姓名: 涂文婷
最后学位: 博士
职称: 副教授
公共职务:
导师岗位: 博导
办公室: 210
电话:
Email: tu.wenting@mail.shufe.edu.cn


个人简介

我目前在上海财经大学的信息管理工程学院担任副教授。进入上财之前，于香港大学的计算机科学系获得博士学位，师从Prof. David Cheung和Prof. Nikos Mamoulis；于华东师范大学的计算机系获得硕士学位，师从孙仕亮教授。
我的研究兴趣包括机器学习算法以及相关应用，包括但不限于迁移学习、深度学习、文本挖掘技术在智能金融（例如征信风控、智能投顾）、推荐系统、教育大数据上的应用。截止到目前，我在上述相关方向上共发表了30余篇学术论文。欢迎访问我最新的个人主页了解更多关于我的科研和教学。
About me
I am currently an associate professor at the School of Information Management and Engineering, Shanghai University of Finance and Economics (SHUFE). I received my PhD degree in computer science from The University of Hong Kong (HKU) in 2016, supervised by Prof. David Cheung and Prof. Nikos Mamoulis. Before that, I received her M. S. degree from the Department of Computer Science, East China Normal University (ECNU) in 2012, supervised by Prof. Shiliang Sun. I has broad interests in data mining, machine learning and nature language processing. For more information about me, you can visit my new homepage.


教授课程

机器学习（本科生 & 博士生, 本科生课程 & 研究生课程，主讲1/1）
机器学习与深度学习（硕士生，研究生课程，合作主讲1/2）
机器学习基础与应用（全校，通识课程，合作主讲1/5）
Teaching
Machine Learning
Machine Learning and Deep Learning
Machine Learning Foundations and Applications



科研项目

基于多源多任务深度学习实现个性化金融推荐的算法研究
（主持，国家级，青年科学基金项目）
基于深度域适应学习框架实现信用风险智能预测的算法研究
（主持，省部级，上海市青年科技英才扬帆计划）
前沿人工智能理论驱动下的金融科技研究
（主持，校级，新进教师科研启动经费）



教育背景

Ph.D @ 香港大学, 计算机科学系
? 导师: Prof. David Cheung & Prof. Nikos Mamoulis
? 研究方向：机器学习与数据挖掘
EducationPh.D @ HKU, Department of Computer Science
? Supervisors: Prof. David Cheung & Prof. Nikos Mamoulis
? Research directions：Machine Learning and Data Mining



