Jingyuan Yang
杨静远
I am an Assistant Professor of Information Systems and Operations Management at the Costello College of Business, George Mason University. I’ve earned my doctoral degree in Information Technology from the Business School at Rutgers, the State University of New Jersey.
My general research interests are data mining, machine learning, and business analytics. I am passionate about developing methodology, models, and algorithms for discovering useful knowledge from data, which can support real-world decision making in Urban Computing, Marketing, and Talent Analytics. My research has been published in premier refereed journals such as INFORMS Journal on Computing (IJOC), IEEE Transactions on Knowledge and Data Engineering (TKDE), Neural Networks, and top conferences of knowledge discovery and data mining, including the IEEE International Conference on Data Mining (ICDM), the SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), and the IEEE International Conference on Big Data (Big Data).
CV.pdf (updated Sep. 3, 2025)Education
Rutgers, The State University of New Jersey
Rutgers, The State University of New Jersey
Nankai University
Experience
Assistant Professor
Instructor & Lecturer
Data Analytics and Machine Learning Intern
Urban Computing Project - Functional Zone Discovery
Marketing Analytics Intern
B2B Marketing Analytics
Research Intern
Talent Mobility Analysis
Research
Iterative prediction-and-optimization for E-logistics distribution network design Junming Liu, Weiwei Chen, Jingyuan Yang, Hui Xiong, Can Chen INFORMS Journal on Computing (IJOC), 2021.
Cross-lingual knowledge transferring by structural correspondence and space transfer Deqing Wang, Junjie Wu, Jingyuan Yang, Baoyu Jing, Wenjie Zhang, Xiaonan He, Hui Zhang IEEE Transactions on Cybernetics (IEEE Trans. Cybern.), 2021.
Exploiting interpretable patterns for flow prediction in dockless bike sharing systems Jingjing Gu, Qiang Zhou, Jingyuan Yang, Yanchi Liu, Fuzhen Zhuang, Yanchao Zhao, Hui Xiong IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2020.
NeuO:Exploiting the sentimental bias between ratings and reviews with neural networks Yuanbo Xu, Yongjian Yang, Jiayu Han, En Wang, Fuzhen Zhuang, Jingyuan Yang, Hui Xiong Neural Networks, 2019.
Dynamic talent flow analysis with deep sequence prediction modeling Huang Xu, Zhiwen Yu, Jingyuan Yang, Hui Xiong, Hengshu Zhu IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2018.
A unified view of social and temporal modeling for B2B marketing campaign recommendation Jingyuan Yang, Chuanren Liu, Mingfei Teng, Ji Chen, Hui Xiong IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2017.
Adaptively transfer category-classifier for handwritten chinese character recognition Yongchun Zhu, Fuzhen Zhuang, Jingyuan Yang, Xi Yang, and Qing He In Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2019.
Caden: A context-aware deep embedding network for financial opinions mining Liang Zhang, Keli Xiao, Hengshu Zhu, Chuanren Liu, Jingyuan Yang, and Bo Jin In IEEE International Conference on Data Mining (ICDM), 2018.
Incomplete label uncertainty estimation for petition victory prediction with dynamic features Junxiang Wang, Yuyang Gao, Andreas Züfle, Jingyuan Yang, and Liang Zhao In IEEE International Conference on Data Mining (ICDM), 2018.
Buyer targeting optimization: A unified customer segmentation perspective Jingyuan Yang, Chuanren Liu, Mingfei Teng, March Liao, and Hui Xiong In IEEE International Conference on Big Data (Big Data), 2016.
Talent circle detection in job transition networks Huang Xu, Zhiwen Yu, Jingyuan Yang, Hui Xiong, and Hengshu Zhu In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016.
Exploiting temporal and social factors for B2B marketing campaign recommendations Jingyuan Yang, Chuanren Liu, Mingfei Teng, Hui Xiong, March Liao, and Vivian Zhu In IEEE International Conference on Data Mining (ICDM), 2015.
Station site optimization in bike sharing systems Junming Liu, Qiao Li, Meng Qu, Weiwei Chen, Jingyuan Yang, Hui Xiong, Hao Zhong, and Yanjie Fu In IEEE International Conference on Data Mining (ICDM), 2015.
Mobile GIS solutions for retail and advertising Jingyuan Yang In Encyclopedia of GIS, pp. 1244-1250, Springer, 2017.
Identifying functional zones within a geographic region Jin Cao, Ran He, Yihao Zhang, Jingyuan Yang U.S. Patent 11,232,115, issued January 25, 2022.
