Yilong Yang - 杨溢龙
Research Interests
-
Automated Software Engineering
-
Requirements Engineering
-
Service Computing
Education
2013.09 - 2019.07
University of Macau, PhD in Software Engineering.
2010.09 - 2013.06
Guizhou University, MSc in Computer Science.
2006.09 - 2010.06
China University of Mining and Technology, BS in Computer Science.
Employment
2020.11 - Current
Beihang University (BUAA), Assistant Professor, School of Software, Beijing, China.
2013.01 - 2013.06
United Nations University - International Institute for Software Technology (UNU-IIST), Fellow, Macau.
Software Engineering Tools
RM2PT - A Tool for Automated Prototype Generation from Lightweight Formal Requirements Model
Publications
Note that ICWS is the top conferences of Service Computing, RE is the top conference of Requirements Engineering, and ICSE is the top conference of Software Engineering.
Software Engineering: Requirements and Code Generation
Tianshu Bao, Jing Yang, Yongfeng Yin, Yilong Yang*. “RM2Doc: A Tool for Automatic Generation of Requirements Documents from Requirements Models”. to presented at the 44th International Conferences on Software Engineering (ICSE’22), Pittsburgh, PA, USA, May 2022. (Demonstration Track)
Yilong Yang, Younggi Bok, Zhuoxi Yang, Eric Sheriff and Tong Li. “Goal2UCM: Automatic Generation of Use Case Model from iStar Model”. presented at The 14th International iStar Workshop as part of the 40th International Conference on Conceptual Modeling, St. John’s, NL, Canada, October 2021.
Bing Li, Zhi Li, Yilong Yang. “NFRNet: A Deep Neural Network for Automatic Classification of Non-Functional Requirements.” presented at IEEE International Requirements Engineering Conference (RE’21), Notre Dame Basilica, USA, Sep. 2021. (Demonstration Track)
Shangfeng Wei, Zhi Li, Yilong Yang, Hongbin Xiao. “Zoom4PF: A Tool for Refining Static and Dynamic Domain Descriptions in Problem Frames” presented at IEEE International Requirement Engineering Conference (RE’21), Notre Dame Basilica, USA, Sep. 2021 (Demonstration Track)
Hongbin Xiao, Zhi Li, Yilong Yang, Jie Deng, and Shangfeng Wei. “An Extended Meta-Model of Problem Frames for Enriching Environmental Descriptions”. presented at IEEE International Workshop on Environment-Driven Requirements Engineering (EnviRE), Sep. 2021.
Yilong Yang, Xiaoshan Li, Wei Ke, Zhiming Liu. “Automated Prototype Generation from Formal Requirements Model”. IEEE Transactions on Reliability. 69(2), pp. 632-656, June 2020 (JCR - Q1)
Yilong Yang, Xiaoshan Li, Zhi Li. “Rapid Prototyping for Requirements Validation: A Best-Practice with RM2PT”. presented at the 28th IEEE International Requirements Engineering Conference (RE’20). Zurich, Switzerland, August 2020. (RE’20 Tutorial)
Yilong Yang, Xiaoshan Li, Zhiming Liu, Wei Ke. “RM2PT: A Tool for Automated Prototype Generation from Requirements Model”. presented at the 41th International Conferences on Software Engineering (ICSE’19), Montreal, QC, Canada, May 2019. (Demonstration Track)
Yilong Yang, Wei Ke and Xiaoshan Li. “RM2PT: Requirements Validation through Automatic Prototyping”. presented at the 27th IEEE International Requirements Engineering Conference (RE’19). Jeju Island, South Korea, September 2019. (Demonstration Track)
Software Engineering: Service Computing
Jing Zhang, Changran Lei , Yilong Yang* , Borui Wang, and Yang Chen. “MMA-Net: A MultiModal-Attention-based Deep Neural Network for Web Services Classification”. presented at International Conference Service-Oriented Computing (ICSOC’21), Dubai, UAE, November 2021 (Short Paper).
