Chief Data Scientist, Data Sciences & Machine Intelligence Group
Chief Data Scientist, Data Sciences & Machine Intelligence Group

Biography

Dr. Halappanavar is a chief data scientist at PNNL, where he serves as the group lead of the Data Science and Machine Intelligence group. He also holds a joint appointment as adjunct faculty in computer science at the School of Electrical Engineering and Computer Science at Washington State University in Pullman. His research has spanned multiple technical foci and includes combinatorial scientific computing, parallel graph algorithms, artificial intelligence and machine learning, and the application of graph theory and game theory to solve problems in application domains, such as scientific computing, power grids, cybersecurity, and life sciences. He co-authored a book on design of parallel graph algorithms on shared-memory architectures and has authored over 90 technical publications for peer-reviewed journals, conferences, and workshops. He is a member of the Society for Industrial and Applied Mathematics (SIAM), and a senior member of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE).

Disciplines and Skills

  • Combinatorial and Graph Algorithms
  • Parallel Computing
  • Artificial Intelligence and Machine Learning
  • Combinatorial Scientific Computing
  • Application Domains such as Computational Biology, Chemistry, and Cybersecurity

Education

  • PhD in Computer Science, Old Dominion University 
  • MS in Computer Science, Old Dominion University 
  • Post Graduate Diploma in Management (Equivalent to MBA), Karnatak Law Society’s Institute of Management Education and Research 
  • BE in Industrial and Production Engineering, Karnatak University                                                                                                            

Affiliations and Professional Service

  • SIAM
  • Senior Member, ACM
  • Senior Member, IEEE

Awards and Recognitions

  • MIT/Amazon Graph Challenge Champions for "TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure," IEEE High Performance Extreme Computing Conference (2020)
  • Amazon Graph Challenge Innovation Award for “Scaling and Quality of Modularity Optimization Methods for Graph Clustering,” IEEE High Performance Extreme Computing Conference (2019)
  • Amazon Graph Challenge Innovation Award for “Direction-Optimizing Label Propagation Algorithm,” IEEE High Performance Extreme Computing Conference (2019)
  • Best Poster Award for “Cyber-Based Interdependent Infrastructure Network Resilience Analysis,” Society for Risk Analysis (2019)
  • Amazon Graph Challenge Student Innovation Award for "Scalable Community Detection Using Vite," IEEE High Performance Extreme Computing Conference (2018)
  • Best Conference Papers Award for “Synthetic Power Grids from Real World Models,” IEEE Power & Energy Society (PES) General Meeting (2018)
  • Best Paper Award in the Attack and Disaster track for “Quantitative Assessment of Transportation Network Vulnerability with Dynamic Traffic Simulation Methods," IEEE Conference on Technologies for Homeland Security (2017)
  • DARPA/Amazon Graph Challenge Champions for "Scalable static and dynamic community detection using Grappolo," IEEE High Performance Extreme Computing Conference (2017)
  • Best Paper Award for “On Stable Marriages and Greedy Matchings,” SIAM Workshop on Combinatorial Scientific Computing (2016)
  • Best Paper Award in the Cyber Security track for "Quantifying Mixed Uncertainties in Cyber Attacker Payoffs," IEEE Conference on Technologies for Homeland Security (2015)
  • Best Paper Award in the Cyber Security track for "Towards A Theory of Autonomous Reconstitution of Compromised Cyber-Systems," IEEE Conference on Technologies for Homeland Security (2013)
  • Old Dominion University's Office of Graduate Studies University Graduate Fellowship (2005 – 2006)

Publications

2023

  • Chen X., M. Minutoli, J. Tian, M. Halappanavar, A. Kalyanaraman, and D. Tao. 2023. "HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures." In Proceedings of the 31st International Conference on Parallel Architectures and Compilation Techniques (PACT 2022), October 8-12, 20 22, Chicago, IL, 412–425. New York, New York: ACM. PNNL-SA-170217.  doi:10.1145/3559009.3569647
  • Du Y., S. Chatterjee, A. Bhattacharya, A. Dutta, and M. Halappanavar. 2023. "Role of Reinforcement Learning for Risk-Based Robust Control of Cyber-Physical Energy Systems." Risk Analysis. PNNL-SA-163685. doi:10.1111/risa.14104

