I am Yu Sha (🦈沙毓🦈), now a PhD candidate at Xidian University, where I was co-advised by Prof. Shuiping Gou
and Prof. Bo Liu. In addition, I am a member of Xidian-FIAS Joint Research Center (XFJRC) and Giersch Science Center (GSC). My research interests includes AI in Industry (especially AI for acoustic damage detection and diagnosis, etc.),
AI in Physics (especially traditional filters with deep learning), AI in Industry (especially cavitation intensity recognition and detection) and Deep Learning (especially Knowledge-guided DL, generative models and attention mechanisms). During 2020 to 2022, I am a PhD vising student in "Deepthinkers" group at
Frankfurt Institute for Advanced Studies (FIAS), where I was co-advised by Prof. Horst Stöcker
and Prof. Kai Zhou. Before that, I received the B.Sc degree from Lanzhou University of Technology in 2019.
09/2020 - 10/2022, PhD Vising Student, Frankfurt Institute for Advanced Studies (FIAS), Germany.
📖 Educations
09/2019 - now, School of Artificial Intelligence, Xidian University (XDU), China.
09/2015 - 06/2019, School of Science, Lanzhou University of Technology (LUT), China.
📚 Publications
Papers:
KDD 2024 (Oral&Poster)
Hierarchical Knowledge Guided Fault Intensity Diagnosis of Complex Industrial Systems Yu Sha, Shuiping Gou, Bo Liu, Ningtao Liu, Johannes Faber, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou
SIGKDD 2024 | CCF: A |
Paper |
Code
The paper explores hierarchical Knowledge of labels with GCN.
The paper presents the Hierarchical Knowledge Correlation Matrix.
The sound cavitation datasets provided by SAMSON AG.
ESWA 2024
Hierarchical Cavitation Intensity Recognition Using Sub-Master Transition Network-based Acoustic Signals in Pipeline Systems
Shuiping Gou, Yu Sha*, Bo Liu, Ningtao Liu, Johannes Faber, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou (If you know, you know)
Expert Systems with Applications | 2024 |SCI: 1-Top |
Paper
The paper presents a two-stage hierarchical classification network
The paper proposes a hierarchical label tree.
The sound cavitation datasets provided by SAMSON AG.
KDD 2022 (Poster)
Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space Yu Sha, Shuiping Gou, Johannes Faber, Bo Liu, Wei Li, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou
SIGKDD 2022 | CCF: A |
Paper |
Code
The paper proposes a global filter layer based on a 1D FFT global filter for long-term interactions.
The paper extends the capability of discriminating real against fake signals to differentiating between local and regional reconstructions.
The paper designs a novel balanceable detection strategy.
EAAI 2022
A multi-task learning for cavitation detection and cavitation intensity recognition of valve acoustic signals Yu Sha, Johannes Faber, Shuiping Gou, Bo Liu, Wei Li, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou
Engineering Applications of Artificial Intelligence | 2022 | SCI: 2-Top |
Paper |
Code
The paper regards cavitation detection and cavitation intensity recognition as a multi-task learning.
The 1-D Double Hierarchical Residual Blocks with large kernel are proposed as an automatic feature extractor.
The sound cavitation datasets provided by SAMSON AG.
Measurement 2022
An acoustic signal cavitation detection framework based on XGBoost with adaptive selection feature engineering Yu Sha, Johannes Faber, Shuiping Gou, Bo Liu, Wei Li, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou
Measurement | 2022 | SCI: 2-Top |
Paper |
Code
The paper proposes a adaptive feature aggregation module.
The paper presents a adaptive feature crosses module.
The sound cavitation datasets provided by SAMSON AG.
Front. Neurosci. 2025
Dynamic Spatio-Temporal Pruning for Efficient Spiking Neural Networks
Shuiping Gou, Jiahui Fu, Yu Sha, Zhen Cao, Zhang Guo, Jason K. Eshraghian, Ruimin Li, Licheng Jiao
Frontiers in Neuroscience | 2025 |SCI: 2-Top |
Paper
A spatio-temporal pruning algorithm is proposed to reduce the temporal redundancy,
Spatial pruning leverages global and inter-layer parameter statistics to minimize model degradation under extreme sparsity.
