Talks
[24] Paper presentation at 6th International Workshop on In Situ Visualization -- held in conjunction with ISC High Performance, June 2022
Title: In Situ Analysis and Visualization of Extreme-Scale Particle Simulations
[23] Project progress talk at Exascale Computing Project (ECP) Community Birds-of-a-Feather (BOF) Days, May 2022
Title: ALPINE Infrastructure and Algorithms
[22] Lightning paper talk at DOE ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, & Communication, Jan. 2022
Title:Model-based Visual Analytics of Big Data: Challenges and Opportunities
[21] Paper presentation at IEEE International Conference on Big Data (IEEE BigData), December 2021
Title: In Situ Adaptive Spatio-Temporal Data Summarization
[20] Paper presentation at In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization (ISAV), November 2021
Title: In Situ Climate Modeling for Analyzing Extreme Weather Events
[19] Invited talk hosted by the E.C.E. Department of Netaji Subhash Engineering College (NSEC), India, November 2021
Title: Data Exploration at Exascale: Challenges, Solutions, and Opportunities
[18] Lightning talk at JuliaCon, July 2021
Title: In-Situ Data Analysis with Julia for E3SM at Large Scale
[17] Invited as a panel member: NSF Center on Pervasive Personalized Intelligence for IoT Systems Scale-up, June 2021
Title: Opportunities and challenges on using Data Visualization
[16] Invited talk at Los Alamos - Arizona Days Conference, May 2021
Title: Statistical Techniques for Enabling Extreme-scale Data Summarization, Feature Exploration, and Visual Analysis
[15] Invited talk at Information Sciences Group (CCS-3), Los Alamos National Laboratory, May 2021
Title: Statistical and Machine Learning Techniques for Enabling Extreme-scale Data Summarization, Feature Exploration, and Visual Analysis
[14] Early career research talk at U.S. Department of Energy Computer Graphics Forum (DOECGF), April 2021
Title: Extreme-scale Data Reduction, Feature Exploration, and Visual Analysis
[13] U.S. Department of Energy Computer Graphics Forum (DOECGF), April 2021
Title: Facilities and Research Update for Los Alamos National Laboratory
[12] 5th Exascale Computing Project (ECP) Annual Meeting, April 2021
Title: In Situ Scalable Data Reduction and Feature Exploration Algorithms for Exascale Simulations
[11] LDRD: In Situ Inference, Los Alamos National Lab, Project review. December 2020
Title: In Situ Climate Modeling and Analysis
[10] 4th Exascale Computing Project (ECP) Annual Meeting, February 2020
Title: In situ Statistical Feature Detection, Characterization, and Tracking
[9] Tutorial: ACM SIGGRAPH Asia Symposium on Visualization, November 2017
Title: Information Theory in Visualization (Co-delivered a tutorial session on behalf of Prof. Han-Wei Shen)
[8] Paper presentation at ACM SIGGRAPH Asia Symposium on Visualization, November 2017
Title: Pointwise Information Guided Visual Analysis of Time-varying Multi-fields
[7] Applied Computer Science Group (CCS-7), Los Alamos National Laboratory, August 2017
Title: Uncertainty, sensitivity, and error analysis and visualization of high-dimensional Input-output models
[6] Paper presentation at IEEE Pacific Visualization, April 2017
Title: Homogeneity Guided Probabilistic Data Summaries for Analysis and Visualization of Large-Scale Data Sets
[5] Paper presentation at IEEE Visualization, October 2016
Title: In situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations
[4] Applied Computer Science Group (CCS-7), Los Alamos National Laboratory, August 2016
Title: Improved Distribution Guided Data Summarization
[3] Invited talk at Statistical Sciences Group (CCS-6), Los Alamos National Laboratory, July 2016
Title: Distribution driven data analysis and visualization
[2] Paper presentation at IEEE Visualization, October 2015
Title: Distribution Driven Extraction and Tracking of Features for Time-varying Data Analysis
[1] Applied Computer Science Group (CCS-7), Los Alamos National Laboratory, July 2015
Title: A Generalized Framework for Comparing across Data Representations