Liang Wu

Liang Wu, Ph.D. [CV]
Machine Learning Data Scientist
Airbnb
Airbnb Data Science

Liang Wu is a machine learning data scientist at Airbnb. He focuses on building search and recommender systems of Airbnb Experiences. He obtained Ph.D. (2019) with Professor Huan Liu from Arizona State University, M.S. (2014) from University of Chinese Academy of Sciences, and B.S. (2011) from Beijing University of Posts and Telecom. His research interests include data mining, applied machine learning, information retrieval and recommender systems.

Contact

Email: liang.wu at airbnb.com

inMail Phone: 48o-738-841o

News

[2020-11] Invited to serve as a PC member for KDD'21.
[2020-10] A regular paper accepted by WSDM'21.
[2020-08] Invited to serve as a PC member for AAAI'21, IJCAI'21, and PAKDD'21.
[2020-06] Invited to serve as a Program Committee member for WSDM'21.
[2020-05] A regular paper accepted by SIGIR'20.
[2020-01] Invited to serve as a Program Committee member for KDD'20.
[2020-01] Invited to serve as a Program Committee member for SIGIR'20.
[2020-01] Invited to serve as a Program Committee member for ASONAM'20
[2019-12] Invited to serve as a Program Committee member for PAKDD'20.
[2019-09] Invited to review for ICLR'20.
[2019-08] Invited to serve as a Program Committee member for AAAI'20.
[2019-07] Received computer science outstanding PhD student award of ASU.
[2019-07] Invited to serve as a Program Committee member for WSDM'20.
[2019-06] A regular paper accepted by WebSci'19, will present it in Boston, MA.
[2019-06] Invited to serve as an industry-track Program Committee member for CIKM'19.
[2019-06] A regular paper accepted by ASONAM'19.
[2019-05] Invited to serve as a research-track Program Committee member for CIKM'19.
[2019-04] Invited to serve as a Program Committee member for BigData'19.

Media Coverage [show/hide]

Professional Activities

Program Committee: AAAI'20'19'18, SIGIR'19'18, KDD'19'18, WSDM'20'19, CIKM'19, PAKDD'18, BigData'19'18.

Journal Reviewer: CSUR, TKDE, TKDD, TOIS, TIST, SNAM, DMKD, WWW J, Intelligent Systems, IRJ, Information Retrieval Journal, TNNLS.