2022

  • Das S., A. Dutta, S. Purohit, E. Serra, M. Halappanavar, and A. Pothen. 2022. "Towards Automatic Mapping of Vulnerabilities to Attack Patterns using Large Language Models." In IEEE International Symposium on Technologies for Homeland Security (HST 2022), November 14-15, 2022, Boston, MA, 1-7. Piscataway, New Jersey: IEEE. PNNL-SA-174298. doi:10.1109/HST56032.2022.10025459
  • Das S., M. Halappanavar, A. Tumeo, E. Serra, A. Pothen, and E. Al-Shaer. 2022. "VWC-BERT: Scaling Vulnerability–Weakness–Exploit Mapping on Modern AI Accelerators." In Proceedings of the IEEE International Conference on Big Data (Big Data 2022), December 17-20, 2022, Osaka, Japan, 1224-1229. Piscataway, New Jersey: IEEE. PNNL-SA-170354. doi:10.1109/BigData55660.2022.10020622
  • Drgona J., S. Mukherjee, A.R. Tuor, M. Halappanavar, and D.L. Vrabie. 2022. "Learning Stochastic Parametric Differentiable Predictive Control Policies." In 10th IFAC Symposium on Robust Control Design (ROCOND 2022), August 30 - September 2, 2022, Kyoto, Japan.  IFAC-PapersOnLine, 55, 121 - 126. Amsterdam: Elsevier. PNNL-SA-170144. doi:10.1016/j.ifacol.2022.09.334
  • Gawande N.A., S. Ghosh, M. Halappanavar, A. Tumeo, and A. Kalyanaraman. 2022. "Towards Scaling Community Detection on Distributed-Memory Heterogeneous Systems." Parallel Computing 111. PNNL-SA-156736. doi:10.1016/j.parco.2022.102898
  • Ghosh S., N.R. Tallent, and M. Halappanavar. 2022. "Characterizing Performance of Graph Neighborhood Communication Patterns." IEEE Transactions on Parallel and Distributed Systems 33, no. 4:915-928. PNNL-SA-152879. doi:10.1109/TPDS.2021.3101425
  • Hussain M., M.H. Khan, A. Azad, S. Chatterjee, R.T. Brigantic, and M. Halappanavar. 2022. "Disruption-Robust Community Detection Using Consensus Clustering in Complex Networks." In IEEE International Symposium on Technologies for Homeland Security (HST 2022), November 14-15, 2022, Virtual, Online, 1-6. Piscataway, New Jersey: IEEE. PNNL-SA-174273.  doi:10.1109/HST56032.2022.10024983
  • Liu X., A. Lumsdaine, M. Halappanavar, K.J. Barker, and A. Gebremedhin. 2022. "Direction-Optimizing Label Propagation Framework for Structure Detection in Graphs: Design, Implementation, and Experimental Analysis." ACM Journal of Experimental Algorithmics 27, no. 2:Art. No. 1.12, pp 1-31. PNNL-SA-163585. doi:10.1145/3564593
  • Mukherjee S., J. Drgona, A.R. Tuor, M. Halappanavar, and D.L. Vrabie. 2022. "Neural Lyapunov Differentiable Predictive Control." In Proceedings of the 61st IEEE Conference on Decision and Control (CDC 2022), December 6-9, 2022, Cancun, Mexico, 2097-2104. Piscataway, New Jersey: IEEE. PNNL-SA-171659. doi:10.1109/CDC51059.2022.9992386
  • Panchal K., S. Das, L.F. De La Torre Quintana, J.H. Miller, R.J. Rallo Moya, and M. Halappanavar. 2022. "Efficient Clustering of Software Vulnerabilities using Self Organizing Map (SOM)." In IEEE International Symposium on Technologies for Homeland Security (HST 2022), November 14-15, 2022, Virtual, Online, 1-7. Piscataway, New Jersey:IEEE. PNNL-SA-174297. doi:10.1109/HST56032.2022.10025443
  • Sambaturu P., M. Minutoli, M. Halappanavar, A. Kalyanaraman, and A. Vullikanti. 2022. "Scalable and Memory-Efficient Algorithms for Controlling Networked Epidemic Processes Using Multiplicative Weights Update Method." In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022),  July 23-29, 2022, Vienna, Austria, 5164-5170. PNNL-SA-174461. doi:10.24963/ijcai.2022/717
  • Shaw Cortez W.E., J. Drgona, A.R. Tuor, M. Halappanavar, and D.L. Vrabie. 2022. "Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach." In Proceedings of the 61th IEEE Conference on Decision and Control (CDC 2022), December 6-9, 2022, Cancun, Mexico, 932-938. Piscataway, New Jersey: IEEE. PNNL-SA-171767. doi:10.1109/CDC51059.2022.9993146

