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LINHONG ZHU www.linhongzhu.com Information Sciences Institute (310) · 448 · 9184 University of Southern California [email protected] EDUCATION Nanyang Technological University Singapore Ph.D. in Computer Engineering Advisor: Dr. Wee Keong Ng and Dr. Byron Choi Thesis: Efficient Methods for Querying and Mining Real-World Graph Data University of Science and Technology of China B.Eng. in Computer Science Aug 2006–Dec 2011 China Sep 2002–Jul 2006 RESEARCH INTERESTS Complex network analysis Sentiment analysis Predictive model Large scale graph mining, query and learning algorithms Dynamic sentiment monitoring and sentiment summarization Forecasting and link prediction modeling WORKING EXPERIENCE Information Sciences Institute Computer Scientist Postdoctoral Research Associate Institute for Infocomm Research Scientist-I Nanyang Technological University Research Assistant University of Southern California Aug 2015-present Jan 2013-Aug 2015 A*STAR, Singapore Oct 2010-Jan 2013 Singapore Jul 2006-Jul 2010 SELECTED PROJECTS Technical Knowledge Acquisition (TechKnAcq) • • Development of technology to generate a practical reading list for large, unstructured collections based on quantifying (a) ‘knowledge complexity and (b) ‘pedagogical value of resources Sponsor: Intelligence Advanced Research Projects Activity (IARPA) Domain-Specific Insight Graph (DIG) • • • May 2015-Present Sep 2015-Present Development of three core techniques: entity resolution, graph summarization and graph search within DIG, which is a domain-specific indexing, search and analysis system. Sponsor: Memex Program under Defense Advanced Research Projects Agency (DARPA) Media Coverage: 60 minutes, Scientific American, Wall St. Journal, BBC, and Wired. Situational Awareness in Social Media Linhong Zhu Jan 2013-Jun 2015 1 • • • The tools developed under this project enable analysts to perform real-time dynamic sentiment analysis on social media streams, extract useful knowledge from extremely noisy social media data, analyze spatial-temporal network data, identify influential people, bots and causal relationships based on observations of their activities, and predict social response. Sponsor: SMISC Program under Defense Advanced Research Projects Agency (DARPA) Media Coverage: DARPA Twitter Bot Challenge [5] covered by Business Insider and MIT Technology Review Crowd Activity Monitoring and Public Sentiment Analysis for Singapore National Day Parade 2012 Jan 2012-Jan 2013 • The tools developed under this project measure the successfulness of the National Day Parade 2012, by analyzing the sentiment of what the public feels about NDP2012 in the social media. HONORS AND AWARDS Postdoctoral Scholars Training & Travel Grants, University of Southern California, 2014 • Invited publication of [15] in ACM TODS on the best papers of SIGMOD 2010 [19] • Nanyang Technological University Graduate Student Fellowship (S$30,000/year for four years) • Undergraduate Research Award, University of Science and Technology of China, 2005 • Outstanding Award in Robot Competition, University of Science and Technology of China, 2005 • Outstanding Student Scholarship, University of Science and Technology of China, 2003–2005 (3 times) • Outstanding Freshmen Scholarship, University of Science and Technology of China, 2002 • TEACHING EXPERIENCE Teaching Assistant: Introduction to Programming Teaching Assistant: Data Structure and OOP Student Mentor: A*STAR research attachment program students: Karan Singh, Simon Jumel Fall 2009 Spring 2009 Summer 2011 and Winter 2011 PUBLICATIONS [1] [2] [3] [4] [5] [6] [7] Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, and Yan Liu. “Latent Space Model for Road Networks to Predict Time-Varying Traffic”. In: To be appeared in 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2016. Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, and Linhong Zhu. “Task selection in spatial crowdsourcing from worker’s perspective”. In: GeoInformatica 20.3 (2016), pp. 529–568. Jonathan Gordon, Linhong Zhu, Gully Burns, Aram Galstyan, and Prem Natarajan. “Modeling Concept Dependencies in a Scientific Corpus”. In: To be appeared in the annual meeting of the Association for Computational Linguistics (ACL). 2016. Laura M. Smith, Linhong Zhu, Kristina Lerman, and Allon G. Percus. “Partitioning Networks with Node Attributes by Compressing Information Flow”. In: To be appeared in ACM Transactions on Knowledge Discovery from Data (TKDD) (2016). VS Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, et al. “The DARPA Twitter Bot Challenge”. In: IEEE Computer Society 49 (2016), pp. 38–46. Linhong Zhu and Kristina Lerman. “Attention Inequality in Social Media”. In: CoRR abs/1601.07200 (2016). Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, and Aram Galstyan. “Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization”. In: To be appeared in IEEE Transactions on Knowledge and Data Engineering (TKDE) (2016). Linhong Zhu 2 [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] Dingxiong Deng, Cyrus Shahabi, and Linhong Zhu. “Task matching and scheduling for multiple workers in spatial crowdsourcing”. In: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2015. 2015, 21:1–21:10. Linhong Zhu, Sheng Gao, Sinno Jialin Pan, Haizhou Li, Dingxiong Deng, and Cyrus Shahabi. “The Pareto Principle is Everywhere: Finding Informative Sentences for Opinion Summarization through Leader Detection”. In: Chapter of Book “Recommendation and Search in Social Networks” (2015). Linhong Zhu and Kristina Lerman. “A Visibility-based Model for Link Prediction in Social Media”. In: International Conference on Social Computing (SocialCom). 