
  3. Zhenghua Chen, Min Wu, Kaizhou Gao, Jiyan Wu, Jie Ding, Zeng Zeng and Xiaoli Li, “A Novel Ensemble Deep Learning Approach for Sleep-Wake Detection Using Heart Rate Variability and Acceleration,” IEEE Transactions on Emerging Topics in Computational Intelligence 5, no. 5 (2020): 803-812.
  4. Zhenghua Chen, Chaoyang Jiang, Shili Xiang, Jie Ding, Min Wu and Xiaoli Li, “Smartphone Sensor Based Human Activity Recognition Using Feature Fusion and Maximum Full A Posteriori,” IEEE Transactions on Instrumentation and Measurement 69, no. 7 (2020): 3992-4001.
  5. Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Zhenghua Chen, Le Zhang, Xuexi Zhang, “Using Reinforcement Learning to Minimize the Probability of Delay Occurrence in Transportation” IEEE Transactions on Vehicular Technology 69, no. 3 (2020): 2424-2436.
  6. Zhenghua Chen, Min Wu, Chengyu Liu and Xiaoli Li, “An Attention Based CNN-LSTM Approach for Sleep-Wake Detection with Heterogeneous Sensors,” IEEE Journal of Biomedical and Health Informatics 25, no. 9 (2020): 3270-3277
  7. Zhenghua Chen, Han Zou, Jiangei Yang, Hao Jiang and Lihua Xie “WiFi Fingerprinting Indoor Localization Using Local Feature based Deep LSTM,” IEEE Systems Journal 14, no. 2 (2020):
  8. Le Zhang, Zhenghua Chen, Bing Li, Cen Chen, Zhiguang Cao, and Kaizhou Gao, “WiFi-Based Indoor Robot Positioning Using Deep Fuzzy Forests,” IEEE Internet of Things Journal 7, no. 11 (2020): 10773-10781.
  9. Jianfei Yang, Han Zou, Shuxin Cao, Zhenghua Chen, and Lihua Xie. “MobileDA: Towards Edge Domain Adaptation” IEEE Internet of Things Journal 7, no. 8 (2020): 6909-6918.
  10. Zhenghua Chen, Mohamed Ibrahim Alhajri Min Wu and Raed Shubair, “A Novel Real-Time Deep Learning Approach for Indoor Localization Based on RF Environment Identification,” IEEE Sensors Letter, 4, no. 6 (2020): 1-4.
  11. Chaoyang Jiang, Zhenghua Chen*, Mustafa K. Masood, Rong Su and Yeng Chai Soh, “Bayesian filtering for building occupancy estimation from carbon dioxide concentration” Energy and Buildings 206 (2020): 109566.