2021

  • Bhuiyan T.H., H. Medal, A.K. Nandi, and M. Halappanavar. 2021. "Risk-Averse Bi-Level Stochastic Network Interdiction Model for Cyber-Security Risk Management." International Journal of Critical Infrastructure Protection 32. PNNL-SA-158981. doi:10.1016/j.ijcip.2021.100408
  • Gawande N.A., S. Ghosh, M. Halappanavar, M.H. Khan, A. Kalyanaraman, M. Minutoli, and N.R. Tallent, et al. 2021. "ExaGraph: Graph and Combinatorial Methods for Enabling Exascale Applications." International Journal of High Performance Computing Applications 35, no. 6:109434E. PNNL-SA-155863. doi:10.1177/10943420211029299
  • Ghosh S., N.R. Tallent, M. Minutoli, M. Halappanavar, R. Peri, and A. Kalyanaraman. 2021. "Single-node Partitioned-Memory for Huge Graph Analytics: Cost and Performance Trade-offs." In Proceedings of the International Conference for High Performance Computing, Network, Storage and Analysis (SC 2021), November 14-19, 2021, Virtual, Online, Art. No. 55. New York, New York: Association for Computing Machinery. PNNL-SA-161359. doi:10.1145/3458817.3476156
  • Jain M., K. Gupta, A. Visweswara Sathanur, V. Chandan, and M. Halappanavar. 2021. "Transfer-Learnt Energy Models for Predicting Electricity Consumption in Buildings with Limited and Sparse Field Data." In American Control Conference (ACC 2021), May 25-28, 2021, New Orleans, LA, 2887-2894. Piscataway, New Jersey: IEEE. PNNL-SA-156692. doi:10.23919/ACC50511.2021.9483228
  • Silva S.J., S.M. Burrows, M. Evans, and M. Halappanavar. 2021. "A Graph Theoretical Intercomparison of Atmospheric Chemical Mechanisms." Geophysical Research Letters 48, no. 1:Article No. e2020GL090481. PNNL-SA-155287. doi:10.1029/2020GL090481
  • Xiang L., M.H. Khan, E. Serra, M. Halappanavar, and A. Sukumaran-Rajan. 2021. "cuTS: Scaling Subgraph Isomorphism on Distributed Multi-GPUSystems Using Trie Based Data Structure." In Proceedings of the International Conference for High Performance Computing, Network, Storage and Analysis (SC 2021), November 14-19, 2021, Virtual, Online, Art. No. 69. New York, New York: Association for Computing Machinery. PNNL-SA-163660. doi:10.1145/3458817.3476214

2020

  • Alexander F.J., A. Almgren, J. Bell, A. Bhattacharjee, J.H. Chen, P. Colella, and D. Daniel, et al. 2020. "Exascale applications: skin in the game." Philosophical Transactions of the Royal Society A. Mathematical, Physical & Engineering Sciences 378, no. 2166:Article No. 20190056. PNNL-SA-150649. doi:10.1098/rsta.2019.0056
  • Barik R., M. Minutoli, M. Halappanavar, N.R. Tallent, and A. Kalyanaraman. 2020. "Vertex Reordering for Real-world Graphs and Applications: An Empirical Evaluation." In IEEE International Symposium on Workload Characterization (IISWC 2020), October 27-30, 2020, Beijing, China, 240-251. Piscataway, New Jersey: IEEE. PNNL-SA-154319. doi:10.1109/IISWC50251.2020.00031
  • Halappanavar M., and S. Ghosh. 2020. "TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure." In IEEE High Performance Extreme Computing Conference (HPEC 2020), September 22-24, 2020, Waltham, MA, 1-6. Piscataway, New Jersey:IEEE. PNNL-SA-154840. doi:10.1109/HPEC43674.2020.9286167
  • Liu X., M. Halappanavar, K.J. Barker, A. Lumsdaine, and A. Gebremedhin. 2020. "Direction-optimizing Label Propagation and its Application for Community Detection." In Proceedings of the 17th ACM International Conference on Computing Frontiers (CF 2020), June 1-10, 2020. Catania, Italy, 192-201. New York, New York: ACM. PNNL-SA-152667. doi:10.1145/3387902.3392634

