CV
Short Descriptioin
Hi, I am Yongli Mou. Now, I am Ph.D. candidate supervised by Prof. Dr. Stefan Decker and co-supervised by Prof. Dr. Oya Beyan and work as a research assistant at the Chair of Computer Science i5 Databases and Information Systems (Informatik 5, DBIS) at RWTH Aachen University since July 2020. My current research focuses on the theories and applications of artificial intelligence in medical and healthcare sector (e.g., federated learning, privacy enhancing technologies and blockchain applications).
Education
- Ph.D., RWTH Aachen University, Germany, 2020 - now
- M.Sc. Computer Science, RWTH Aachen University, Germany, 2016 - 2020
- B.Sc. Computer Science, Hannover University of Applied Sciences and Arts, Germany, 2013 - 2016
- B.Sc. Computer Science, Zhejiang University of Science and Technology, China, 2011 - 2013
Work Experience
- Research Assistant: 2020.04 - 2020.06
- RWTH Aachen University, Germany
- Software Development of Distributed Analytics Platform
- Internship: 2019.10 - 2020.03
- National Institute of Informatics, Japan
- Bridge Damage Detection using Computer Vision
- Supervisor: Prof. Prendinger
- Research Assistant: 2018.07 - 2019.05
- Werkzeugmaschinenlabor (WZL), Germany
- Research project of Interdisciplinary Modeling Language (IML)
- Research Assistant: 2016.06 - 2016.08
- Bosch SoftTec GmbH, Germany
- Bachelor Thesis: Chinese voice control of the in-vehicle-smartphone integration solution mySPIN by using Natural Language Processing with Android
- Supervisor: Prof. Ahlers
- Teaching Assistant: 2014.09 - 2016.07
- University Hannover of Applied Sciences and Arts, Germany
- Tutorial of Mathematic 1 and 2: Mathematical Logic, Discrete mathematics and Linear Algebra
- Supervisor: Prof. Sprengel
Skills
- Program languages
- Python, Java, C/C++, Javascript
- Languages
- Chinese (native)
- English (fluent)
- German (fluent)
- Japanese (beginner)
- General Business Skills
- Good presentation skills
- Works well in a team
News
Projects
Publications
Vision based pixel-level bridge structural damage detection using a link ASPP network
Deng W, Mou Y, Kashiwa T, Escalera S, Nagai K, Nakayama K, Matsuo Y, Prendinger H. (2020). "Vision based pixel-level bridge structural damage detection using a link ASPP network." Automation in Construction. 110, 102973.
Distributed Skin Lesion Analysis Across Decentralised Data Sources
Mou Y, Welten S, Jaberansary M, Yediel YU, Kirsten T, Decker S, Beyan O. "Distributed Skin Lesion Analysis Across Decentralised Data Sources." Studies in health technology and informatics. 2021 May 27;281:352-6.
Optimized Federated Learning on Class-Biased Distributed Data Sources
Mou Y, Geng J, Welten S, Chun R, Decker S, Beyan O. (2021). "Optimized Federated Learning on Class-biased Distributed Data Sources." In Joint European Conference on Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2021. Communications in Computer and Information Science, vol 1524. Springer, Cham. https://doi.org/10.1007/978-3-030-93736-2_13
A Privacy-Preserving Distributed Analytics Platform for Health Care Data
Welten S, Mou Y, Neumann L, Jaberansary M, Yediel Ucer Y, Kirsten T, Decker S, Beyan O. (2022). "A Privacy-Preserving Distributed Analytics Platform for Health Care Data." Methods Inf Med. 0026-1270, DOI:10.1055/s-0041-1740564.
Multi-Institutional Breast Cancer Detection Using a Secure On-Boarding Service for Distributed Analytics
Welten S, Hempel L, Abedi M, Mou Y, Jaberansary M, Neumann L, Weber S, Tahar K, Yediel Ucer Y, Löbe M, Decker S, Beyan O, Kirsten T. (2022). "Multi-Institutional Breast Cancer Detection Using a Secure On-Boarding Service for Distributed Analytics." Applied Sciences. 12, no. 9: 4336, DOI:10.3390/app12094336
Blockchain-based Cross-organizational Workflow Platform
Geng J, Rehman AA, Mou Y, Decker S, Rong C. "Blockchain-based Cross-organizational Workflow Platform" In2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). 2022 Dec 13 (pp. 53-59)
Improved Gradient Inversion Attacks and Defenses in Federated Learning
Geng J, Mou Y, Li Q, Li F, Beyan O, Decker S, Rong C. "Improved Gradient Inversion Attacks and Defenses in Federated Learning" IEEE Transactions on Big Data. 2023 Jan 23
Rare Diseases in Hospital Information Systems–An Interoperable Methodology for Distributed Data Quality Assessments
Tahar K, Martin T, Mou Y, Verbuecheln R, Graessner H, Krefting D. (2023). " Rare Diseases in Hospital Information Systems–An Interoperable Methodology for Distributed Data Quality Assessments." Methods Inf Med, DOI:10.1055/a-2006-1018.
pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints
Mou, Y., Geng, J., Zhou, F., Beyan, O., Rong, C. and Decker, S. (2023). "pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints." In Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023. (pp. 283-294). Springer Nature, Cham.
Self-sovereign Identity-based Access Control Management in Forestry 4.0
Mou Y, Chen J, Zhang Z, Roßmann J, Decker S. "Self-sovereign Identity-based Access Control Management in Forestry 4.0" In2023 10th International Conference on Future Internet of Things and Cloud (FiCloud). 2023 Aug 14 (pp. 159-166)