Shusen Liu

Postdoc Researcher
Computation/Center for Applied Scientific Computing
Email: liu42@llnl.gov
Phone: +19254220744

My research interests lie primarily in data science, particularly for data that is high-dimensional in nature. I am interested in the applications of high-dimensional data visualization techniques for understanding/interpreting machine learning models and various simulation ensembles.

 

Journal Publications:

NLIZE: A Perturbation-Driven Visual Interrogation Tool for Analyzing and Interpreting Natural Language Inference Model 
Shusen Liu, Zhimin Li, Tao Li, Vivek Srikumar, Valerio Pascucci and Peer-Timo Bremer,
IEEE Transactions on Visualization and Computer Graphics (InfoVis 2018), to appear

Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections 
Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy and Peer-Timo Bremer,
Computer Graphics Forum (EuroVis 2018), to appear

Visual Exploration of Semantic Relationships in Neural Word Embeddings 
Shusen Liu, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Vivek Srikumar, Bei Wang, Yarden Livnat and Valerio Pascucci.
IEEE Transactions on Visualization and Computer Graphics (InfoVis 2017), 24(1), 553-562, 2018

Visualizing High-Dimensional Data: Advances in the Past Decade. 
Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer and Valerio Pascucci.
IEEE Transactions on Visualization and Computer Graphics, 23(3), 1077-2626, 2017

Grassmannian Atlas: A General Framework for Exploring Linear Projections of High-Dimensional Data. 
Shusen Liu, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Bei Wang, Brian Summa, and Valerio Pascucci.
Computer Graphics Forum (CGF), 35(3), 1-10, 2016

Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections. 
Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer and Valerio Pascucci.
Computer Graphics Forum (CGF), 34(3), 271-280, 2015

Analyzing Simulation-Based PRA Data Through Traditional and Topological Clustering: A BWR Station Blackout Case Study. 
Dan Maljovec, Shusen Liu, Bei Wang, Valerio Pascucci, Peer-Timo Bremer, Diego Mandelli and Curtis Smith.
Reliability Engineering & System Safety (RESS), 2015.

Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data. 
Shusen Liu, Bei Wang, Peer-Timo Bremer and Valerio Pascucci.
Computer Graphics Forum (CGF), 33(3), 101-110, 2014

CT Based Computerized Identification and Analysis of Human Airways: A Review. 
Jiantao Pu, Suicheng Gu, Shusen Liu, Shaocheng Zhu, David Wilson, Jill M. Siegfried and David Gur. 
Medical physics, 39(5), 2603-2616, 2012.

Feature-Based Statistical Analysis of Combustion Simulation Data. 
Janine C. Bennett, Vaidyanathan Krishnamoorthy, Shusen Liu, Ray W. Grout, Evatt R. Hawkes, Jacqueline H. Chen, Jason Shepherd, Valerio Pascucci and Peer-Timo Bremer. 
IEEE Transactions on Visualization and Computer Graphics, 17(12), 1822-1831, 2011.

Fast Blood Flow Visualization of High-Resolution Laser Speckle Imaging Data Using Graphics Processing Unit. 
Shusen Liu, Pengcheng Li and Qingming Luo. 
Optics express, 16(19), 14321-14329, 2008.

 

Peer-reviewed Conference Publications:

 

Embedded Domain-Specific Language and Runtime System for Progressive Spatiotemporal Data Analysis and Visualization 
Cameron Christensen, Shusen Liu, Giorgio Scorzelli, Ji-Woo Lee, Peer-Timo Bremer and Valerio Pascucci.
IEEE Symposium on Large Data Analysis and Visualization (LDAV), 2016.

Visualizing High-Dimensional Data: Advances in the Past Decade. 
Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer and Valerio Pascucci.
The Eurographics Conference on Visualization (EuroVis15), State-of-The-Art Reports (STARS), 2015.

Multivariate Volume Visualization through Dynamic Projections. 
Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer and Valerio Pascucci.
IEEE Symposium on Large Data Analysis and Visualization (LDAV), 35-42, 2014.

Analyzing Simulation-Based PRA Data Through Clustering: a BWR Station Blackout Case Study. 
Dan Maljovec, Shusen Liu, Bei Wang, Valerio Pascucci, Peer-Timo Bremer, Diego Mandelli and Curtis Smith.
International Conference on Probabilistic Safety Assessment and Management (PSAM), 2014.

Gaussian Mixture Model Based Volume Visualization. 
Shusen Liu, Joshua A. Levine, Peer-Timo Bremer and Valerio Pascucci.
IEEE Symposium on Large Data Analysis and Visualization (LDAV), 73-77, 2012. (Best Paper Award)