2019

  • Aksoy S.G., E. Purvine, E. Cotilla Sanchez, and M. Halappanavar. 2019. "A generative graph model for electrical infrastructure networks." Journal of Complex Networks 7, no. 1:128-162. PNNL-SA-136381. doi:10.1093/comnet/cny016
  • Aksoy S.G., E. Purvine, E. Cotilla Sanchez, and M. Halappanavar. 2019. "A generative graph model for electrical infrastructure networks." Journal of Complex Networks 7, no. 1:Pages 128-162. PNNL-SA-130657. doi:10.1093/comnet/cny016
  • Dobrian F., M. Halappanavar, A. Pothen, and A. AL-Herz. 2019. "A 2/3- Approximation Algorithm for Vertex Weighted Matching in Bipartite Graphs." SIAM Journal on Scientific Computing 41, no. 1:A566-A591. PNNL-SA-142834. doi:10.1137/17M1140029
  • Ghosh S., M. Halappanavar, A. Kalyanaraman, M.H. Khan, and A. Gebremedhin. 2019. "Exploring MPI Communication Models for Graph Applications Using Graph Matching as a Case Study." In IEEE 33rd International Parallel & Distributed Processing Symposium (IPDPS 2019), May 20-24, 2019, Rio de Janeiro, Brazil, 761-779. Los Alamitos, California: IEEE Computer Society. PNNL-SA-138882. doi:10.1109/IPDPS.2019.00085
  • Ghosh S., M. Halappanavar, A. Tumeo, A. Kalyanaraman, and A. Gebremedhin. 2019. "miniVite: A Graph Analytics Benchmarking Tool for Massively Parallel Systems." In IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS 2018), November 12, 2018, Dallas, TX, 51-56. Piscataway, New Jersey: IEEE. PNNL-SA-138790. doi:10.1109/PMBS.2018.8641631
  • Ghosh S., M. Halappanavar, A. Tumeo, and A. Kalyanaraman. 2019. "Scaling and Quality of Modularity Optimization Methods for Graph Clustering." In IEEE High Performance Extreme Computing Conference (HPEC 2019), September 24-26, 2019, Waltham, MA. Piscataway, New Jersey:IEEE. PNNL-SA-145324. doi:10.1109/HPEC.2019.8916299
  • Khan M.H., M. Halappanavar, T.J. Hagge, K. Kowalski, A. Pothen, and S. Krishnamoorthy. 2019. "Mapping Arbitrarily Sparse Two-body Interactions on One-dimensional Quantum Circuits." In IEEE 26th International Conference on High Performance Computing, Data, and Analytics (HiPC 2019), December 17-20, Hyderabad, India, 52-62. Los Alamitos, California: IEEE Computer Society. PNNL-SA-144919. doi:10.1109/HiPC.2019.00018
  • Liu X., J.S. Firoz, M.J. Zalewski, M. Halappanavar, K.J. Barker, A. Lumsdaine, and A. Gebremedhin. 2019. "Distributed Direction-Optimizing Label Propagation for Community Detection." In IEEE High Performance Extreme Computing Conference (HPEC 2019), September 24-26, 2019, Waltham, MA. Piscataway, New Jersey: IEEE. PNNL-SA-146972. doi:10.1109/HPEC.2019.8916215
  • Minutoli M., M. Halappanavar, A. Kalyanaraman, A. Visweswara Sathanur, R.S. McClure, and J.E. McDermott. 2019. "Fast and Scalable Implementations of Influence Maximization Algorithms." In IEEE International Conference on Cluster Computing (CLUSTER 2019), September 23-26, 2019, Albuquerque, NM. Piscataway, New Jersey: IEEE. PNNL-SA-141177. doi:10.1109/CLUSTER.2019.8890991
  • Visweswara Sathanur A., B. Sripimonwan, M. Halappanavar, S. Chatterjee, A. Ganguly, and K. Clark. 2019. "Identification of Critical Airports from the Perspective of Delay and Disruption Propagation in Air Travel Networks." In IEEE International Symposium on Technologies for Homeland Security (HST 2019), November 5-6, 2019, Woburn, MA, 1-6. Piscataway, New Jersey: IEEE. PNNL-SA-147072. doi:10.1109/HST47167.2019.9032999

