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).

News

Best Technical Implementation Award and First Price of Industry Challenge at Blockchain Hackathon 2021 Germany

Publications

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)

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.

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.

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

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)

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

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.

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

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.

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.

Projects

Collaboration On Rare Diseases (CORD)

LEUKO EXPERT

National Research Data Infrastructure for Personal Health Data (NFDI4Health)

Polypharmazie, Arzneimittelwechselwirkungen, Risiken (POLAR)

Smart Medical Information Technology for Healthcare (SMITH)

Teaching

Data Driven Medicine (WS 20/21)

Methods for Data Reusability (WS 20/21)

Data Science in Medicine (SS 21)

Data Science in Medicine (WS 21/22)

Data Science in Medicine (SS 22)

Data Science in Medicine (WS 22/23)

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
  • Research project of Personal Health Train: Development of Distributed Analytics Platform
• Internship: 2019.10 - 2020.03
  • National Institute of Informatics, Japan
  • Research project of Deep Learning in Civil Engineering: Bridge Damage Detection using Computer Vision
  • Supervisor: Prof. Prendinger
• Research Assistant: 2018.07 - 2019.05
  • Werkzeugmaschinenlabor (WZL), Germany
  • Research project of Interdisciplinary Modeling Language

Skills

• Program languages
  • Python, Java, C/C++
• Languages
  • Chinese (native)
  • English (fluent)
  • German (fluent)
  • Japanese (beginner)
• General Business Skills
  • Good presentation skills
  • Works well in a team