Large Scale Data Analytics, Numerical Computing, Visual Analytics, Text and Social Network Analysis,
High Performance Computing, Bioinformatics

• Constrained Low Rank Approximation for Effective and Efficient Data Analytics
  • Nonnegative Matrix and Tensor Factorizations
  • Co-embedding Learning and Link Prediction for Multi-view Data in Healthcare Analytics
  • Hypergraph Analysis, Clustering, and Community Detection
  • Text Analysis and Fast Algorithms for Large-scale Topic Discovery
  • Adaptive Dimension Reduction and Classification
• High Performance Computing for Constrained Low-Rank Approximation
  • Open-source MPI-based Software Development
  • Robust, Scalable and Practical Large Scale Low-Rank Approximation
  • Lower Dimensional Representation/Embedding of Massive Data
• Visual Analytics for Large-scale Topic Modeling and Search Space Reduction
  • Fast Algorithms on Imperfect, Heterogeneous, Distributed Data for Interactive Analysis
  • Dimension Reduction and Data Reduction: Foundations for Visualization
  • Multi-scale Characterization of Document Themes, Granularity, and Triage