2018

  • Bakker C., M. Halappanavar, and A. Visweswara Sathanur. 2018. "Dynamic Graphs, Community Detection, and Riemannian Geometry." Applied Network Science 3, no. 1:Article No. 3. PNNL-SA-129998. doi:10.1007/s41109-018-0059-2
  • Bhatia U., S. Chatterjee, A.R. Ganguly, J. Gao, M. Halappanavar, M.R. Oster, and K. Clark, et al. 2018. "Aviation Transportation, Cyber Threats, and Network-of-Networks: Modeling Perspectives for Translating Theory to Practice." In IEEE International Symposium on Technologies for Homeland Security (HST 2018), October 23-24, 2018, Woburn, MA, 1-7. Piscataway, New Jersey: IEEE. PNNL-SA-134574. doi:10.1109/THS.2018.8574123
  • Bhuiyan T.H., M. Halappanavar, R.D. Friese, H. Medal, L. De La Torre, A. Visweswara Sathanur, and N.R. Tallent. 2018. "Stochastic Programming Approach for Resource Selection under Demand Uncertainty." In 22nd International Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP 2018), May 25, 2018, Vancouver, BC, Lecture Notes in Computer Science, edited by D Klusacek, W Cirne, and N Desai, 11332, 107 - 126. Cham: Springer. PNNL-SA-130071. doi:10.1007/978-3-030-10632-4_6
  • Duan Q., E. Al-Shaer, S. Chatterjee, M. Halappanavar, and C.S. Oehmen. 2018. "Proactive Routing Mutation Against Stealthy Distributed Denial of Service Attacks - Metrics, Modeling and Analysis." Journal of Defense Modeling and Simulation 15, no. 2:219-230. PNNL-SA-128859. doi:10.1177/1548512917731002
  • Ghosh S., M. Halappanavar, A. Tumeo, A. Kalyanaraman, and A. Gebremedhin. 2018. "Scalable Distributed Memory Community Detection Using Vite." In IEEE High Performance Extreme Computing Conference (HPEC 2018), September 25-27, 2018, Waltham, MA, 1-7. Piscataway, New Jersey: IEEE. PNNL-SA-136309. doi:10.1109/HPEC.2018.8547534
  • Ghosh S., M. Halappanavar, A. Tumeo, A. Kalyanaraman, H. Lu, D.G. Chavarria-Miranda, and M.H. Khan, et al. 2018. "Distributed Louvain Algorithm for Graph Community Detection." In IEEE International Parallel & Distributed Processing Symposium (IPDPS 2018), May 21-25, 2018, Vancouver, BC, 885-895. Los Alamitos, California: IEEE Computer Society. PNNL-SA-130211. doi:10.1109/IPDPS.2018.00098
  • Visweswara Sathanur A., M. Halappanavar, Y. Shi, and Y. Sagduyu. 2018. "Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks." In Social Network Based Big Data Analysis and Applications. Lecture Notes in Social Networks, edited by M Kaya, et al. 123-142. Cham: Springer International Publishing AG. PNNL-SA-122958. doi:10.1007/978-3-319-78196-9_6
  • Young S.J., Y.V. Makarov, R. Diao, M. Halappanavar, M.R. Vallem, R. Fan, and R. Huang, et al. 2018. "Topological Power Grid Statistics from a Network-of-Networks Perspective." In IEEE Power & Energy Society General Meeting (PESGM 2018), August 5-10, 2018, Portland, OR. Piscataway, New Jersey: IEEE. PNNL-SA-130492. doi:10.1109/PESGM.2018.8586475
  • Young S.J., Y.V. Makarov, R. Diao, R. Fan, R. Huang, J.G. O'Brien, and M. Halappanavar, et al. 2018. "Synthetic Power Grids from Real World Models." In IEEE Power & Energy Society General Meeting (PESGM 2018), August 5-10, 2018, Portland, OR. Piscataway, New Jersey: IEEE. PNNL-SA-130491. doi:10.1109/PESGM.2018.8585792

