PEOPLE

BodyPursuits: Exploring Smooth Pursuit Gaze Interaction Based on Body Motion Targets
Hansen, A.; Makarem, S.; Kunze, K.; Zhou, Y.; Knierim, M. T.; Clarke, C.; Gellersen, H.; Beigl, M.; Röddiger, T.
2025. Proceedings of the 2025 Symposium on Eye Tracking Research and Applications, Art.-Nr.: 3, Association for Computing Machinery (ACM). doi:10.1145/3715669.3723110 

MicroNAS for memory and latency constrained hardware aware neural architecture search in time series classification on microcontrollers
King, T.; Zhou, Y.; Röddiger, T.; Beigl, M.
2025. Scientific Reports, 15 (1), Art.-Nr.: 7575. doi:10.1038/s41598-025-90764-z  

Lightweight Neural Networks for Human Activity Recognition. Dissertation
Zhou, Y.
2024, Dezember 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000177498  

MLP-HAR: Boosting Performance and Efficiency of HAR Models on Edge Devices with Purely Fully Connected Layers
Zhou, Y.; King, T.; Zhao, H.; Huang, Y.; Riedel, T.; Beigl, M.
2024. ISWC ’24: Proceedings of the 2024 ACM International Symposium on Wearable Computers. Ed.: V. Kostakos, 133–139, Association for Computing Machinery (ACM). doi:10.1145/3675095.3676624  

ExTea: An Evolutionary Algorithm-Based Approach for Enhancing Explainability in Time-Series Models
Huang, Y.; Zhou, Y.; Zhao, H.; Fang, L.; Riedel, T.; Beigl, M.
2024. Springer. doi:10.5445/IR/1000171098 

Standardizing Your Training Process for Human Activity Recognition Models – A Comprehensive Review in the Tunable Factors
Huang, Y.; Zhao, H.; Zhou, Y.; Riedel, T.; Beigl, M.
2024. Mobile and Ubiquitous Systems: Computing, Networking and Services – 20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14–17, 2023, Proceedings, Part II. Ed.: A. Zaslavsky, 15–27, Springer Nature Switzerland. doi:10.1007/978-3-031-63992-0_2  

A Survey on Wearable Human Activity Recognition: Innovative Pipeline Development for Enhanced Research and Practice
Huang, Y.; Zhou, Y.; Zhao, H.; Riedel, T.; Beigl, M.
2024. 2024 IEEE International Joint Conference on Neural Networks (IJCNN 2024), Yokohama, 30th June - 5th July 2024, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IJCNN60899.2024.10650060  

Deep Neural Network Pruning with Progressive Regularizer
Zhou, Y.; Zhao, H.; Hefenbrock, M.; Li, S.; Beigl, M.
2024. 2024 IEEE International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, 30 June - 05 July 2024, 1–10, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IJCNN60899.2024.10650997  

AutoAugHAR: Automated Data Augmentation for Sensor-based Human Activity Recognition
Zhou, Y.; Zhao, H.; Huang, Y.; Röddiger, T.; Kurnaz, M.; Riedel, T.; Beigl, M.
2024. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 8 (2), Art.-Nr.: 48. doi:10.1145/3659589  

Enhancing Efficiency in HAR Models: NAS Meets Pruning
Zhou, Y.; King, T.; Huang, Y.; Zhao, H.; Riedel, T.; Röddiger, T.; Beigl, M.
2024. 22nd IEEE International Conference on Pervasive Computing and Communications (PerCom 2024), 33–38, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PerComWorkshops59983.2024.10502894  

Optimizing AutoML for Tiny Edge Systems: A Baldwin-effect Inspired Genetic Algorithm
Huang, Y.; Zhou, Y.; Zhao, H.; Riedel, T.; Beigl, M.
2024. 22nd IEEE International Conference on Pervasive Computing and Communicaitons (PerCom 2024), Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PerComWorkshops59983.2024.10503202  

ExTea: An Evolutionary Algorithm-Based Approach for Enhancing Explainability in Time-Series Models
Huang, Y.; Zhou, Y.; Zhao, H.; Fang, L.; Riedel, T.; Beigl, M.
2024. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track – European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part X. Ed.: A. Bifet, 429–446, Springer Nature Switzerland. doi:10.1007/978-3-031-70381-2_27 

