My name is Yongfeng Zhang, Postdoc Research Associate in the College of Information and Computer Science (CICS) at the University of Massachusetts (UMass) Amherst. Prior to this I was an Assistant Specialist in School of Engineering (SoE), UC Santa Cruz (UCSC). I have obtained my PhD and Bachelor's Degree in Computer Science from Department of Computer Science and Technology of Tsinghua University, researching on Machine Learning, Computational Economics, Personalization Theories, and Sentiment Analysis. I have also obtained my Bachelor's Degree in Economics from the National School of Development, Peking University. I am a Siebel Scholar and a Baidu Scholar, as well as a Microsoft and IBM PhD Fellowship.
- Machine Learning and Data Mining
- Economic Data Science
- Computational and Internet Economics
- Personalized Recommender Systems
- Textual Sentiment Analysis
Within the above areas, I focus on Econimic Web Intelligence, including the application and analysis of Economic theories in commonly used web applications, such as recommendation and search, especially on the research of Internet Welfare Economics. I also reasearch on the sentiment analysis of natural language such as user reviews, and its application in e-commerce, recommender systems, and economical models.
Ph.D. in Computer Science, Tsinghua University
2011.09 – 2016.07; Study at the Department of Computer Science; major in Machine Learning, Computational Economics, Recommender Systems, and Sentiment Analysis; Awarded as Beijing Excellent PhD Graduate and Tsinghua Excellent PhD Graduate.
Bachelor in Computer Science, Tsinghua University
2007.09 – 2011.07; Also studied in the Department of Computer Science, Tsinghua University; Awarded as an Excellent Graduate.
Bachelor in Economics, Peking University
2014.09 – 2016.07; National School of Development, Peking University, Beijing, China.
Postdoctoral Research Associate, College of Information and Computer Science (CICS), University of Massachusetts Amherst (UMass)
2016.09 – current; Research in Economic Web Intelligence (e.g., Recommendation and IR), in cooperation with Professor W. Bruce Croft.
Assistant Specialist, School of Engineering (SoE), UC Santa Cruz (UCSC)
2015.07 – 2016.09; Research in Personalized Recommendation and Computational Economics, in cooperation with Professor Yi Zhang.
Research Assistant, School of Computing (SoC), National University of Singapore (NUS)
2013.12 – 2015.03; Personalized Recommendation and Search, NExT Search Center, in cooperation with Prof. Min-Yen Kan and Chua Tat-Seng.
- PC Member:
CIKM 2014, CIKM 2015, NAACL-HLT 2016, INTELLI 2016, WEB 2017, WSDM 2017, WWW 2017, SIGIR 2017, IJCAI 2017
ACM Transactions on Information Systems (TOIS), ACM Transactions on Knowledge Discovery from Data (TKDD)
ACM Transactions on Intelligent Systems and Technology (TIST), IEEE Transactions on Multimedia (MM)
Frontiers of Computer Science (FCS), Information Retrieval Journal (IRJ), Information Processing Letters (IPL)
IJCAI 2013, AAAI 2013, WSDM 2014, AAAI 2014, WWW 2015, SIGIR 2015, IJCAI 2015, KDD 2015, SIGIR 2016, KDD 2016
Honors and Awards:
- 2016 Tsinghua University Academic Rising Star (21 out of 10, 000+)
- 2016 Excellent PhD Dissertation of Tsinghua Univeristy
- 2016 Beijing Excellent PhD Graduate
- 2016 Tsinghua University Excellent PhD Graduate
- 2015 Microsoft PhD Fellowship (only 13 out of 90 distinguished PhD candidates from 40 leading research universities/institutions worldwide)
- 2014 Siebel Scholar (awarded for academic excellence to 85 top students from the world's 19 selected leading graduate schools)
- 2014 Baidu Scholar (only 8 out of more than 1,600 applicants worldwide)
- 2014-2015 IBM International PhD Fellowship
- 2014 ACM RecSys Student Travel Support
- 2013, 2014 ACM SIGIR Student Travel Support
- 2012 Google Excellent Student Scholarship
- 2011 Excellent Graduate of Computer Science Department, Tsinghua University
- 2010 IBM Scholarship of Tsinghua University
- 2008 Excellent Volunteer of the 29th Beijing Olympic Games
- 2007 First Prize of National High School Math League
- 2017-01-26 Will give a talk Unstructured Data Mining for Web Personalization in Boston University.