2017

  • Halappanavar M., H. Lu, A. Kalyanaraman, and A. Tumeo. 2017. "Scalable Static and Dynamic Community Detection Using Grappolo." In IEEE High Performance Extreme Computing Conference (HPEC 2017), September 12-14, 2017, Waltham, Massachusetts, 1-6. Piscataway, New Jersey: IEEE. PNNL-SA-128510. doi:10.1109/HPEC.2017.8091047
  • Lu H., M. Halappanavar, D. Chavarria-Miranda, A. Gebremedhin, A.R. Panyala, and A. Kalyanaraman. 2017. "Algorithms for Balanced Graph Colorings with Applications in Parallel Computing." IEEE Transactions on Parallel and Distributed Systems 28, no. 5:1240-1256. PNNL-SA-114188. doi:10.1109/TPDS.2016.2620142
  • Naim M., F. Manne, M. Halappanavar, and A. Tumeo. 2017. "Community Detection on the GPU." In IEEE International Parallel and Distributed Processing Symposium (IPDPS 2017), May 29-June 2, 2017, Orlando, Florida, 625 - 634. Piscataway, New Jersey: IEEE. PNNL-SA-123598. doi:10.1109/IPDPS.2017.16
  • Panyala A.R., D.G. Chavarria, J.B. Manzano Franco, A. Tumeo, and M. Halappanavar. 2017. "Exploring Performance and Energy Tradeoffs for Irregular Applications: A Case Study on the Tilera Many-core Architecture." Journal of Parallel and Distributed Computing 104. PNNL-SA-118976. doi:10.1016/j.jpdc.2016.06.006
  • Panyala A.R., O. Subasi, M. Halappanavar, A. Kalyanaraman, D.G. Chavarria Miranda, and S. Krishnamoorthy. 2017. "Approximate Computing Techniques for Iterative Graph Algorithms." In IEEE 24th International Conference on High Performance Computing (HiPC 2017), December 18-21, 2017, Jaipur, India, 23 - 30. Los Alamitos, California: IEEE Computer Society. PNNL-SA-129904. doi:10.1109/HiPC.2017.00013
  • Purvine E., E. Cotilla Sanchez, M. Halappanavar, Z. Huang, G. Lin, S. Lu, and S. Wang. 2017. "Comparative Study of Clustering Techniques for Real-Time Dynamic Model Reduction." Statistical Analysis and Data Mining 10, no. 5:263-276. PNNL-SA-112433. doi:10.1002/sam.11352
  • Schram M., V. Bansal, R.D. Friese, N.R. Tallent, J. Yin, K.J. Barker, and E.G. Stephan, et al. 2017. "Integrating prediction, provenance, and optimization into high energy workflows." Journal of Physics: Conference Series 898, no. 6:Article No. 062052. PNNL-SA-129007. doi:10.1088/1742-6596/898/6/062052
  • Shekar V., L. Fiondella, S. Chatterjee, and M. Halappanavar. 2017. "Quantifying Economic and Environmental Impacts of Transportation Network Disruptions with Dynamic Traffic Simulation." In IEEE International Symposium on Technologies for Homeland Security (HST 2017), April 25-26, 2017, Waltham, MA, 1-4. Piscataway, New Jersey: IEEE. PNNL-SA-124020. doi:10.1109/THS.2017.7943472
  • Shekar V., L. Fiondella, S. Chatterjee, and M. Halappanavar. 2017. "Quantitative Assessment of Transportation Network Vulnerability with Dynamic Traffic Simulation Methods." In IEEE International Symposium on Technologies for Homeland Security (HST 2017), April 25-26, 2017, Waltham, MA, 1-7. Piscataway, New Jersey: IEEE. PNNL-SA-124025. doi:10.1109/THS.2017.7943454
  • Tipireddy R., S. Chatterjee, P.R. Paulson, M.R. Oster, and M. Halappanavar. 2017. "Agent-Centric Approach for Cybersecurity Decision-Support with Partial Observability." In IEEE International Symposium on Technologies for Homeland Security (HST 2017), April 25-26, 2017, Waltham, MA, 1-6. Piscataway, New Jersey: IEEE. PNNL-SA-122071. doi:10.1109/THS.2017.7943478
  • Yeung Y., A. Pothen, M. Halappanavar, and Z. Huang. 2017. "AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids." SIAM Journal on Scientific Computing 39, no. 5:S809 -- S827. PNNL-SA-119762. doi:10.1137/16M1082755

2016

  • Bhuiyan T.H., A. Nandi, H. Medal, and M. Halappanavar. 2016. "Minimizing Expected Maximum Risk from Cyber-Attacks with Probabilistic Attack Success." In IEEE International Symposium onTechnologies for Homeland Security (HST 2016), May 10-11, 2016, Waltham, MA. Piscataway, New Jersey: IEEE. PNNL-SA-116665. doi:10.1109/THS.2016.7568892
  • Chatterjee S., M. Halappanavar, R. Tipireddy, and M.R. Oster. 2016. "Game Theory and Uncertainty Quantification for Cyber Defense Applications." SIAM News 49, no. 6:1-5. PNNL-SA-119091.
  • Chatterjee S., R. Tipireddy, M.R. Oster, and M. Halappanavar. 2016. "Propagating Mixed Uncertainties in Cyber Attacker Payoffs: Exploration of Two-Phase Monte Carlo Sampling and Probability Bounds Analysis." In IEEE Symposium on Technologies for Homeland Security (HST 2016), May 10-11, 2016, Waltham, MA. Piscataway, New Jersey: IEEE. PNNL-SA-120091. doi:10.1109/THS.2016.7568967
  • Halappanavar M., A.V. Sathanur, and A. Nandi. 2016. "Accelerating the Mining of Influential Nodes in Complex Networks through Community Detection." In ACM International Conference on Computing Frontiers (CF 2016), May 16-18, 2016, Como, Italy, 64-71. New York, New York: Association for Computing Machinery. PNNL-SA-115824. doi:10.1145/2903150.2903181
  • Kalyanaraman A., M. Halappanavar, D. Chavarria-Miranda, H. Lu, K. Duraisamy, and P.P. Pande. 2016. "Fast Uncovering of Graph Communities on a Chip: Toward Scalable Community Detection on Multicore and Manycore Platforms." Foundations and Trends in Electronic Design Automation 10, no. 3:145-247. PNNL-SA-113556. doi:10.1561/1000000044
  • Khan A., A. Pothen, M.A. Patwary, N.R. Satish, N. Sundaram, F. Manne, and M. Halappanavar, et al. 2016. "EFFICIENT APPROXIMATION ALGORITHMS FOR WEIGHTED B-MATCHING." SIAM Journal on Scientific Computing 38, no. 5:S593-S619. PNNL-SA-116676. doi:10.1137/15M1026304
  • Manne F., M. Naim, H. Lerring, and M. Halappanavar. 2016. "On Stable Marriages and Greedy Matchings." In Proceedings of the Seventh SIAM Workshop on Combinatorial Scientific Computing, October 10-12, 2016, Albuquerque, New Mexico, edited by AH Gebremedhin, EG Boman and B Ucar, 92-101. Philadelphia, Pennsylvania: SIAM. PNNL-SA-119688. doi:10.1137/1.9781611974690.ch10
  • Rauf U., F. Gillani, E. Al-Shaer, M. Halappanavar, S. Chatterjee, and C.S. Oehmen. 2016. "Formal Approach For Resilient Reachability based on End-System Route Agility." In Third ACM Workshop on Moving Target Defense (MTD 2016), October 24-28, 2016, Vienna, Austria, 117-127. New York, New York: ACM. PNNL-SA-121212. doi:10.1145/2995272.2995275
  • Saha S., A.K. Vullinati, M. Halappanavar, and S. Chatterjee. 2016. "Identifying Vulnerabilities and Hardening Attack Graphs for Networked Systems." In IEEE Symposium on Technologies for Homeland Security (HST 2016), May 10-11, 2016, Waltham, MA. Piscataway, New Jersey: IEEE. PNNL-SA-116666. doi:10.1109/THS.2016.7568884

