Dr. Tao Li is currently an associate professor in the School of Computer Science, Florida International University. He
received his Ph.D. in computer science from the Department of Computer Science, University of Rochester in 2004. (My old homepage at Rochester). He was a recipient of NSF CAREER Award
(2006-2010) and multiple IBM Faculty Research Award. In 2009, he received
FIU's Excellence in Research and Creativities Award. In 2010, he
IBM Scalable Data Analytics Innovation Award.
He is on the editorial board of ACM
Transactions on Knowledge Discovery from Data (ACM TKDD),
IEEE Transactions on
Knowledge and Data Engineering (IEEE TKDE), and
Knowledge and Information System
Dr Tao Li's research explores two related topics on learning from
data---how to efficiently discover useful patterns and how to effectively
retrieve information. The interests lie broadly in data mining and machine
learning studying both the algorithmic and application issues. The
algorithmic aspects involve developing new scalable, efficient and
interactive algorithms that can handle very large databases. The underlying
techniques studied include clustering, classification, semi-supervised
learning, similarity and temporal pattern discovery. The application issues
focus on actual implementation and usage of the algorithms on a variety of
real applications with different characteristics including bioinformatics,
text mining, music information retrieval and event mining for computer
A Fast, Integrated, and User-Friendly System for Data Mining in Distributed
Environment developed by my group.
A new book entitled
"Music Data Mining" has appeared from CRC Press. Here
the publisher link
Excellence in Research Award, College of Engineering and Computing,
Florida International University, 2012
Affairs Committee (UAC) Award, 2011-2014
Excellence in Mentorship Award, College of Engineering and Computing,
Florida International University, 2011
- 2011 Kauffman
- IBM Scalable Data
Analytics Innovation Award, 2010
Foundation (NSF) Career Award,
- Excellence in Student
Mentoring Award, School of Computing and Information Sciences, Florida
International University, 2009
- Excellence in
Research Award, Florida International University, 2009
- Excellence in
Faculty Scholarship, Florida International University, 2008
- IBM Faculty Award,
2005, 2007 & 2008
- IBM Shared
University Research (SUR) Award, 2005
Affairs Committee (UAC) Award, 2005-2008
Research Award, School of Computer Science, Florida International
Data Mining Meets the Needs of
Disaster Information Management.
IEEE Transactions on Human-Machine Systems, 43(5): 451-464,
FIU-Miner: A Fast,
Integrated, and User-Friendly System for Data Mining in Distributed
Environment, In SIGKDD 2013
iHR: An Online
Recruiting System for Xiamen Talent Service Center,
In SIGKDD 2013.
An Integrated Framework
for Optimizing Automatic Monitoring Systems in Large IT Infrastructures,
In SIGKDD 2013.
- Cloud Analytics for Capacity
Planning and Instant VM Provisioning, IEEE
Transactions on Network and Service Management (TNSM)
, 2013, in press.
Summarization via Discriminative Sentence Selection,
Transactions on Knowledge Discovery from Data (ACM TKDD), 6(3):
Dynamic Query Forms for Database Queries,
IEEE Transactions on Knowledge and
Data Engineering (TKDE), 2013, in press.
A Learning Approach to
SQL Query Results Ranking Using Skyline and Users' Current Navigational
IEEE Transactions on Knowledge and
Data Engineering (TKDE), 2012, in press.
Non-negative Tri-factor Tensor Factorizations with
Knowledge and Information
Discovering Lag Intervals for Temporal Dependencies,
In SIGKDD 2012: 633-641, 2012.
MEET - A Generalized
Framework for Reciprocal Recommendation, In
Storyline from Microblogs, In
DClusterE: A Framework for Evaluating and
Understanding Document Clustering Using Visualization.
ACM Transactions on Intelligent Systems and Technology,
Self-adaptive Cloud Capacity Planning,
In IEEE SCC 2012:
Generating Pictorial Storylines via
Minimum-Weight Connected Dominating Set Approximation in Multi-view
Optimizing System Monitoring Configurations for
Non-Actionable Alerts, In
Clustering and Multi-Document Summarization,
Transactions on Knowledge Discovery from Data (ACM TKDD), 5(3):
Applying Data Mining Techniques to
Address Disaster Information Management Challenges on Mobile Devices,
2011, 283-291, 2011.
Combining File Content and File
Relations for Cloud Based Malware Detection,
2011, 222-230, 2011.
