姓名: 方慧
最后学位: 博士
职称: 副教授
公共职务:
导师岗位: 博导
办公室: 525
电话:
Email: fang.huiATmail.shufe.edu.cn


个人简介

Dr. Hui Fang is an Associate Professor in SHUFE. Her main research interests lie intackling complex business problems by leveraging interdisciplinary methods from ComputerScience (e.g., machine learning and data mining), Economics (e.g., econometric analysis), Behavior (e.g., userstudy) and Psychology. My research focus is on two areas: (1) business analytics; and (2) user modeling anddecision-making. Below is a more detailed description of her current research interests:
1) Business Analytics (BA)
Trust Prediction in Online Communities
Personalized Product Recommendation
E-commerce and Social Networks
2) User Modeling and Decision-making (UM&DM)
Subjectivity and Dishonesty Modeling
Online Review and Reputation Systems
Data-Driven Decision-making


Presently she is the Senior Editor of the ECRA journal, and invited referees of other journals and conferences like TKDE, JASIST, Cybernetics, DSS, PACIS, and ICIS. She also serves as a Program Committee Member for international conferences, including UMAP and IJCAI, etc.





教授课程

机器学习与深度学习
深度学习
商务智能之数据可视化
信息系统导论
管理信息系统





科研项目

国家自然科学基金青年项目，**，基于信任理论与机器学习的在线评价质量评估模型研究，2017.01-2019.12，在研，主持。
International Collaborator, Singapore MOE AcRF Tier 1 “Link Prediction in Signed Social Networks"





教育背景

2015, 新加坡南洋理工大学计算机工程学院, 博士

2010, 南京大学信息管理系, 硕士
2008, 南京大学信息管理与信息系统, 学士





发表论文

Journal Paper：
Hui Fang, Jie Zhang, and Murat Sensoy. “A Generalized Stereotype Learning Approach and its Instantiationin Trust Modeling”, Electronic Commerce Research and Applications (ECRA), 30: 149-158, 2018
Hui Fang, GuibingGuo and Jie Zhang. “Multi-faceted Trust and Distrust Prediction for RecommenderSystems”. Decision Support Systems (DSS), 71:37-47, 2015.
Hui Fang, JieZhang, Murat Sensoy and Nadia Magnenat Thalmann. “Reputation Mechanism forE-Commerce in Virtual Reality Environments”. Electronic Commerce Research andApplications (ECRA), 13 (6): 409-422, 2014.
Hui Fang, JieZhang, Yang Bao and Qinghua Zhu. “Towards Effective Online Review Systems inthe Chinese Context: A Cross-Cultural Empirical Study”. Electronic CommerceResearch and Applications (ECRA), 12 (3): 208-220, 2013.
Kewen Wu, Julita Vassileva, Qinghua Zhu, Hui Fang and Xiaojie Tan. “Supporting Group Collaboration inWiki by Increasing the Awareness of Task Conflict”. Aslib Proceedings, 65 (6), 2013.


Conference paper：
Xiaoming Li, Hui Fang, and Jie Zhang. “SupervisedUser Ranking in Signed SocialNetworks”, In Proceedingsof the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019.
Yihong Liu, Hui Fang, Yang Bao. "SCNetworkViz: AWeb-Based System for Interactive Visualization of SupplyChain Network", Demo paper, The 28th Workshop on Information Technologies and Systems (WITS),2018.
Hui Fang, Hailiang Huang, Gujie Li, and Yanhong Li. “Learning from Mistakes: Constructing and MiningMisdiagnosis Database to Reduce Cognitive Error". In Proceedings of the 39th International Conferenceon Information Systems (ICIS), 2018.
Xiaoming Li, Hui Fang, and Jie Zhang. “FILE: A Novel Framework for Predicting Social Status in SignedNetworks”. In Proceedings of the 32rd AAAI Conference on Artificial Intelligence (AAAI), 2018
Xiaoming Li, Hui Fang, Qing Yang, and Jie Zhang. “Who is Your Best Friend?: Ranking Social NetworkFriends According to Trust Relationship”, In Proceedings of the 26th ACM Conference on User Modeling,Adaptation and Personalization (UMAP), 2018.
Xiaoming Li, Hui Fang, and Jie Zhang. “A Feature-based Approach for the Redefined Link Prediction Problemin Signed Networks”. In Proceedings of the 13th International Conference on Advanced Data Miningand Applications (ADMA), 2017
Yang Bao, Hui Fang, and Jie Zhang. “TopicMF: Simultaneously Exploiting Ratings and Reviewsfor Recommendation”. In Proceedings of the 28th AAAI Conference on ArtificialIntelligence (AAAI), 2014.
Hui Fang, YangBao, and Jie Zhang. “Leveraging Decomposed Trust in Probabilistic MatrixFactorization for Effective Recommendation”. In Proceedings of the 28th AAAIConference on Artificial Intelligence (AAAI),2014.
Hui Fang, JieZhang and Nadia Magnenat-Thalmann. “Subjectivity Grouping: Learning from Users’Rating Behavior”. In Proceedings of the 13th International Joint Conference onAutonomous Agents and Multiagent Systems (AAMAS),pages 1241-1248, 2014.
Hui Fang,YangBao, and Jie Zhang. “Misleading Opinions Provided by Advisors: Dishonesty orSubjectivity”. In Proceedings of 23rd International Joint Conference onArtificial Intelligence (IJCAI),2013.
Hui Fang, JieZhang and Nadia Magnenat Thalmann. “A Trust Model Stemmed from the DiffusionTheory for Opinion Evaluation”. In Proceedings of the 12th International JointConference on Autonomous Agents and Multiagent Systems (AAMAS), pages 805-812, 2013.
Hui Fang, JieZhang, Murat Sensoy and Nadia Magnenat Thalmann. “SARC: Subjectivity Alignmentfor Reputation Computation”. In Proceedings of the 11th InternationalConference on Autonomous Agents and Multiagent Systems (AAMAS), pages 1365-1366, 2012.
Hui Fang, Jie Zhang, Murat ?Sensoy and Nadia Magnenat Thalmann. “A Generalized Stereotypical Trust Model”. In Proceedings of the 11th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom), pages 698-705, 2012.
Hui Fang, Jie Zhang, Murat ?Sensoy and Nadia Magnenat Thalmann. “A Reputation Mechanism for Virtual Reality - Five-Sense Oriented Feedback Provision and Subjectivity Alignment”. In Proceedings of the 10th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom), pages 312-319, 2011.





荣誉奖励


Outstanding Reviewer, Electronic Commerce Research and Applications journal, Elsevier, 2016
Google Anita Borg Memorial Scholarship (1 of 15 Recipients), Asia, 2012
IJCAI Travel Scholarship, 2013
SIGART AAMAS Travel Scholarship, 2012 and 2013
DragonVenture-NTU Scholarship (1 of 10 Recipients), 2011