JBHI 2024
Self-supervised, Non-Contact Heartbeat Detection Based on Ballistocardiograms utilizing Physiological Information Guidance
Changezhe Jiao, Aoyu Yang, Hantao Zhao, Ruhan Yi, Shuiping Gou, Yu Sha, Wanshun Wen, Licheng Jiao, Marjorie Skubic
IEEE Journal of Biomedical and Health Informatics | 2024 |SCI: 1-Top |
Paper
A non-contact, self-supervised heart rate detection method based on physiological information,
The paper proposes a heartbeat mapping algorithm based on Bidirectional Long Short-Term Memory Network.
MIR 2023
Prioritization Hindsight Experience based on Spatial Position Attention for Robots
Ye Yuan, Yu Sha, Feixiang Sun, Haofan Lu, Shuiping Gou, Jie Luo
Machine Intelligence Research | 2025 | SCI: 4 |
Paper
The paper proposes a spatial position attention module for the existing HER framework.
The paper presents a theoretical analysis of the total spatial position distance of manipulated object.
Eight robotic manipulation tasks in the Fetch and Hand robot environments of OpenAI Gym.
DH3D 2022
Phase Retrieval for Terahertz Holography with Physics-Informed Deep Learning
Mingjun Xiang, Lingxiao Wang, Yu Sha, Hui Yuan, Kai Zhou, Hartmut G Roskos
Digital Holography and Three-Dimensional Imaging | 2022 | EI |
Paper
The paper proposes a two novel phase retrieval methods for THz holography.
The paper employs unsupervised learning and supervised learning based on the MNIST dataset.
AIIG 2022
A study on small magnitude seismic phase identification using 1D deep residual neural network
Wei Li, Megha Chakraborty, Yu Sha, Kai Zhou, Johannes Faber, Georg Rümpker, Horst Stöcker, Nishtha Srivastava
Artificial Intelligence in Geosciences | 2022 | SCI: 2 |
Paper |
Code
1D deep Residual Neural Network for tackling the problem of seismic signal detection and phase identification.
The method is trained and tested on the dataset recorded by the Southern California Seismic Network.
The model generalizability is also tested further on the STanford EArthquake Dataset.
Deep Learning-based Small Magnitude Earthquake Detection and Seismic Phase Classification
Wei Li, Yu Sha, Kai Zhou, Johannes Faber, Georg Rümpker, Horst Stöcker, Nishtha Srivastava
arXiv 2204.02870 | Paper | Code
Smart home system based on STC89C52
Liang Qin, Yu Sha, Yumeng Xu
Practical Electronics | 2018 | Paper
Study on operation analysis and decision making for sharing-bicycles
Hong Zhang, Dixin Zhou, Chuanqi Cheng, Yu Sha Big Data Research | 2019 | Paper
Hierarchical Cavitation Intensity Recognition Using Sub-Master Transition Network-based Acoustic Signals in Pipeline Systems
Shuiping Gou, Yu Sha, Zhang Guo, Bo Liu
Invention Patent | 202310945885.1 |
Face Aging Method Based on Adversarial Learning of Local and Global Region Policies
Shuiping Gou, Ruichen Xue, Nuo Tong, Ruimin Li, Yu Sha, Ningtao Liu
Invention Patent | 202310941541.3 |
Physics-Guided Global Filtering Attention Convolutional Neural Networks for Image Classification
Zhang Guo, Huiyu Chen, Shuiping Gou, Yu Sha, Xinlin Wang, Bo Liu
Invention Patent | 202411474637.4 |
🧰 Projects
Xidian University (XDU):
Analysis of battlefield situation of artificial intelligence in the context of big data The 20th Research Institute of China Electronics Technology Group Corporation-Xidian Joint Laboratory for Artificial Intelligence | Completed | Project Participant
Knee intensity recognition for smart wearable devices based on machine learning Xijing Hospital | Completed | Project Participant
Frankfurt Institute for Advanced Studies (FIAS):
Cavitation and leakage detection in large pump/pipe using AI method SAMSON AG | Under Study | Project Participant
Lanzhou University of Technology (LUT):
LoRa based non-contact life detection system National Undergraduate Innovation and Entrepreneurship Training Project | Completed | Project Participant
Evaluation of students' comprehensive ability and program design based on fuzzy theory LUT Innovation and Entrepreneurship Training Program | Completed | Project Leader
Research on the cultivation of college students' creative ability by mathematical modeling competition LUT Technology Innovation Fund | Completed | Project Participant
WeChat program design for second-hand transaction and donation platform on campus LUT Technology Innovation Fund | Completed | Project Participant