Awards

Third (3/164) on the Leaderboard, Honorable Mention Award of KDD Cup 2012

ASU Teaching Excellence Award Nomination, 2014

Outstanding PhD Student in CSE, ASU, 2019

Conference Papers

Liang Wu, Mihajlo Grbovic, Jundong Li, Toward User Engagement Optimization in 2D Presentation. ACM International Conference on Web Search and Data Mining (WSDM 2021), March 8-12, 2021. Jerusalem, Isreal. PDF
Liang Wu, Mihajlo Grbovic, How Airbnb Tells You Will Enjoy Sunset Sailing in Barcelona? Recommendation in a Two-Sided Travel Marketplace. ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), July 25-30, 2020. Xi'an, China. PDF
Liang Wu, Diane Hu, Liangjie Hong, Huan Liu, Turning Clicks into Purchases: Revenue Optimization for Product Search in E-Commerce. ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), July 8-12, 2018. Ann Arbor, Michigan, USA. PDF
Liang Wu, Huan Liu, Debunking Rumors in Social Networks: A Timely Approach. ACM Web Science Conference 2019 (WebSci 2019), June 30-July 3, 2019, Boston, MA, USA. PDF
Jundong Li, Liang Wu, Ruocheng Guo, Chenghao Liu, and Huan Liu, Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019), June 30-July 3, 2019, Boston, MA, USA. PDF
Liang Wu, Jundong Li, Fred Morstatter, Huan Liu, Toward Relational Learning with Misinformation. SIAM International Conference on Data Mining (SDM 2018), May 3-5, 2018. San Diego, California, USA. PDF Slides Poster BibTex
Liang Wu, Huan Liu, Tracing Fake-News Footprints: Characterizing Social Media Messages by How They Propagate. The 11th ACM International Conference on Web Search and Data Mining (WSDM 2018), Feb 6-8, 2018. Los Angeles, California, USA. PDF Slides BibTex. The Morning Paper, IBTimes, AlterNet, Salon, GOOD, MSU Today.
Jundong Li, Liang Wu, Harsh Dani, and Huan Liu, Unsupervised Personalized Feature Selection , The 32nd AAAI Conference on Artificial Intelligence (AAAI), Feb 2-7, 2018. New Orleans, LA, USA.
Jundong Li, Kewei Cheng, Liang Wu, and Huan Liu, Streaming Link Prediction on Dynamic Attributed Networks , The 11th ACM International Conference on Web Search and Data Mining (WSDM 2018), Feb 6-8, 2018. Los Angeles, California, USA.
Liang Wu, Xia Hu, Fred Morstatter, Huan Liu, Adaptive Spammer Detection with Sparse Group Modeling. The 11th International AAAI Conference on Web and Social Media (ICWSM 2017), May 15-18, 2017. Montreal, Canada. PDF Slides BibTex
Liang Wu, Xia Hu, Huan Liu, Early Identification of Personalized Trending Topics in Microblogging, poster paper. The 11th International AAAI Conference on Web and Social Media (ICWSM 2017), May 15-18, 2017. Montreal, Canada. PDF Poster BibTex
Liang Wu, Xia Hu, Fred Morstatter, Huan Liu. Detecting Camouflaged Content Polluters, poster paper. The 11th International AAAI Conference on Web and Social Media (ICWSM 2017), May 15-18, 2017. Montreal, Canada. PDF Slides BibTex
Liang Wu, Jundong Li, Xia Hu, Huan Liu, Gleaning Wisdom from the Past: Early Detection of Emerging Rumors in Social Media, SIAM International Conference on Data Mining (SDM 2017). PDF Slides BibTex
Jundong Li, Liang Wu, Osmar R. Za�ane, and Huan Liu, Toward Personalized Relational Learning , SIAM International Conference on Data Mining (SDM 2017).
Liang Wu, Xia Hu, Huan Liu, Relational Learning with Social Status Analysis, The 9th International Conference on Web Search and Data Mining (WSDM 2016). PDF Slides BibTex
Justin Sampson, Fred Morstatter, Liang Wu, and Huan Liu, Leveraging the Implicit Structure within Social Media for Emergent Rumor Detection, in Proceedings of 25th ACM International Conference on Information and Knowledge Management (CIKM 2016).
Fred Morstatter, Liang Wu, Tahora H. Nazer, Kathleen M. Carley, and Huan Liu, A New Approach to Bot Detection: Striking the Balance between Precision and Recall, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016). ASU Now
Jundong Li, Xia Hu, Liang Wu, and Huan Liu, Robust Unsupervised Feature Selection on Networked Data, in Proceedings of SIAM International Conference on Data Mining (SDM 2016).
Liang Wu, Liang Du, Bo Liu, Guandong Xu, Yong Ge, Yanjie Fu, Jianhui Li, Yuanchun Zhou and Hui Xiong, Heterogeneous Metric Learning with Content-based Regularization for Software Artifact Retrieval, in Proceedings of the IEEE International Conference on Data Mining (ICDM 2014).
Liang Wu, Alvin Chin, Guandong Xu, Liang Du, Xia Wang, Kangjian Meng, Yonggang Guo, and Yuanchun Zhou, Who Will Follow Your Shop? Exploiting Multiple Information Sources in Finding Followers, International Conference on Database Systems for Advanced Applications (DASFAA 2013).
Liang Wu, Yuanchun Zhou, Fei Tan, Fenglei Yang, and Jianhui Li, Generating Syntactic Tree Templates for Feature-based Opinion Mining, in Proceedings of 7th International Conference on Advanced Data Mining and Applications (ADMA 2011).

Qiuxiang Dong, Zhi Guan, Liang Wu, and Zhong Chen, Fuzzy Keyword Search Over Encrypted Data in the Public Key Setting, in Proceedings of Web-Age Information Management (WAIM'2013).