Jing Zhang, Yang Chen, Yilong Yang*, Changran Lei, Deqiang Wang. “ServeNet-LT: A Normalized Multi-head Deep Neural Network for Long-tailed Web Services Classification.”. presented at IEEE International Conferences on Web Services (ICWS’21), Chicago, IL, USA. September 2021. (Regular Paper).
Yilong Yang, Zhaotian Li, Jing Zhang and Yang Chen. “Transfer Learning for Web Services Classification”. presented at IEEE International Conferences on Web Services (ICWS’21), Chicago, IL, USA. September 2021. (Short Paper).
Bing Li, Zhi Li, Yilong Yang*, “Residual Attention Graph Convolutional Network for Web Services Classification”. Neurocomputing. 440, pp. 45-57 (2021) (JCR - Q1)
Yilong Yang, Nafees Qamar, Peng Liu, Katarina Grolinger, Weiru Wang, Zhi Li, Zhifang Liao. “ServeNet: A Deep Neural Network for Web Services Classification. presented at IEEE 12th International Conferences on Web Services (ICWS’20), Beijing, China, Oct. 2020. (Regular Paper).
Yilong Yang, Wei Ke, Weiru Wang, Yongxin Zhao “Deep Learning for Web Services Classification”. presented at IEEE 11th International Conferences on Web Services (ICWS’19), Milan, Italy, July 2019. (Work-in-progress Paper).
Yilong Yang, “SSC-ASP: An Integrated Framework for Semantic Service Composition Using Answer Set Programming”. Innovative Solutions and Applications of Web Services Technology. ISBN: 9781522572688. (Book-Chapter)
Yilong Yang, Jing Yang, Xiaoshan Li, Weiru Wang. “An Integrated Framework for Semantic Service Composition using Answer Set Programming”. International Journal of Web Services Research. 11(4), pp. 47-61 (2014) (JCR - Q4).
Software Engineering: Formal Methods
Yilong Yang, Wei Ke, Jing Yang, Xiaoshan Li. “Integrating UML With Service Refinement for Requirements Modeling and Analysis”. IEEE Access, 7, pp. 11599-11612 (2019). (JCR - Q1)
Yilong Yang, Quan Zu, Xiaoshan Li. “Real-Time System Modeling and Verification Through Labeled Transition System Analyzer”. IEEE Access, 7, pp. 26314-26323 (2019). (JCR - Q1)
Yongxin Zhao, Xi Wu, Jing Liu, Yilong Yang. “Formal Modeling and Security Analysis for OpenFlow-Based Networks. 2018 23rd International Conference on Engineering of Complex Computer Systems (ICECCS’18), Melbourne, VIC, 2018, pp. 201-204.
Interdisciplinary Applications: Health and Pharmaceutics
Yilong Yang, Zhuyifan Ye, Yan Su, Qianqian Zhao, Xiaoshan Li, Defang Ouyang. Deep Learning for in-vitro Prediction of Pharmaceutical Formulations. Acta Pharmaceutica Sinica B, 9(1), pp. 177-185 (2019) (JCR - Q1)
Run Han, Hui Xiong, Zhuyifan Ye, Yilong Yang, and Defang Ouyang. Predicting physical stability of solid dispersions by machine learning techniques. Journal of Controlled Release, 311-312, pp.16-25 (2019). (JCR - Q1)
Zhuyifan Ye, Yilong Yang, Defang Ouyang. An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction. Molecular pharmaceutics, 16(2), pp.533-541 (2018). (Co-First Author and JCR - Q1)
Run Han, Yilong Yang, Xiaoshan Li, and Defang Ouyang. Predicting oral disintegrating tablet formulations by neural network techniques. Asian Journal of Pharmaceutical Sciences, 13(4), pp.336-342 (2018). (Co-First Author and JCR - Q1)
Yilong Yang, Zu Quan, Peng Liu, Defang Ouyang, Xiaoshan Li. MicroShare: Privacy-Preserved Medical Resource Sharing through MicroService Architecture. International Journal of Biological Sciences, 14(8), pp. 907-919 (2018). (JCR - Q1)
Yilong Yang, Xiaoshan Li, Nafees Qamar, Peng Liu, Wei Ke, Bingqing Shen, Zhiming Liu. “MedShare: A Novel Hybrid Cloud for Medical Resource Sharing among Autonomous Healthcare Providers”. IEEE Access, 6, pp. 46949-46961 (2018). (JCR - Q1).