2015

  • Bhowmick S., T. Chen, and M. Halappanavar. 2015. "A new augmentation based algorithm for extracting maximal chordal subgraphs." Journal of Parallel and Distributed Computing 76. PNNL-SA-106337. doi:10.1016/j.jpdc.2014.10.006
  • Chatterjee S., M. Halappanavar, R. Tipireddy, M.R. Oster, and S. Saha. 2015. "Quantifying Mixed Uncertainties in Cyber Attacker Payoffs." In IEEE International Symposium on Technologies for Homeland Security (HST 2015), April 14-16, 2015, Waltham, Massachusetts, 1-6. Piscataway, New Jersey: IEEE. PNNL-SA-106540. doi:10.1109/THS.2015.7225287
  • Chatterjee S., R. Tipireddy, M.R. Oster, and M. Halappanavar. 2015. "A Probabilistic Framework for Quantifying Mixed Uncertainties in Cyber Attacker Payoffs." National Cybersecurity Institute Journal 2, no. 3:13-24. PNNL-SA-114140.
  • Chavarria-Miranda D., A.R. Panyala, M. Halappanavar, J.B. Manzano Franco, and A. Tumeo. 2015. "Optimizing Irregular Applications for Energy and Performance on the Tilera Many-core Architecture." In Proceedings of the 12th ACM International Conference on Computing Frontiers (CF 2015), May 18-21, 2015, Ischia, Italy, Article No. 12. New York, New York: ACM. PNNL-SA-108596. doi:10.1145/2742854.2742865
  • Chavarria-Miranda D., M. Halappanavar, S. Krishnamoorthy, J.B. Manzano Franco, A. Vishnu, and A. Hoisie. 2015. "On the Impact of Execution Models: A Case Study in Computational Chemistry." In Joint International Workshop on High-level Parallel Programming Models and Supportive Environments (HIPS) and Large-Scale Parallel Processing (LSPP), held in conjunction with the 29th IEEE International Parallel & Distributed Processing Symposium Workshop (IPDPSW 2015), May 25-29, 2015, Hyderabad, India, 255-264. Piscataway, New Jersey: IEEE. PNNL-SA-108382. doi:10.1109/IPDPSW.2015.111
  • Halappanavar M., A. Pothen, M. Azad, F. Manne, J. Langguth, and A. Khan. 2015. "Codesign Lessons Learned from Implementing Graph Matching on Multithreaded Architectures." Computer 48, no. 8:46-55. PNNL-SA-110586. doi:10.1109/MC.2015.215
  • Lu H., M. Halappanavar, and A. Kalyanaraman. 2015. "Parallel Heuristics for Scalable Community Detection." Parallel Computing 47. PNNL-SA-108735. doi:10.1016/j.parco.2015.03.003
  • Lu H., M. Halappanavar, D. Chavarria-Miranda, A. Gebremedhin, and A. Kalyanaraman. 2015. "Balanced Coloring for Parallel Computing Applications." In 29th IEEE International Parallel & Distributed Processing Symposium, May 25-29, 2015, Hyderabad, India, 7-16. Los Alamitos, California: IEEE Computer Society. PNNL-SA-108594. doi:10.1109/IPDPS.2015.113
  • Naim M., F. Manne, M. Halappanavar, A. Tumeo, and J. Langguth. 2015. "Optimizing Approximate Weighted Matching on Nvidia Kepler K40." In IEEE 22nd International Conference on High Performance Computing (HiPC 2015), December 16-19, 2015, Bangalore, India, 105-114. Los Alamitos, California: IEEE Computer Society. PNNL-SA-113350. doi:10.1109/HiPC.2015.15