- 2016-10-17 See how machine learninhg can help to quantity essential economic concepts and model the online economy in our paper “Multi-Product Utility Maximization for Economic Recommendation” accepted as a full paper in WSDM 2017.
- 2016-06-05 We are organizing the Tsinghua University Forum on Intelligent Recommendation, with distinguished keynote speakers Prof. Jian-Yun Nie from UMontreal, Dr. Xing Xie from MSRA, Dr. Quan Yuan from Alibaba, and Dr. Yading Yue from Tencent. Welcome to join!
- 2016-06-01 Will give a talk Personalized Recommendation based on Internet Surplus Maximization in Renmin University of China.
- 2016-05-18 Gave a talk Internet Welfare Economics in School of Computer Science, Beijing University of Technology.
- 2015-12-16 Let's promote the Web Intelligence towards Social Good! See our paper “Economic Recommendation with Surplus Maximization” accepted as a full paper in WWW 2016.
- 2015-04-17 Nearly driven crazy by the countless and continuously emerging approachs of shilling attach in practical recommender systems? See our paper “Catch the Black Sheep: Unified Framework for Shilling Attack Detection based on Fraudulent Action Propagation” in IJCAI 2015.
- 2015-01-18 Leverage the rather mature time series analysis techniques for business intelligence. See our paper “Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis” accepted as a full paper by WWW 2015.
- 2014-11-21 It's time to care about the role of textual reivews in recommender systems! See our research proposal “Incorporating Phrase-level Sentiment Analysis on Textual Reviews for Personalized Recommendation” accepted by WSDM 2015.
- 2014-11-10 Our paper “SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering” is accepted as a full paper by AAAI 2015.
- 2014-08-09 Our paper entitled “Understanding the Sparsity: Augmented Matrix Factorization with Sampled Constraints on Unobservables” is accepted as a long paper by CIKM 2014.
- 2014-07-07 My research proposal “Browser-Oriented Universal Cross-Site Recommendation and Explanation based on User Browsing Logs” is accepted by the Doctoral Symposium of the RecSys 2014 conference.
- 2014-04-12 Our paper “Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis” is accepted as a long paper by SIGIR 2014.
- 2014-04-12 Our paper entitled “Do Users Rate or Review? Boost Phrase-level Sentiment Labeling with Review-level Sentiment Classification” has been accepted as a short paper by SIGIR 2014.
- 2013-12-08 I am visiting as a research assistant at the School of Computing (SoC) in the National University of Singapore (NUS) for about 3 months.
- 2013-09-15 Our paper entitled “Towards the Adaption to the Open Texture of Law” was accepted by CSMES 2013.
- 2013-08-18 Our paper entitled “A Unified Framework for Emotional Elements Extraction based on Finite State Matching Machine” was accepted as a long paper by NLPCC 2013.
- 2013-04-05 Our paper “Improve Collaborative Filtering Through Bordered Block Diagonal Form Matrices” was accepted as a long paper by SIGIR 2013.
- 2013-02-08 Our paper entitled “Localized Matrix Factorization for Recommendation based on Matrix Block Diagonal Forms” was accepted as a long paper by WWW 2013.
- 2013-02-05 Our paper “A General Collaborative Filtering Framework based on Matrix Bordered Block Diagonal Forms” was accepted as a short paper by ACM Hypertext 2013.
- 2013-01-10 Our paper entitled “Is Fengshui Science or Superstition? A New Criterion for Judging the Value of Knowledge Systems” is published in Vol.3 No.1 in Journal of Literature and Art Studies.
- 2012-10-08 I gave a talk about “Framework of Distributed Recommender Systems“ in State Key Laboratory of Intelligent Technology and Systems of CS Dept. at Tsinghua University.
- 2012-04-23 I gave a talk about “A Suervey of Recommender Systems“ in State Key Laboratory of Intelligent Technology and Systems of CS Dept. at Tsinghua University.