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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)
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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)
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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