When Airline Insurance Meets a Pandemic: Designing Machine Learning Resilience Under Volatile Drift and Data Deficiency Jingjing Li, Yuan Qu, Jingyuan Yang* (*author names in alphabetical order) Information Systems Research (ISR), R & R, Under Review. Abstract Available on SSRN
Societal Advancement through Equitable Decision Paths: A Performance-Adaptive Multi-Agent Reinforcement Learning Approach Pengzhan Guo, Keli Xiao, Jingyuan Yang* (*author names in alphabetical order) Management Information Systems Quarterly (MISQ), Under Review. Available on SSRN
Everyone Contributes! Incentivizing Strategic Cooperation in Multi-LLM Systems via Sequential Public Goods Games Yunhao Liang, Yuan Qu#, Jingyuan Yang#, Shaochong Lin, Max Z.J. Shen (#corresponding author) Under Review, Available on arXiv
Acqui-hiring or Acqui-quitting: Post-M&A Turnover Prediction via a Dual-fit Model Jingyuan Yang, Denghui Zhang, Hao Zhong Targeting Journal of Management Information Systems (JMIS), Pending Submission, Available on SSRN
Graph-infused Multitask Learning for Inter-segment Lead Scoring Jingyuan Yang, Jiyeon Hong, Chuanren Liu, Hui Xiong. Targeting Marketing Science.
Who Thrives, Who Stays? Predicting Talent Potential from Level-Aware Career Moves Dawei Xu, Jingyuan Yang, Hao Zhong, Xitong Li. Targeting Information Systems Research (ISR).
Diminishing Social Capital Returns from Employee Ambassadorship: Evidence from WeChat Chaitanya Kaligotla, Sarah Wittman, Jingyuan Yang, Yuan Qu, Wei Zeng Targeting Organization Science. Available on SSRN
Hybrid LLM-Enhanced Reinforcement Learning for Sequential Decision Making Pengzhan Guo, Keli Xiao, Jingyuan Yang. Targeting Information Systems Research (ISR).
Developing Expert AI for Medical Education and Clinical Collaboration Bryan Sullivan, Jingyuan Yang, Siddharth Bhattacharya Targeting Information Systems Research (ISR).
One Size Does Not Fit All: Personal Match and Marketing Message Effectiveness on Social Networks Jingyuan Yang, Yuan Qu, Wei Zeng Targeting Decision Support Systems (DSS).
Teaching
Costello College of Business, George Mason University
MIS431 - Data Mining for Business Applications, Undergraduate Course, In-Person & Online, Spring 2022, Fall 2022, Spring 2023, Spring 2024, Fall 2024, Spring 2025, Fall 2025. MIS430 - Data Warehousing, Undergraduate Course, 2018-2019 (In-Person) & 2020-2021 (Online) MIS 892 – Emerging Technologies in IS Research (Deep Learning, LLMs, Reinforcement Learning Modules), PhD Course, Spring 2025. MIS 721 - Seminar in Information Systems (Machine Learning and AI Module), PhD Course, Fall 2021, Fall 2023, Fall 2024.
Rutgers Business School, Rutgers University
Data Mining (29:623:311), Undergraduate, Spring 2017 Management Information System (29:623:220), Undergraduate, Fall 2014 & Fall 2015 Data Mining for Business Intelligence (29:623:386), Undergraduate, Fall 2012 & Fall 2013
Professional Activities
- Institutional Services
- Costello College of Business, George Mason University
- Affiliate Faculty, The Center for Retail Transformation
- Affiliate Faculty, The Institute of Digital Innovation (IDIA)
- ISOM Research Seminar Series Co-Coordinator 2020-2024
- Ph.D. Hiring Committee 2021-2023
- MIS Representative in Business Analytics Concentration Committee 2020-2023
- Ad-Hoc ISOM Tenure-Track Faculty Search Committee 2020
- Faculty Marshal, GMU College of Business Commencements 2019, 2025
- Presentations
Who Thrives, Who Stays? Predicting Talent Potential from Level-Aware Career Move GMU Costello Summer Research Series, George Mason University, Fairfax, VA, 2025
Talent Analytics for Acqui-hiring GMU Costello Summer Research Series, George Mason University, Fairfax, VA, 2024
Long-Term Decision-Making for Social Benefit: A Multi-Agent Reinforcement Learning Approach The INFORMS Workshop on Data Science (WDS), Seattle, WA, October 2024
Acqui-hiring or Acqui-quitting: Data Driven Post-M&A Turnover Prediction via a Dual-fit Model The Conference on Information Systems and Technology (CIST), Indianapolis, IN, October 2022 AI Thrust Research Seminar, Hong Kong University of Science and Technology, Virtual, October 2022 Research Seminar Presentation, University of Iowa, Iowa City, IA, USA, September 2022
Building Resilience During Crises: A Big Data Empowered Reinforcement Learning Approach for Airline Insurance The INFORMS Workshop on Data Science (WDS), 2021. Research-in-Progress Presentation, George Mason University, Fairfax, VA, 2021
One Size Does Not Fit All: Personal Match and Marketing Message Effectiveness on Social Networks Research Seminar Presentation, Stony Brook University, Stony Brook, NY, 2019
Talent Analytics with Job Transition Networks: Talent Circle Detection and Talent Flow Prediction Invited Research Presentation, Leidos, Reston, VA, 2019
B2B Marketing Campaign Recommendation: A Social and Temporal Perspective Invited Research Presentation, Indiana University, Bloomington, IN, 2017
A Unified Clustering Approach for Identifying Functional Zones Using Points of Interest Data Summer Research Presentation, Nokia Bell Labs, Murray Hill, NJ, 2017
Tutorial of Advanced Density-based Clustering Summer Research Presentation, Nokia Bell Labs, Murray Hill, NJ, 2017
Buyer Targeting Optimization: A Unified Customer Segmentation Perspective IEEE International Conference on Big Data (Big Data), 2016
Exploiting Temporal Behavior Patterns and Community Networks for B2B Marketing Campaign Recommendations IEEE International Conference on Data Mining (ICDM), 2015
- Conference Organizing Services
- The Ignite Talk Chair, the Workshop on Information Technologies and Systems (WITS), 2025.