Tutorials

Liang Wu, Filippo Menczer, Huan Liu, Mining Misinformation in Social Media: Understanding Its Rampant Spread, Harm, and Intervention, ICDM 2017 Tutorial. Tutorial Site
Liang Wu, Fred Morstatter, Huan Liu, Misinformation in Social Media: Diffusion, Detection and Intervention., SBP-BRIMS 2016 Tutorial. Link PDF

The blog article on KDNuggets introduces the key terms about mining misinformation.

Book Chapters

Liang Wu, Huan Liu, Detecting Crowdturfing in Social Media, Encyclopedia of Social Network Analysis and Mining, Springer, 2016. PDF

Liang Wu, Fred Morstatter, Xia Hu, Huan Liu, Mining Misinformation in Social Media, Big Data in Complex and Social Networks, CRC Press, 2016. 123-152. PDF

Journal Papers

Liang Wu, Fred Morstatter, and Huan Liu. SlangSD: Building and Using a Sentiment Dictionary of Slang Words for Short-Text Sentiment Classification. Journal of Language Resources and Evaluation (2018).
Fred Morstatter, Liang Wu, Uraz Yavanoglu, Stephen S. Corman, and Huan Liu. Identifying Framing Bias in Online News. ACM Transactions on Social Computing (2018).
Yuanchun Zhou, Mingjie Tang, Weike Pan, Jinyan Li, Weihang Wang, Jing Shao, Liang Wu, Jianhui Li, Qiang Yang, Baoping Yan, Bird Flu Outbreak Prediction via Satellite Tracking, IEEE Intelligent Systems, 2014.
Yuwei Wang, Yuanchun Zhou, Ying Liu, Ze Luo, Danhuai Guo, Jing Shao, Fei Tan, Liang Wu, Jianhui Li, Baoping Yan, A grid-based clustering algorithm for wild bird distribution, Frontiers of Computer Science, 2013.

Posters and Workshop Papers

Liang Wu, Early Detection of Misinformation in Social Media, Doctoral Forum, SIAM International Conference on Data Mining (SDM 2017).
Liang Wu, Fred Morstatter, Daniel J. Baird, Justin Sampson, Kai Shu, and Huan Liu, Integrating Interactive and Computational Approaches for News Understanding, SBP Grand Data Challenge, International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP 2016).
Liang Wu, Bin Cao, Yuanchun Zhou, Jianhui Li, Improving Query Suggestion through Noise Filtering and Query Length Prediction, WWW (Companion Volume) 2014.
Bo Liu, Liang Wu, Jianqiang Li, Ji-Jiang Yang, Exploiting Incremental Reasoning in Healthcare Based on Hadoop and Amazon Cloud, Workshops at AAAI 2014.
Qi Hu, Keke Cai, Weishan Dong, Liang Wu, Guanqun Zhang, and Heyuan Huang, Content Mapping Recommendation for IT Compliance Automation, 17th International Workshop on the Web and Databases (WebDB'2014).
Liang Wu, Alvin Chin, Yuanchun Zhou, Xia Wang, Kangjian Meng, Yonggang Guo, and Jianhui Li, Context-aware Prediction of User's First Click, KDD 2012 Workshop on Context Discovery and Data Mining.

Students Mentored

I served as committee member for Venkatesh Magham's Master's Thesis. We worked on adversarial attack algorithms in social media.

TweetTracker 2.0

I led the efforts to revamp TweetTracker with Shobhit Sharma (front-end development), Ashutosh Bhadke (back-end development) and Kunal Bansal (system integration).

Geospatial Tweet Data Visualization

I led a capstone project to build an interactive explorer of tweets with Corey Mcneish and Christina Wilmot (data analysis), Raquel Lippincott and Spencer Graf (data visualization), Matthew Gross and Philip Terzic (data crawling).

Fake News Geolocation Visualization

I served as the second reader for Lilian Ngweta's Honor's Thesis. We bulit a fake news visualization system that illustrated how misinformation propagated in the U.S. geographically.

Professional Experience

Research Intern in Nokia Research Center, Microsoft Research Asia, and NEC Labs China.