PEOPLE

PRINT-SAFE: Printed Ultra-Low-Cost Electronic X-Design with Scalable Adaptive Fault Endurance
Pal, P.; Gheshlaghi, T.; Zhao, H.; Hefenbrock, M.; Beigl, M.; Tahoori, M. B.
2025. ACM Transactions on Embedded Computing Systems, 24 (5s), 1–22. doi:10.1145/3758096  

Power-Constrained Printed Neuromorphic Hardware Training
Gheshlaghi, T.; Zhao, H.; Pal, P.; Hefenbrock, M.; Beigl, M.; B. Tahoori, M.
2025. 62nd ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, 22-25 June 2025, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DAC63849.2025.11132902  

ADAPT-pNC: Mitigating Device Variability and Sensor Noise in Printed Neuromorphic Circuits with SO Adaptive Learnable Filters
Gheshlaghi, T.; Pal, P.; Zhao, H.; Hefenbrock, M.; Beigl, M.; Tahoori, M. B.
2025. 2025 Design, Automation & Test in Europe Conference (DATE), 1–7, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/DATE64628.2025.10992786 

Neural Evolutionary Architecture Search for Compact Printed Analog Neuromorphic Circuits
Zhao, H.; Pal, P.; Hefenbrock, M.; Wang, Y.; Beigl, M.; Tahoori, M. B.
2025. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1–14. doi:10.1109/TCAD.2024.3524357 

ADAPT-pNC: Mitigating Device Variability and Sensor Noise in Printed Neuromorphic Circuits with SO Adaptive Learnable Filters
Gheshlaghi, T.; Pal, P.; Zhao, H.; Hefenbrock, M.; Beigl, M.; Tahoori, M. B.
2025. Institute of Electrical and Electronics Engineers (IEEE). doi:10.5445/IR/1000178050  

Fit2Ear Dataset
Zhao, H.; Röddiger, T.; Feng, Y.; Beigl, M.
2025, März 5. doi:10.35097/LuEUQApwxQrvGfKm 

Algorithm-Driven Design and Optimization of Printed Analog Neuromorphic Circuits. Dissertation
Zhao, H.
2024, November 5. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000175711  

Neural Architecture Search for Highly Bespoke Robust Printed Neuromorphic Circuits
Pal, P.; Zhao, H.; Gheshlaghi, T.; Hefenbrock, M.; Beigl, M.; Tahoori, M. B.
2024. ACM Digital Library. doi:10.5445/IR/1000172645  

Fit2Ear: Generating Personalized Earplugs from Smartphone Depth Camera Images
Zhao, H.; Röddiger, T.; Yufei, F.; Beigl, M.
2024. ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ’24), 679 – 684, Association for Computing Machinery (ACM). doi:10.1145/3675094.3680525 

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  

Fault Sensitivity Analysis of Printed Bespoke Multilayer Perceptron Classifiers
Pal, P.; Afentaki, F.; Zhao, H.; Saglam, G.; Hefenbrock, M.; Zervakis, G.; Beigl, M.; Tahoori, M. B.
2024. 29th IEEE European Test Symposium (ETS 2024), Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ETS61313.2024.10567964  

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  

Analog Printed Spiking Neuromorphic Circuit
Pal, P.; Zhao, H.; Shatta, M.; Hefenbrock, M.; Mamaghani, S. B.; Nassif, S.; Beigl, M.; B. Tahoori, M.
2024. 2024 Design, Automation and Test in Europe Conference (DATE), 6 S., Institute of Electrical and Electronics Engineers (IEEE)  

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 

Towards Temporal Information Processing – Printed Neuromorphic Circuits with Learnable Filters
Zhao, H.; Pal, P.; Hefenbrock, M.; Beigl, M.; Tahoori, M. B.
2023. 18th ACM International Symposium on Nanoscale Architectures (NANOARCH 2023), Dresden, 18.12 - 20.12.2023), Association for Computing Machinery (ACM). doi:10.5445/IR/1000164433  

Power-Aware Training for Energy-Efficient Printed Neuromorphic Circuits
Zhao, H.; Pal, P.; Hefenbrock, M.; Beigl, M.; Tahoori, M.
2023. 42nd IEEE/ACM International Conference on Computer-Aided Design, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCAD57390.2023.10323917  

Highly-dependable printed neuromorphic circuits based on additive manufacturing
Zhao, H.; Hefenbrock, M.; Beigl, M.; Tahoori, M. B.
2023. Flexible and Printed Electronics, 8 (8), Art.-Nr.: 025018. doi:10.1088/2058-8585/acd8cd  

Highly Bespoke Robust Printed Neuromorphic Circuits
Zhao, H.; Sapui, B.; Hefenbrock, M.; Yang, Z.; Beigl, M.; Tahoori, M. B.
2023. 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), Antwerp, Belgium,17-19 April 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/DATE56975.2023.10137298  

Split Additive Manufacturing for Printed Neuromorphic Circuits
Zhao, H.; Hefenbrock, M.; Beigl, M.; Tahoori, M. B.
2023. 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), Antwerp, Belgium, 17-19 April 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/DATE56975.2023.10136891  

Aging-Aware Training for Printed Neuromorphic Circuits
Zhao, H.; Hefenbrock, M.; Beigl, M.; Tahoori, M. B.
2022. International Conference on Computer Aided Design (ICCAD ’22), October 30-November 3, 2022, San Diego, CA, USA, Art.-No.: 38, Association for Computing Machinery (ACM). doi:10.1145/3508352.3549411  

Printed Electrodermal Activity Sensor with Optimized Filter for Stress Detection
Zhao, H.; Scholz, A.; Beigl, M.; Ni, S.; Singaraju, S. A.; Aghassi-Hagmann, J.
2022. International Symposium on Wearable Computers (ISWC’22) , Atlanta, GA and Cambridge, UK, September 11-15, 2022, 112–114, Association for Computing Machinery (ACM). doi:10.1145/3544794.3558479  

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  

Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena
Röddiger, T.; Clarke, C.; Breitling, P.; Schneegans, T.; Zhao, H.; Gellersen, H.; Beigl, M.
2022. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 6 (3), Article 135. doi:10.1145/3550314  

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  

AirCase: Earable Charging Case with Air Quality Monitoring and Soundscape Sonification
Zhao, H.; Roddiger, T.; Beigl, M.
2021. Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers: September 21-25, 2021 ; Virtual Event, 180–184, Association for Computing Machinery (ACM). doi:10.1145/3460418.3479329 

Kalman Filtered Compressive Sensing Using Pseudo-Measurements
Zhao, H.; Funk, C.; Noack, B.; Hanebeck, U. D.; Beigl, M.
2021. Proceedings of the 2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2021), 1–8, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/MFI52462.2021.9591186 

Zustandsrekonstruktion mit wenigen Messungen durch Kombination von Kalman-Filterung und Compressive-Sensing. Masterarbeit
Zhao, H.
2020, November 15. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000158992  

Magnetisches Tracking-System: Projektarbeit
Zhao, H.
2020. doi:10.5445/IR/1000165240