Before Year 2020

  1. Zhenghua Chen, Le Zhang, Chaoyang Jiang, Zhiguang Cao and Wei Cui, “WiFi CSI Based Passive Human Activity Recognition Using Attention Based BLSTM,” IEEE Transactions on Mobile Computing 18, no. 11 (2019): 2714-2724.
  2. Qingchang Zhu, Zhenghua Chen*, and Yeng Chai Soh “A Novel Semi-supervised Deep Learning Method for Human Activity Recognition,” IEEE Transactions on Industrial Informatics 15, no. 7 (2019): 3821-3830.
  3. Chaoyang Jiang, Zhenghua Chen*, Rong Su and Yeng Chai Soh, “Group Greedy Methods for Sensor Placement” IEEE Transactions on Signal Processing 67, no. 9 (2019): 2249-2262.
  4. Zhenghua Chen, Chaoyang Jiang and Lihua Xie, “A Novel Ensemble ELM for Human Activity Recognition Using Smartphone Sensors,” IEEE Transactions on Industrial Informatics 15, no. 5 (2019): 2691 - 2699.
  5. Rui Zhao, Ruqiang Yan, Zhenghua Chen, Kezhi Mao and Robert X.Gao, ”Deep Learning and Its Applications to Machine Health Monitoring” Mechanical Systems and Signal Processing, 115 (2019): 213-237.
  6. Kaizhou Gao, Zhiguang Cao, Le Zhang, Zhenghua Chen, Yuyan Han, Quanke Pan, “A review on swarm intelligence and evolutionary algorithms for solving flexible job shop scheduling problems” IEEE/CAA Journal of Automatica Sinica, 6 (4), 904-916, 2019.
  7. Zhenghua Chen, Le Zhang, Zhiguang Cao, and Jing Guo “Distilling the Knowledge from Handcrafted Features for Human Activity Recognition,” IEEE Transactions on Industrial Informatics, 14, no. 10 (2018): 4334-4342.
  8. Zhenghua Chen and Chaoyang Jiang, “Building occupancy modeling using generative adversarial network,” Energy and Buildings 174 (2018): 372-379.
  9. Zhenghua Chen, Chaoyang Jiang and Lihua Xie, “Building Occupancy Estimation and Detection: A Review,” Energy and Buildings 169 (2018): 260-270.
  10. Zhenghua Chen, Rui Zhao, Qingchang Zhu, Mustafa K. Masood, Yeng Chai Soh and Kezhi Mao, “Building Occupancy Estimation with Environmental Sensors via CDBLSTM,” IEEE Transactions on Industrial Electronics 64, no. 12 (2017): 9549-9559.
  11. Zhenghua Chen, Qingchang Zhu, Yeng Chai Soh and Le Zhang, “Robust Human Activity Recognition Using Smartphone Sensors via CT-PCA and Online SVM,” IEEE Transactions on Industrial Informatics 13, no. 6 (2017): 3070-3080.
  12. Zhenghua Chen, Qingchang Zhu, Mustafa K. Masood and Yeng Chai Soh, “Environmental Sensors based Occupancy Estimation in Buildings via IHMM-MLR,” IEEE Transactions on Industrial Informatics 13, no. 5 (2017): 2184-2193.
  13. Qingchang Zhu, Zhenghua Chen, Mustafa K. Masood and Yeng Chai Soh,”Occupancy estimation with environmental sensing via non-iterative LRF feature learning in time and frequency domains” Energy and Buildings 141 (2017): 125-133
  14. Zhenghua Chen, Qingchang Zhu and Yeng Chai Soh, “Smartphone Inertial Sensor Based Indoor Localization and Tracking with iBeacon Corrections,” IEEE Transactions on Industrial Informatics 12, no. 4 (2016): 1540-1549.
  15. Zhenghua Chen, Mustafa K. Masood and Yeng Chai Soh, “A fusion framework based occupancy estimation with environmental parameters in office buildings,” Energy and Buildings 133 (2016): 790-798.
  16. Zhenghua Chen and Yeng Chai Soh, “Comparing model-based and data-driven approaches for regular occupancy prediction in commercial buildings,” Journal of Building Performance Simulation, (2016): 1-9.
  17. Zhenghua Chen, Jinming Xu and Yeng Chai Soh, “Modeling regular occupancy in commercial buildings using stochastic models,” Energy and Buildings 103 (2015): 216-223.

Conference Publications

  1. Graph Contextual Contrasting for Multivariate Time Series Classification
    Yucheng Wang, Yuecong Xu, Jianfei Yang, Min Wu, Xiaoli Li, Lihua Xie and Zhenghua Chen*,
    AAAI 2024 (Acceptance Rate: 23.75%)

  2. Fully-Connected Spatial-Temporal Graph for Multivariate Time Series Data
    Yucheng Wang, Yuecong Xu, Jianfei Yang, Min Wu, Xiaoli Li, Lihua Xie and Zhenghua Chen*,
    AAAI 2024 (Acceptance Rate: 23.75%)

  3. Augmenting and Aligning Snippets for Few-Shot Video Domain Adaptation
    Yuecong Xu, Jianfei Yang, Yunjiao Zhou, Min Wu, Xiaoli Li, and Zhenghua Chen*,
    ICCV 2023

  4. Source-Free Domain Adaptation with Temporal Imputation for Time Series Data
    Mohamed Ragab, Emadeldeen Eldele, Chuan Sheng Foo, Min Wu, Xiaoli Li, and Zhenghua Chen*,
    KDD 2023 (Acceptance Rate: 22%)

  5. Distilling Universal and Joint Knowledge for Cross-Domain Model Compression on Time Series Data
    Qing Xu, Min Wu, Xiaoli Li, Kezhi Mao, and Zhenghua Chen*,
    IJCAI 2023 (Acceptance Rate: 15%)