- Discussant, the Summer Workshop on AI for Business (SWAIB), 2024.
- Cluster Co-Chair, “Human, Machines, Algorithms” Cluster, the INFORMS Annual Meeting (INFORMS), 2022.
- Local Chair, the INFORMS Workshop on Data Science (WDS), 2022.
- Session Chair, the INFORMS Workshop on Data Science (WDS), 2021.
- Session Chair, the INFORMS Annual Meeting (INFORMS), 2019, 2020, 2021.
- Local Chair, the INFORMS Workshop on Data Science (WDS), 2020.
- Conference Program Committee Members and Reviewer Services
- Program Committee, the INFORMS Workshop on Data Science (WDS), 2020 - 2025.
- Program Committee, the Conference on Information Systems and Technology (CIST), 2022 - 2025.
- Associate Editor, the International Conference on Information Systems (ICIS), 2020, 2024, 2025.
- Program Committee, the Workshop on Information Technologies and Systems (WITS), 2023 - 2025.
- Program Committee, the Summer Workshop on AI for Business (SWAIB), 2024, 2025.
- Associate Editor, the Pacific Asia Conference on Information Systems (PACIS), 2021, 2022, 2025.
- Program Committee, the International Joint Conference on Artificial Intelligence (IJCAI), 2024, 2025.
- Senior Program Committee, the AAAI Conference on Artificial Intelligence (AAAI), 2023, 2024.
- Program Committee, the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2020 - 2023.
- Reviewer, the Hawaii International Conference on System Sciences (HICSS), 2021, 2022, 2023.
- Program Committee Co-Chair, the SIAM International Conference on Data Mining (SDM), 2022.
- Program Committee, the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018, 2019.
- Program Committee, the International Conference on Knowledge Science, Engineering and Management (KSEM), 2017, 2018.
- Journal Reviewer
- Management Information Systems Quarterly (MIS Quarterly), 15 reports
- Information Systems Research (ISR), 5 reports
- Management Science (MS), 3 reports
- INFORMS Journal on Computing (IJOC), 7 reports
- Journal of Management Information Systems (JMIS), 2 reports
- ACM Transactions on Management Information Systems (TMIS), 7 reports
- Production and Operations Management (POM), 1 report
- Decision Support Systems (DSS), 1 report
- Frontiers in Big Data (Front. Big Data), 3 reports
- IEEE Transactions on Knowledge and Data Engineering (TKDE), 2 reports
- ACM Transactions on Intelligent Systems and Technology (TIST), 3 reports
- Information Technology and Management (IT&M), 2 reports
- Electronic Commerce Research and Applications (ECRA), 3 reports
- ACM Transactions on Knowledge Discovery in Data (TKDD), 6 reports
- IEEE Transactions on Big Data (TBD), 3 reports
- Data & Knowledge Engineering (DATAK), 5 reports
- International Journal of Automation and Computing (IJAC), 5 reports
Awards, Grants & Media Coverage
- Awards & Grants
- GMU Costello College of Business Competitive Summer Research Award 2024, 2025
- Prabuddha De Best Paper Award, Workshop on Information Technologies and Systems (WITS) 2024
- 4-VA grant, (Co-PI), Building Machine Learning Resilience During Disasters, $15,000 2024-2025
- GMU School of Business Outstanding Research Publication Award 2019-2022
- IEEE International Conference on Data Mining (ICDM) Travel Award 2015
- SIAM International Conference on Data Mining (SDM) Travel Award 2014 & 2015
- Dean's Fund for Summer Research, Rutgers Business School 2014
- Tianjin Scholarship, Nankai University 2007-2008
- The 1st Zhou Enlai Scholarship, Nankai University 2007
- Outstanding Student Leader, Nankai University 2006-2009
- Selected Media Coverage
- Tech Talent Investment Pipeline (TTIP) of Costello College of Business, Post M&A, will employees leave or stay? Just ask AI, April 2024.
- Sullivan Foundation, What AI Can Tell Us About Bike-Sharing (and Other Social Innovations), September 2022.
- Ideas with Impact from George Mason University Costello College of Business, Building a 'digital twin' of the real world, September 2022.
- The George, Adapting artificial intelligence for real-world solutions, September 2022.