Center for Visual and Decision Informatics

As the Director of Research, he leads several research initiatives in the broader area of cyber physical systems and big data across three centers within IRI. He is also the Managing Site Director of NSF CVDI – an NSF Industry/University Cooperative Research Center in the area of big data. His research interest is in the broader area of cyber physical systems – specifically addressing real-world informatics and integrated systems modeling issues. He has led various efforts in the area of big data platforms, system resilience, modeling & verification of distributed systems, software defined networks, visual analytics, and evolutionary networks. His research has generated over $7M in funding from various state and federal agencies including NSF, DHS S&T, DOE, state agencies, and the private sector. He has 15 peer-reviewed conference/journal publications, 2 U.S. Patents, and authored several technical reports. He is also part of the US Ignite community leadership group and representative from the city of Lafayette. He has also served on various conference program, and review committees. Most recently he served as the Industry sponsorship chair for the 1st and 2nd IEEE International Conference on Big Data, and is invited to serve as the workshop chair for the IEEE International Conference on Data Mining (ICDM) 2017.

Privacy-aware Stress & Activity Recognition Using Wearables in Hospitals – 9a.008.UL
Visual Analytics of Real-time Hospital Emergency Department Operations: A Human-Centric Approach 8a.006.UL
Fault-Tolerance Strategies for Handling Data-Streams on Edge-Networks: Application to Smart Buildings 7a.001.UL
An Ontology-based Architecture for Providing Insights 6a.025.UL
Data Management Strategy for the Water Institute of the Gulf
Big Data Research for Automated Detection and Recognition of Wildlife
Predicting Future Relations: Incremental and Robust Link Prediction 15.2
Visual Analytic Methods for Dynamic Graphs
Visual Analytic Approaches to Mining Large-scale Time-Evolving Graphs
Real-Time Analysis and Visualization of Multi-dimensional Sensor Data

Advanced Machine Learning for Industrial Application – Partially Supporting Measures Against COVID19 – 9a.009.TAU
Enabling Mobile Visual Analytics 6a.050.UL
A Predictive Analytics Framework for Spatiotemporal Hotspots
A Spatio-Temporal Data Mining Approach for Fraud Detection
Social Media for Decision Informatics with Application to Emerging Events

Ontology-based Fast Semantic Indexing for Structured and Unstructured Data in Health Care 7a.003.UL
Mitigating Concept Drift for Time-varying Domain through Adaptive Learning 6a.022.UL

• Gottumukkala, N. R., R. Nassar, C.B. Leangsuksun, M. Paun. “Reliability of a system of k nodes for high performance computing applications”. IEEE Transactions on Reliability, Volume 59, Issue 1, March 2010, pp. 162 – 169
  
• S. Katz, G. Allen, R. Cortez, C. Cruz-Neira, R. Gottumukkala, Z. D. Greenwood, L. Guice, S. Jha, R. Kolluru, T. Kosar, L. Leger, H. Liu, C. McMahon, J. Nabrzyski, B. Rodriguez-Milla, E. Seidel, G. Speyrer, M. Stubblefield, B. Voss, and S. Whittenburg, “Louisiana: A Model for Advancing Regional e-Research through Cyberinfrastructure,” Philosophical Transactions of the Royal Society A, v. 367, pp. 2459-2469, 2009
  
• Engelmann, C. S. L. Scott, D. E. Bernholdt, N. R. Gottumukkala, C. B. Leangsuksun, J. Varma, C. Wang, F. Mueller, A. G. Shet, P. Sadayappan. “MOLAR: Adaptive Runtime Support for High-End Computing Operating and Runtime Systems, ACM SIGOPS Operating Systems Review” Volume 40, Issue 2, pp. 63-72, 2006
  
• Gottumukkala, R.N., Siva, R., & Venna, V.R. (2015). Visual analytics of time evolving large-scale graphs. The IEEE Intelligent Informatics Bulletin 16(1), 10-16