SCENE: A Scalable Two-stage
Personalized News Recommendation System,
In SIGIR 2011:125-134.
Clustering to Explore Multiple Clustering Views,
SDM 2011: 920-931.
LogSig: Generating System
Events from Raw Textual Logs, In
Natural Event Summarization,
CIKM 2011: 765-774.
ASAP: A Self-Adaptive Prediction System for Instant Cloud
Resource Demand Provisioning, In
Semi-supervised Hierarchical Clustering, In
Learning to Rank for Query-focused Multi-document Summarization,
- Community Discovery Using Nonnegative Matrix Factorization,
Data Mining and Knowledge
Discovery, 22(3): 493-521, 2011.
Matrix Factorization Based Approach for Active Dual Supervision from
Document and Word Labels, In
Integrating Clustering and Multi-Document Summarization by Bi-mixture
Probabilistic Latent Semantic Analysis (PLSA) with Sentence Bases,
A Framework for Generating System Events from Raw Textual Logs,In
ICDM 2010, 491-500, 2010.
Subset Non-Negative Matrix Factorization and its Applications to
ICDM 2010, 541-550, 2010.
Binary Matrix Factorization for Analyzing Gene
Expression Data, Data
Mining and Knowledge Discovery. 20(1): 28-52, 2010.
Automatic Malware Categorization Using Cluster
SIGKDD 2010: 95-104, 2010.
Using Data Mining Techniques to Address Critical
Information Exchange Needs in Disaster Affected Public-Private Networks,
Convex and Semi-Nonnegative Matrix
IEEE Trans. Pattern Anal. Mach. Intell. 32(1): 45-55, 2010.
Bridging Domains with Words: Opinion Analysis
with Matrix Tri-factorizations, In
DM 2010: 293-302.
A Non-negative Matrix Tri-factorization Approach to
Sentiment Classification with Lexical Prior Knowledge,
ACL 2009: 244-252.
Intelligent File Scoring System for Malware
Detection from the Gray List,
SIGKDD 2009: 1385-1394.
- Semi-Supervised Multi-Task Learning with Task Regularizations, In
Transformation for Cross-domain Sentiment Classification,
SIGIR 2009: 716-717.
IJCAI 2009: 1279-1284.
- Dynamic Active Probing of Helpdesk
Databases, In VLDB
Simultaneous Tensor Subspace Selection and Clustering: The Equivalence of
High Order SVD and K-Means Clustering, In
SIGKDD 2008: 327-335.
Multi-Document Summarization via Sentence-Level
Semantic Analysis and Symmetric Matrix Factorization,
in SIGIR 2008: 187-194.
Transformation from Word Space to Document Space, in
SIGIR 2008: 307-314.
- On the
Equivalence Between Nonnegative Matrix Factorization and Probabilistic
Latent Semantic Indexing, in:
Computational Statistics and Data Analysis,
52(8): 3913-3927, 2008.
Semi-Supervised Clustering via Matrix Factorization, In
SIAM DM 2008: 1-12.
Weighted Consensus Clustering, In
SIAM DM 2008: 798-809.
Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix
ICDM 2007: 577-582.
Adaptive Dimension Reduction Using Discriminant Analysis and K-means
Addressing Diverse User Preferences in SQL-Query-Result Navigation,
In SIGMOD 2007: 641-652.
Framework using Green's Function and Kernel Regularization with Application
for Recommender System, In SIGKDD 2007: 260-269.
Orthogonal Nonnegative Matrix Tri-factorizations for Clustering,
In SIGKDD 2006: 126-135.
- The Relationships among Various Nonnegative Matrix
Factorization Methods for Clustering, In
ICDM 2006: 362-371.
Intelligent Music Retrieval.
Transactions on Multimedia, 8(3): 564-574 (2006).
View On Clustering Binary Data,
Framework on Mining Logs Files for Computing System Management,In
SIGKDD 2005: 776-781.
A General Model
for Clustering Binary Data, In SIGKDD 2005: 188-197.
Clustering via Adaptive Subspace Iteration, In
SIGIR 2004: 218-225.
Criterion in Categorical Clustering, In
ICML 2004: 536-543.
Study of Feature Selection and Multiclass Classification Methods for Tissue
Classification Based on Gene Expression,
Comparative Study on Content-Based Music Genre Classification, In
SIGIR 2003: 282-289.
Meeting Time: Thursday: 7:50pm -- 10:30pm
Meeting Room: GL 137