发表论文

Publications (selected) (Google Schorlar)
Tags:ML (Machine Learning), NLP (Nature Language Processing), DL (Deep Learning), Recsys (Recommendation Systems), Fintech, BCI (Brain-computer Interface), Security,
* (Corresponding author)
2020:
Jun Chang, Wenting Tu*, Changrui Yu, Chuan Qin: Assessing Dynamic Qualities of Investor Sentiments for Stock Recommendation. Information Processing and Management (IPM) , 2020 (Accepted) [ML+Fintech]
Jun Chang, Yujie Ding, Wenting Tu*: FollowAKOInvestor: Using Machine Learning to Hear Voices from All Kinds of Investors. Proceedings of the 32th IEEE International Conference on Tools with Artificial Intelligence (ICTAI) , 2020 [ML+Fintech]
Min Yang, Weiyi Huang, Wenting Tu, Qiang Qu, Ying Shen, Kai Lei: Multitask Learning and Reinforcement Learning for Personalized Dialog Generation: An Empirical Study. IEEE Transactions on Neural Networks and Learning Systems (TNNLS) , 2020 [DL+NLP]
2019:
Hui Li, Yu Liu, Yuqiu Qian, Nikos Mamoulis, Wenting Tu*, David W.Cheung: H2MF: Hidden Hierarchical Matrix Factorization for Recommender Systems. Data Mining and Knowledge Discovery (DMKD), 2019 [Recsys]
Min Yang, Qiang Qu, Wenting Tu, Ying Shen, Zhou Zhao, Xiaojun Chen: Exploring Human-Like Reading Strategy for Abstractive Text Summarization. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) , 2019[DL+NLP]
Min Yang, Wenting Tu*, Wei Zhou, Qiao Liu, JiaZhu: Advanced Community Question Answering by Leveraging External Knowledge and Multi-task Learning. Knowledge-Based Systems , 2019 [DL+NLP]
2018:
Jun Chang, Wenting Tu*: A Stock-movement Aware Approach for Discovering Investors' Personalized Preferences in Stock Markets. Proceedings of the 30th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2018 [Recsys+Fintech]
Min Yang, Wenting Tu*, Qiang Qu, Zhou Zhao, Xiaojun Chen, Jia Zhu: Personalized Response Generation by Dual-learning based Domain Adaptation. Neural Networks (IF: 7.197), 2018 [DL+NLP]
Wenting Tu, Min Yang, David W.Cheung, Nikos Mamoulis: Investment Recommendation by Discovering High-quality Opinions in Investor based Social Networks. Information Systems (Elsevier) (IF: 2.551), 2018 [ML+Recsys+Fintech]
2017:
Wenting Tu, David W.Cheung, Nikos Mamoulis, Min Yang, Ziyu Lu: Activity Recommendation with Partners. ACM Transactions on the Web (IF: 1.163), 2017 [Recsys]
Wenting Tu, David W.Cheung, Nikos Mamoulis: More Focus on What You Care About: Personalized Top Reviews Set. Neurocomputing (IF: 3.241), 2017 [NLP+Recsys]
2016:
Wenting Tu, David W.Cheung, Nikos Mamoulis, Min Yang, Ziyu Lu: Investment Recommendation using Investor Opinions in Social Media. Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2016 (short paper) [ML+Recsys+Fintech]
2015:
Wenting Tu, David W.Cheung, Nikos Mamoulis, Min Yang, Ziyu Lu: Activity Partner Recommendation. Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2015 [Recsys]
Wenting Tu, David W.Cheung, Nikos Mamoulis: Time-sensitive Opinion Mining for Prediction. Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015 (poster) [NLP+Fintech]
Wenting Tu, David W.Cheung, Nikos Mamoulis: Improving Microblog Rtrieval from Exterior Corpus by Automatically Constructing Microblogging Corpus. Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015 (poster) [NLP]
Wenting Tu, David W.Cheung, Nikos Mamoulis, Min Yang, Ziyu Lu: Real-time Detection and Sorting of News on Microblogging Platforms. Proceedings of the 29th Pacific Asia Conference on Language, Information and Computing (PACLIC), 2015 (poster) [NLP]
Before 2015:
Wenting Tu, Shiliang Sun: Semi-supervised Feature Extraction for EEG Classification. Pattern Analysis and Applications (PAA), 2013 [ML+BCI]
Wenting Tu, Shiliang Sun: Dynamical Ensemble Learning with Model-friendly Classifiers for Domain Adaptation. Proceedings of the 21st International Conference on Pattern Recognition (ICPR), 2012 [ML]
Wenting Tu, Shiliang Sun: A Subject Transfer Framework for EEG Classification. Neurocomputing, 2012 [ML+BCI]
Wenting Tu, Shiliang Sun: Cross-domain representation-learning framework with combination of class-separate and domain-merge objectives. Workshop on Cross Domain Knowledge Discovery in Web and Social Network Mining (KDD-Workshop), 2012 [ML]
Wenting Tu, Shiliang Sun: Transferable Discriminative Dimensionality Reduction. Proceedings of the 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2011 [ML]
Wenting Tu, Shiliang Sun: Semi-supervised Feature Extraction with Local Temporal Regularization for EEG classification. Proceedings of the 21st International Joint Conference on Neural Networks (IJCNN), 2011 [ML+BCI]
Wenting Tu, Shiliang Sun: Importance Weighted Extreme Energy Ratio for EEG Classification. Proceedings of the 17th International Conference on Neural Information Processing (ICONIP), 2011 [ML+BCI]





荣誉奖励

上海财经大学第二届青年教师教学竞赛理工组三等奖
上海市研究生优秀成果（学位论文）
香港大学研究生奖学金（全额）
华东师范大学优秀毕业生
华东师范大学一等奖学金
Awards Third-class Prize, The 2nd young teachers' teaching competition, Shanghai University of Finance and Economics
Shanghai Outstanding Theses (awarded by the Shanghai Degree Committee)
Postgraduate Scholarships, The University of Hong Kong
Outstanding Graduates, East China Normal University
First-class Postgraduate Scholarship, East China Normal University

--------------- 感谢我的父母--------------
------Deepest gratitude to my parents------