Unsupervised Personalized Deep Learning for Wearable Human Activity Recognition
Huang, Y.; Zhou, Y.; Zhao, H.; Riedel, T.; Beigl, M.
2024. Springer 

McXai: Local Model-Agnostic Explanation As Two Games
Huang, Y.; Schaal, N.; Hefenbrock, M.; Zhou, Y.; Riedel, T.; Beigl, M.
2023. 2023 International Joint Conference on Neural Networks (IJCNN), 01–08, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IJCNN54540.2023.10191756 

Universal Distributional Decision-Based Black-Box Adversarial Attack with Reinforcement Learning
Huang, Y.; Zhou, Y.; Hefenbrock, M.; Riedel, T.; Fang, L.; Beigl, M.
2023. Neural Information Processing – 29th International Conference, ICONIP 2022, Virtual Event, November 22–26, 2022, Proceedings. Part III. Ed.: M. Tanveer, 206 – 215, Springer International Publishing. doi:10.1007/978-3-031-30111-7_18 

Automatic Feature Engineering Through Monte Carlo Tree Search
Huang, Y.; Zhou, Y.; Hefenbrock, M.; Riedel, T.; Fang, L.; Beigl, M.
2023. Machine Learning and Knowledge Discovery in Databases – European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part III. Ed.: M.-R. Amini, 581–598, Springer Nature Switzerland. doi:10.1007/978-3-031-26409-2_35 

Tools and methods for Edge-AI-systems
Schwabe, N.; Zhou, Y.; Hielscher, L.; Röddiger, T.; Riedel, T.; Reiter, S.
2022. at - Automatisierungstechnik, 70 (9), 767–776. doi:10.1515/auto-2022-0023 

TinyHAR: A Lightweight Deep Learning Model Designed for Human Activity Recognition
Zhou, Y.; Zhao, H.; Huang, Y.; Hefenbrock, M.; Riedel, T.; Beigl, M.
2022. International Symposium on Wearable Computers (ISWC’22) , Atlanta, GA and Cambridge, UK, September 11-15, 2022, 89–93, Association for Computing Machinery (ACM). doi:10.1145/3544794.3558467  

Improving Human Activity Recognition Models by Learnable Sparse Wavelet Layer
Zhao, H.; Zhou, Y.; Riedel, T.; Hefenbrock, M.; Beigl, M.
2022. International Symposium on Wearable Computers (ISWC’22) , Atlanta, GA and Cambridge, UK, September 11-15, 2022, 84–88, Association for Computing Machinery (ACM). doi:10.1145/3544794.3558461  

DragTapVib: An On-Skin Electromagnetic Drag, Tap, and Vibration Actuator for Wearable Computing
Fang, L.; Zhu, T.; Pescara, E.; Huang, Y.; Zhou, Y.; Beigl, M.
2022. Augmented Humans 2022. Ed.: M. Mochimaru, 203–211, Association for Computing Machinery (ACM). doi:10.1145/3519391.3519395  

McXai: Local model-agnostic explanation as two games
Huang, Y.; Schaal, N.; Hefenbrock, M.; Zhou, Y.; Riedel, T.; Fang, L.; Beigl, M.
2022 

Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone
Zhou, Y.; Hefenbrock, M.; Huang, Y.; Riedel, T.; Beigl, M.
2021. Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track : European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part IV. Ed.: Y. Dong, 461–477, Springer International Publishing. doi:10.1007/978-3-030-67667-4_28 

Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone
Zhou, Y.; Gao, Y.; Huang, Y.; Hefenbrock, M.; Riedel, T.; Beigl, M.
2020 

NeuralIO: Indoor outdoor detection via multimodal sensor data fusion on smartphones
Wang, L.; Sommer, L.; Riedel, T.; Beigl, M.; Zhou, Y.; Huang, Y.
2020. Science and Technologies for Smart Cities: 5th EAI International Summit, SmartCity360, Braga, Portugal, December 4-6, 2019, Proceedings. Ed.: H. Santos, 127–138, Springer. doi:10.1007/978-3-030-51005-3_13 

NeuralIO: Indoor-Outdoor Detection via Multimodal Sensor Data Fusion on Smartphones
Wang, L.; Sommer, L.; Zhou, Y.; Huang, Y.; Wang, J.; Riedel, T.; Beigl, M.
2020. Sensors and materials, 32 (1), Article: 1. doi:10.18494/SAM.2020.2586