  6. SEnsor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation
    Yucheng Wang, Yuecong Xu, Jianfei Yang, Zhenghua Chen*, Min Wu, Xiaoli Li and Lihua Xie,
    AAAI 2023 (Acceptance Rate: 19.6%)

  7. Multi-task Self Supervised Adaptation for Reinforcement Learning
    Keyu Wu, Zhenghua Chen*, Min Wu, Shili Xiang, Ruibing Jin, Le Zhang and Xiaoli Li,
    IEEE ICIEA 2022 (Best Paper Award)

  8. Cost-effective Elderly Fall Detection with Symmetry Transformer Networks
    Bing Li, Wei Cui, Yanru Chen, Joey Tianyi Zhou, Zhenghua Chen, Yuli Li, and Min Wu,
    IEEE SmartCity 2022 (Best Paper Award)

  9. Source-Free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition
    Yuecong Xu, Jianfei Yang, Haozhi Cao, Keyu Wu, Min Wu, and Zhenghua Chen*,
    ECCV 2022 Code is available here.

  10. Generalizing Reinforcement Learning through Fusing Self-Supervised Learning into Intrinsic Motivation
    Keyu Wu, Min Wu, Zhenghua Chen*, Yuecong Xu, Xiaoli Li,
    AAAI 2022

  11. Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer
    Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang
    NeurIPS 2021, Code is available here.

  12. Deep Reinforcement Learning Boosted Partial Domain Adaptation
    Keyu Wu, Min Wu, Jianfei Yang, Zhenghua Chen*, Zhengguo Li and Xiaoli Li,
    IJCAI 2021

  13. Time-Series Representation Learning via Temporal and Contextual Contrasting
    Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li and Cuntai Guan,
    IJCAI 2021 Code is available here.

  14. A Multi-Stage Progressive Learning Strategy for COVID-19 Diagnosis using Chest Computed Tomography with Imbalanced Data
    Zaifeng Yang, Yubo Hou, Zhenghua Chen, Le Zhang, and Jie Chen,
    ICASSP 2021.

  15. Two-Stream Convolution Augmented Transformer for Human Activity Recognition
    Bing Li, Wei Cui, Wei Wang, Le Zhang, Zhenghua Chen, and Min Wu
    AAAI 2021, Code is available here.

  16. A Deep Learning Approach for Sleep-Wake Detection from HRV and Accelerometer Data
    Zhenghua Chen, Min Wu, Jiyan Wu, Jie Ding, Zeng Zeng, Karl Surmacz, Xiaoli Li,
    IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2019.

  17. Indoor localization using smartphone sensors and ibeacons
    Zhenghua Chen, Qingchang Zhu, Hao Jiang, Yeng Chai Soh,
    Industrial Electronics and Applications (ICIEA), 2015 IEEE 10th Conference on, pp. 1723-1728. IEEE, 2015.

  18. Modeling building occupancy using a novel inhomogeneous Markov chain approach
    Zhenghua Chen, Yeng Chai Soh,
    Automation Science and Engineering (CASE), 2014 IEEE International Conference on, pp. 1079-1084. IEEE, 2014.

  19. Building occupancy detection from carbon-dioxide and motion sensors
    Chaoyang Jiang, Zhenghua Chen, Lih Chieh Png, Korkut Bekiroglu, Seshadhri Srinivasan, Rong Su,
    Control, Automation, Robotics and Vision (ICARCV), 2018 IEEE International Conference on, 2018.

  20. Accurate Indoor Localization and Tracking Using Mobile Phone Inertial Sensor, WiFi and iBeacon
    Han Zou, Zhenghua Chen, Hao Jiang, Lihua Xie, Costas Spanos,
    Inertial Sensors and Systems (INERTIAL), 2017 IEEE International Symposium on, pp. 1-4. IEEE, 2017.

  21. Using unlabeled acoustic data with locality-constrained linear coding for energy-related activity recognition in buildings
    Qingchang Zhu, Zhenghua Chen, Yeng Chai Soh,
    Automation Science and Engineering (CASE), 2015 IEEE International Conference on, pp. 174-179. IEEE, 2015.

  22. Smartphone-based Human Activity Recognition in buildings using Locality-constrained Linear Coding
    Qingchang Zhu, Zhenghua Chen, Yeng Chai Soh,
    Industrial Electronics and Applications (ICIEA), 2015 IEEE 10th Conference on, pp. 214-219. IEEE, 2015.