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LINHONG ZHU
www.linhongzhu.com
Information Sciences Institute
(213)−880−3429
University of Southern California
[email protected]
EDUCATION
Nanyang Technological University
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
Singapore
Aug 2006–Dec 2011
China
Sep 2002–Jul 2006
WORKING EXPERIENCE
Information Sciences Institute, University of Southern California, Los Angeles
Computer Scientist
Aug 2015-present
Postdoctoral Research Associate
Jan 2013–Aug 2015
Institute for Infocomm Research, A*STAR, Singapore
Scientist-I
Oct 2010–Jan 2013
Nanyang Technological University, Singapore
Research Assistant
Aug 2006–Jul 2010
SELECTED PROJECTS
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Domain-Specific Insight Graph (DIG)
Sep 2015–Present
Propose an unsupervised entity resolution framework that determines whether two nodes refer to the
same real-world entity using the multi-type graph summarization approach [9], and apply to human
trafficking domain (e.g., merging two different names used by the same victim) and illicit weapon
trading domain (e.g., matching users from one web site to another)
Media Coverage: 60 minutes, Scientific American, Wall St. Journal, BBC, and Wired.
Technical Knowledge Acquisition (TechKnAcq)
May 2015–Present
Generate a personalized reading list for diverse learners from large, unstructured corpora by quantifying
(a) “knowledge complexity” [3] and (b) “pedagogical value” of resources
Provide user modeling and personalized educational resource recommendation
Situational Awareness in Social Media
Jan 2013–Jun 2015
Perform real-time sentiment analysis with tripartite graph modeling on large-scale twitter data [13]
Identify influential people and bots [6], and predict social response [8] with latent space modeling
Media Coverage: DARPA Twitter Bot Challenge [6] covered by Business Insider and MIT Technology
Review
Public Sentiment Analysis for Singapore National Day Parade
Jan 2012–Jan 2013
Measure the successfulness of National Day Parade 2012 of Singapore by analyzing the sentiment of
public feelings from the social media feeds (e.g., Facebook, YouTube, Twitter)
Monitor and detect trending topics and events that are related to National Day Parade
Linhong Zhu
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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: Proceedings of the 22nd
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: The annual meeting of the Association for
Computational Linguistics (ACL). 2016.
Kuan Liu, Xing Shi, Anoop Kumar, Linhong Zhu, and Prem Natarajan. “Temporal Learning and
Sequence Modeling for a Job Recommender System”. In: RecSys Challenge (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 Temporal
Latent Space Inference for Link Prediction in Dynamic Social Networks”. In: IEEE Transactions
on Knowledge and Data Engineering (TKDE) (2016).
Linhong Zhu, Majid Ghasemi-Gol, Pedro Szekely, Aram Galstyan, and Craig Knoblock. “Unsupervised Entity Resolution on Multi-type Graphs”. In: International Sematic Web Conference
(ISWC)[Best Paper Award]. 2016.
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, 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).
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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 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.
GRANTS AND AWARDS
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Best Paper Award in ISWC 2016 [9]
Co-PI, DSBox: Data Scientist In A Box (Pending), 7.4M
Co-PI, Programming Analytics for Graphs on Memory-optimized Architectures (Pending), 9.5M
Postdoctoral Scholars Training & Travel Grants, University of Southern California, 2014
Invited publication of [17] in ACM TODS on the best papers of SIGMOD 2010 [21]
Nanyang Technological University Graduate Student Fellowship (S$30,000/year for four years)
Excellent Award in Robot Competition, University of Science and Technology of China, 2005
Excellent Student Scholarship, University of Science and Technology of China, 2003–2005 (3 times)
Excellent Freshmen Scholarship, University of Science and Technology of China, 2002
TEACHING EXPERIENCE
Ph.D. Mentees
Majid Ghasemi-Gol (advisor: Dr. Pedro Szekely)
Kuan Liu (advisor: Dr. Prem Natarajan)
Yike Liu (Summer Intern)
Fall 2015–present
Spring 2016-present
Summer 2016
Master Mentees
LingZhe Teng
Spring 2016
Undergraduate Mentees
Karan Singh
Simon Jumel
Winter 2011
Summer 2011
Teaching Assistant
Introduction to Programming
Data Structure and OOP
Fall 2009
Spring 2009
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.
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.
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PROFESSIONAL SERVICE
Journal reviews
ACM Transactions on Speech and Language Processing, 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 reviews
International Conference on Web Search and Data Mining (WSDM)
2018
Artificial Intelligence and Statistics Conference (AISTATS)
2017
Thirtieth Annual Conference on Neural Information Processing Systems (NIPS)
2016
ACM International Conference on Data Management (SIGMOD), The International Conference on
World Wide Web (WWW)
2015
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 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
TALKS
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Discovering Big Data’s Value through Scalable Graph Analytics. UCLA, USA, Mar 2016.
Discovering Big Data’s Value through Scalable Graph Analytics. Amazon, USA, Jun 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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