2014, pp. 236–243. Linhong Zhu, Aram Galstyan, James Cheng, and Kristina Lerman. “Tripartite Graph Clustering for Dynamic Sentiment Analysis on Social Media”. In: Proceedings of the ACM International Conference on Management of Data (SIGMOD). 2014, pp. 1531–1542. Laura M. Smith, Linhong Zhu, Kristina Lerman, and Zornitsa Kozareva. “The Role of Social Media in the Discussion of Controversial Topics”. In: International Conference on Social Computing (SocialCom). 2013. Linhong Zhu, Sheng Gao, Sinno Jialin Pan, Haizhou Li, Dingxiong Deng, and Cyrus Shahabi. “Graph-based informative-sentence selection for opinion summarization”. In: Advances in Social Networks Analysis and Mining. 2013, pp. 408–412. James Cheng, Linhong Zhu, Yiping Ke, and Shumo Chu. “Fast algorithms for maximal clique enumeration with limited memory”. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2012, pp. 1240–1248. James Cheng, Yiping Ke, Ada Wai-Chee Fu, Jeffrey Xu Yu, and Linhong Zhu. “Finding maximal cliques in massive networks”. In: ACM Transactions on Database Systems 36.4 (2011). Linhong Zhu, Wee Keong Ng, and James Cheng. “Structure and attribute index for approximate graph matching in large graphs”. In: Information Systems 36.6 (2011). Linhong Zhu, Wee Keong Ng, and Shuguo Han. “Classifying Graphs Using Theoretical Metrics: A Study of Feasibility”. In: Proceedings of the 16th International Conference on Database Systems for Advanced Applications. 2011, pp. 53–64. Linhong Zhu, Aixin Sun, and Byron Choi. “Detecting spam blogs from blog search results”. In: Information Processing & Management 47.2 (2011). James Cheng, Yiping Ke, Ada Wai-Chee Fu, Jeffrey Xu Yu, and Linhong Zhu. “Finding maximal cliques in massive networks by H*-graph”. In: Proceedings of the ACM International Conference on Management of Data (SIGMOD). 2010, pp. 447–458. Linhong Zhu, Byron Choi, Bingsheng He, Jeffrey Xu Yu, and Wee Keong Ng. “A Uniform Framework for Ad-Hoc Indexes to Answer Reachability Queries on Large Graphs”. In: Proceedings of the 14th International Conference on Database Systems for Advanced Applications. 2009, pp. 138– 152. Linhong Zhu, Aixin Sun, and Byron Choi. “Online spam-blog detection through blog search”. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM). 2008, pp. 1347–1348. PROFESSIONAL SERVICE Journal reviews ACM Transactions on Speech and Language Processing, Electronic Commerce Research and Applications, Knowledge and Information Systems (KAIS), Information Sciences, ACM Transactions on Intelligent Systems and Technology (TIST), IEEE Transactions on Knowledge and Data Engineering (TKDE), PLOS ONE, Social Network Analysis and Mining Conference Program Committee Thirtieth Annual Conference on Neural Information Processing Systems (NIPS) External conference reviews Linhong Zhu 2016 3 ACM International Conference on Data Management (SIGMOD), The International Conference on World Wide Web (WWW) 2015 The 6th International Conference on Social Informatics (Socinfo), The International Conference on World Wide Web (WWW), The IEEE International Conference on Big Data, ACM Conference on Knowledge Discovery and Data Mining (SIGKDD), International Conference on Very Large Data Bases (PVLDB), International Conference on Web-Age Information Management (WAIM), International Conference on Database Systems for Advanced Applications (DASFAA) 2014 International Conference on Advances in Social Networks Analysis and Mining (ASONAM), International Conference on Database and Expert Systems Applications (DEXA), Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2010 International Conference on Web-Age Information Management (WAIM) 2008 LEADERSHIP AND VOLUNTEER EXPERIENCE • • • • • • ISI representative, University of Southern California Postdoctoral Association, 2013–2014. Member of Social Committee at Institute for Infocomm Research, 2010–2013. Member of China United Alumni Association at Singapore Tech Exchange Group, 2010–2012. Volunteer for Singapore Heart Foundation, 2009–2010. University of Science and Technology of China Alumni Association at Singapore, 2006–2012. Dept. Publicity, Student Association, University of Science and Technology of China, 2003–2005. TALKS • • • • • • • • • • • • Discovering Big Data’s Value through Scalable Graph Analytics. UCLA, USA, March 2016. Discovering Big Data’s Value through Scalable Graph Analytics. Amazon, USA, June 2015. Discovering Big Data’s Value through Scalable Graph Analytics. NEC Lab, USA, May 2015. Large-scale Social Media Analysis with Structure and Content Information. ShanghaiTech University, China, Dec 2014. Tripartite Graph Clustering for Dynamic Sentiment Analysis in Social Media. SIGMOD, USA, Jun 2014. A Visibility-based Model for Link Prediction in Social Media. Stanford University, USA, May 2014. Graph-based Informative Sentence Selection for Opinion Summarization. ASONAM, Canada, Aug 2013. Structure and Context Aware Network Analysis. Information Sciences Institute, USA, Jul 2012. Efficient Methods for Querying and Mining Real-World Graph Data. Ph.D. oral defense. Nanyang Technological University, Singapore, Sep 2011. An Automatical System for Sentiment Analysis based on Leader Identification. Institute for Infocomm Research, Singapore, Jun 2011. A Uniform Framework for Ad-hoc Indexes to Answer Reachability Queries on Large Graphs. University of Queensland, Australia, Apr 2009. Partitioning Algorithms for Querying Large Graphs. Nanyang Technological University, Aug 2008. Linhong Zhu 4