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Raju Gottumukkala, PhD

 Dr. Raju Gottumukkala is the Director of Research for the Informatics Research Institute at UL Lafayette and the Director of the Accessible Healthcare through AI-Augmented Decisions Center. He is also the AAMA/LEQSF Regents Associate Professor in Mechanical Engineering. He has led several research initiatives in the broader area of cyber-physical systems and big data across multiple centers within IRI. He was also the Site Director of NSF CVDI, an NSF Industry–University Cooperative Research Center in 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 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 has authored several technical reports. He is also part of the US Ignite community leadership group and a representative from Lafayette. He has also served on various conference programs and review committees. Most recently, he served as the industry sponsorship chair for the 1st and 2nd IEEE International Conference on Big Data. He was invited to be the workshop chair for the IEEE International Conference on Data Mining.

Dr. Gottumukkala has led R&D efforts totaling over $100M and has authored over 50 peer-reviewed publications. Some of Dr. Gottumukkala’s notable research efforts include VAStream (www.vastream.net) from NSF, NSF Center for Visual and Decision Informatics, and developing a High-confidence Medical Cyber-physical system research instrument. He has also successfully led stress detection studies using machine learning.

Education

Ph.D. Computational Analysis and Modeling, Louisiana Tech University, 2008
M.S.  Computer Science, Louisiana Tech University,  2003
B.E.  Computer Science and Engineering, University of Madras, 1999

Contact Information:

​Rougeou Hall, Room 223
P.O. Box 43678, Lafayette, LA 70504
Phone:(337) 482-0632
Email: raju@louisiana.edu

LinkedIn: https://www.linkedin.com/in/raju-gottumukkala-a8830419/

Researchgate: https://www.researchgate.net/profile/Raju_Gottumukkala3

Honors and Awards:

  • 2017 “Ralph E. POWE Junior Faculty Enhancement Award”, One of the 36 recipients of national award from Oak Ridge Associated Universities
  • 2017 "Innovative Project of the Year", State of Louisiana’s Clean Fuel Coalition, Baton Rouge, Louisiana. Award presented by LA DEQ Secretary Dr. Chuck Brown
  • 2016 Awarded “Outstanding Achievement in Research & Sponsored Activities” for generating external sponsored projects in the amount of $500,000 or more, University of Louisiana at Lafayette
  • 2017 US Ignite Application that is most likely to have a Big Impact NextGen BEOC: 2016 US Ignite Application Summit, Austin, TX. (with Dr. Michael Dunaway)
  • The project titled “Forecasting Influenza Occurrence to Improve ED Operations” was mentioned as one of the 50 Industry-Nominated Technology Breakthroughs of NSF Industry/University Cooperative Research Centers”

Selected Publications:

  • Venna, S. R., Tavanaei, A., Gottumukkala, R. N., Raghavan, V. V., Maida, A., & Nichols, S. A novel data-driven model for real-time influenza forecasting. IEEE Access Vo. 7, pp. 7691-7701, 2019 [IMPACT FACTOR: 3.4]
  • Cao, G., Iosifidis, A., Gabbouj, M., Raghavan, V., & Gottumukkala, R. (2018). Deep Multi-view Learning to Rank. arXiv preprint arXiv:1801.10402.(under review)
  • 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
  • Raju Gottumukkala, Rizwan Merchant, Andrew Roche, Kaleb Leon, Adam Tauzin, Paul Darby, Cyber-physical System Security of Vehicle Charging Stations, Accepted at the IEEE Greentech Conference, April 3rd to 6th 2019.
  • Jessica Wojkiewicz, Satya Katragadda, Raju Gottumukkala, A Concept-Drift Based Predictive-Analytics Framework: Application for Real-Time Solar Irradiance Forecasting, Poster Paper, 2018 IEEE International Conference on Big Data
  • Satya, Katragadda, Raju Gottumukkala, Murali Pusala, Vijay Raghavan, Jessica Wojkiewicz, Distributed Real Time Link Prediction on Graph Streams, 3rd IEEE Workshop on Real-time and Stream Analytics in Big Data & Stream Data Management, IEEE Big Data 2018.
  • Ahmad, S, SM Zobaed, R. Gottumukkala, and M. Amini. “Edge Computing for User-Centric Secure Search on Big Data in Cloud” Submitted to the 19th Annual IEEE/ACM International Symposium in Cluster, Cloud, and Grid (Under review)
  • Amirhossein Tavanaei, Raju Gottumukkala, Vijay Raghavan, Anthony Maida, Unsupervised Rank Aggregation using Parameterized Function Optimization, 2018 IEEE International Joint Conference on Neural Networks
  • Shailendra Gaikwad, Sana Tafleen, Raju Gottumukkala, Khalid Elgazzar, Fault Tolerance of Real-time Video Streaming Protocols over SDN Networks”, 14th International Wireless Communications & Mobile Computing Conference (IWCMC)
  • Matin Hosseini, Mohsen Amini Salehi, Raju Gottumukkala, “Enabling Interactive Video Stream Prioritization for Public Safety Monitoring through Effective Batch Scheduling”, Accepted in the 19th IEEE International Conference on High Performance Computing and Communications (HPCC ’17), Bangkok, Thailand, Dec. 2017
  • Pusala, M. K., Benton, R. G., Raghavan, V. V., & Gottumukkala, R. N. (2017, November). Supervised approach to rank predicted links using interestingness measures. In Bioinformatics and Biomedicine (BIBM), 2017 IEEE International Conference on (pp. 1085-1092). IEEE.
  • Raju Gottumukkala, John Zachary, Baker Kearfott ,Ramesh Kolluru, “Real-Time Information Driven Decision Support System for Evacuation Planning”, 2012 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support, March 6-8 2012, New Orleans, LA, USA
  • Gottumukkala, N. R., C. Leangsuksun, T. Narate, R. Nassar, S.L. Scott. “Reliability-Aware Resource Allocation in HPC Systems”, Proceedings of the IEEE International Conference on Cluster Computing 2007, Austin, Texas
  • Song, H., Leangsuksun, C, Nassar, R., N. Raju, Gottumukkala, Scott, S., Availability modeling and analysis on high performance cluster computing. In Proceedings of the First International Conference on Systems, Availability, Reliability and Security, 2006
  • Gottumukkala, N. R., T. Sun: “Modeling and Assessment of Production Printing Workflows Using Petri Nets”, International Conference on Business Process Management, pp. 319-333, 2005
  • Hertong Song, Chokchai B. Leangsuksun, N. R Gottumukkala, Raja Nassar, Stephen L. Scott, and Andy Yoo, "Near-Real-time Availability Monitoring and Modeling for HPC/HEC runtime systems'', Los Alamos Computer Science Institute (LACSI) Symposium, 2005
  • N. Raju, Gottumukkala, Y. Liu, C. B. Leangsuksun, R. Nassar, and S. L Scott, Reliability analysis of HPC clusters, Proceedings of the High Availability and Performance Computing Workshop, 2006
  • N. Raju Gottumukkala, Box Leangsuksun, Raja Nassar, Mihaela Paun, Dileep Sule, “Reliability Aware Optimal-K Node allocation of parallel applications in large scale HPC systems”, High Availability and Performance Computing Workshop (HAPCW 2008), Denver, Colorado
  • Haochun Zhang, Raju Gottumukkala, Baker Kearfott, Ramesh Kolluru, “A Multi-Objective Mixed Optimization Model for POD to Distribute Emergency Supplies”, Institute for Operations Research and the Management Sciences (INFORMS) 2010 Conference, November 2010
  • N. Raju Gottumukkala, Fuel Demand Estimation for Hurricane Evacuation in Louisiana: Evacuee Behavior for Gustav, Ike, Katrina & Rita, the 2012 National Evacuation Conference, February 7-9, New Orleans, LA
  • N. Raju Gottumukkala, Ramesh Kolluru, Xiaoduan Sun, Mark Smith, Bob Grambling, Haochun Zhang, “Fuel Demand Estimation for Regional Hurricane Evacuation”, The National Evacuation Conference, Feb 3-5, 2010, New Orleans, LA.
  • N. Raju Gottumukkala, “Improving Disaster Response: NIMSAT”, The 2009 Gulf Coast Marine Conference, Sponsored by the National Oceanic and Atmospheric Administration, the National Weather Service, and National Ocean Service,, LITE Center, Lafayette, LA.
  • N. Raju Gottumukkala, Rusti Liner, “GIS Projects at NIMSAT Institute” The 25th Annual Remote Sensing and GIS Workshop, April 14-16 2009, Baton Rouge, Louisiana
  • N. R. Gottumukkala, C. Leangsuksun, and S. L. Scott. Reliability-aware approach to improve job completion time for large-scale parallel applications. In Proceedings of 2nd Workshop on High Performance Computing Reliability Issues (HPCRI) 2006, Austin, TX, USA, February 11-15, 2006
  • Sun, T., J. Walker, S. Revankar, N. R. Gottumukkala. “Workflow Auto Generation from User Constraints and Hierarchical Dependence Graphs for Workflows”, Awarded US Patent No 7580911
  • Sun, T., N.R. Gottumukkala, M.S. David, “Validation and Analysis of JDF Workflows using Colored Petri Nets”, Patent Application, Xerox Corp No 20060242002