Bingqing Shen, Jingzhi Guo, and Yilong Yang. “MedChain: Efficient Healthcare Data Sharing via Blockchain”. Applied Sciences, 9(6), p.1207 (2019). (JCR - Q3)
Noted that: Completed publication list in Google scholar
Research Projects
2021.03
- 2022.03
Automatic Prototyping and Verification of Industrial Requirements (工业软件需求原型化与协同验证) (PI)
2016 - 2019
Model-Driven Software Development from Requirement Description to Code Generation. Macau Science and Technology Development Fund. FDCT 103/2015/A3. (Main Contributor)
2016 - 2019
Applying RUP Iterative Development for Formal Requirements Analysis and Validation. National Natural Science Foundation of China. NSFC 61562011. (Main Contributor)
2012 - 2015
Secure Architecture for Electronic Health Records (SAFEHR). Macau Science and Technology Development Fund. FDCT 018/2011/A1. (Main Contributor)
2012 - 2013
Dependable and Intelligent Service-oriented Architecture for Hybrid Cloud. Innovation Fund of Guizhou University. No. ligong2012036. (PI)
2011 - 2012
Distributed Architecture of Crawler based on P2P network. Natural Science Foundation of GuiYang. No. zhukehetong2011201da-4-2. (PI)
Research Services
PC Members: IJCAI’20, ECAI’20, and NASAC’19 (Blockchain Track)
Session Chair: APSCC’14
Reviewer for conferences: FSEN’21, SETTA’20, TASE’20’19, ISSRE’19, SEH’20’19, ICTAC’17, ICFEM’16, KSE’15, and TASE’14
Reviewer for journals: IEEE Transactions on Software Engineering, IEEE Internet of Things Journal, IET Intelligent Transport Systems, Computer Networks, Wireless Networks, Journal of Biomedical and Health Informatics, Applied Clinical Informatics, Chemometrics and Intelligent Laboratory Systems, Frontier of Computer Science.
Patent
- 2021108906230 一种基于需求原型化的软件开发方法
- 2021108906245 一种从目标模型到 UML 需求模型转化方法
- 2021108912246 一种基于迁移学习的 Web 服务分类方法
- 2021108912316 一种基于需求模型的企业级系统生成方法
Open Source Projects
My personal GitHub account hosts my open source projects as well as listing contributions to open source tools. It mainly contains:
1 - RM2PT Case Studies: RM2PT-CaseStudies
2 - MicroShare: Privacy-Preserved Medical Resource Sharing through MicroService Architecture: MedShare-MicroService
3 - MedShare: A Novel Hybrid Cloud for Medical Resource Sharing among Autonomous Healthcare Providers: MedShare
4 - Deep Learning for Web Service Classification: ServeNet
5 - Deep Learning for Pharmaceutical Formulation Prediction: DeepPharm
6 - Data Splitting for Small Data: MD-FIS
Technical Certifications
- Cloud-Native Application Development with Java EE (2019)
- Master Microservices with Spring Boot and Spring Cloud (2019)
- The Complete Flutter Development Bootcamp with Dart (2019)
- IBM MicroServices (2019)
- Deep Learning - Andrew Ng (2018)
- Java EE 8 Microservices (2017)
- Machine Learning - Andrew Ng (2014)
- Red Hat Certified Engineer - RHCE (2008)
- Cisco Certified Network Professional - CCNP (2007)
Techniques
- Java / Java EE
- Python
- C/C++
- C#
- Javascrip / HTML / CSS
- LaTeX
- Bash
- Git / SVN
- Linux / Unix
- Docker
- Kubernetes
- TensorFlow / DeepLearning4j
Placements
To be Announced.
Other Links
ORCID
Google scholar
ResearchGate
DBLP
Arxiv Preprint
GitHub
Knowledge Center