2014

  • Chavarria-Miranda D., M. Halappanavar, and A. Kalyanaraman. 2014. "Scaling Graph Community Detection on the Tilera Many-core Architecture." In 21st International Conference on High Performance Computing (HiPC 2014), December 17-20, 2014, Dona Paula, India. Piscataway, New Jersey: IEEE. PNNL-SA-103170. doi:10.1109/HiPC.2014.7116708
  • Langguth J., M. Azad, M. Halappanavar, and F. Manne. 2014. "On Parallel Push-Relabel based Algorithms for Bipartite Maximum Matching." Parallel Computing 40, no. 7:289 - 308. PNNL-SA-91913. doi:10.1016/j.parco.2014.03.004
  • Lu H., A. Kalyanaraman, M. Halappanavar, and S. Choudhury. 2014. "Parallel Heuristics for Scalable Community Detection." In 28th IEEE International Parallel & Distributed Processing Symposium Workshops (IPDPS 2014), May 19-23, 2014, Phoenix, Arizona, 1374-1385. Los Alamitos, California: IEEE Computer Society. PNNL-SA-99348.
  • Manne F., and M. Halappanavar. 2014. "New Effective Multithreaded Matching Algorithms." In 28th IEEE International Parallel & Distributed Processing Symposium, May 19-23, 2014, Phoenix, Arizona, 519-528. Piscataway, New Jersey: IEEE. PNNL-SA-99347. doi:10.1109/IPDPS.2014.61

2013

  • Ali N., S. Krishnamoorthy, M. Halappanavar, and J.A. Daily. 2013. "Multi-fault Tolerance for Cartesian Data Distributions." International Journal of Parallel Programming 41, no. 3:469-493. PNNL-SA-87233. doi:10.1007/s10766-012-0218-5
  • Halappanavar M., S. Choudhury, E.A. Hogan, P.S. Hui, J.R. Johnson, I. Ray, and L.B. Holder. 2013. "Towards A Network-of-Networks Framework for Cyber Security." In IEEE Intelligence and Security Informatics, June 4-7, 2013, Seattle, Washington, 106-108. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. PNNL-SA-94257. doi:10.1109/ISI.2013.6578796
  • Hogan E.A., J.E. Cotilla Sanchez, M. Halappanavar, S. Wang, P.S. Mackey, P. Hines, and Z. Huang. 2013. "Towards Effective Clustering Techniques for the Analysis of Electric Power Grids." In HiPCNA-PG: Proceedings of the 3rd International Workshop on High Performance Computing, Networking and Analytics for the Power Grid, November 17-21, 2013, Denver Colorado, Article No. 1. New York, New York: ACM. PNNL-SA-98979. doi:10.1145/2536780.2536785
  • Hogan E.A., J.R. Johnson, and M. Halappanavar. 2013. "Graph Coarsening for Path Finding in Cybersecurity Graphs." In Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop (CSIIRW 2013), January 8-10, 2013, Oak Ridge, Tennessee, edited by F Sheldon, et al, Paper No. 7. New York, New York: ACM. PNNL-SA-90064. doi:10.1145/2459976.2459984
  • Hogan E.A., J.R. Johnson, M. Halappanavar, and C. Lo. 2013. "Graph Analytics for Signature Discovery." In IEEE International Conference on Intelligence and Security Informatics (ISI 2013), June 4-7, 2013, Seattle, Washington, 315-320. Piscataway, New Jersey: IEEE. PNNL-SA-94756. doi:10.1109/ISI.2013.6578850
  • Hogan E.A., P.S. Hui, S. Choudhury, M. Halappanavar, K.J. Oler, and C.A. Joslyn. 2013. "Towards a Multiscale Approach to Cybersecurity Modeling." In IEEE International Conference on Technologies for Homeland Security (HST 2013), November 12-14, 2013, Waltham, MA, 80-85. Piscataway, New Jersey: IEEE. PNNL-SA-96793. doi:10.1109/THS.2013.6698980
  • Ramuhalli P., M. Halappanavar, J.B. Coble, and M. Dixit. 2013. "Towards A Theory of Autonomous Reconstitution of Compromised Cyber-Systems." In IEEE International Conference on Technologies for Homeland Security (HST 2013), November 12-14, 2013, Waltham, MA, 577-583. Piscataway, New Jersey: IEEE. PNNL-SA-96745. doi:10.1109/THS.2013.6699067

2012

  • Azad M., M. Halappanavar, S. Rajamanickam, E.G. Boman, A. Khan, and A. Pothen. 2012. "Multithreaded Algorithms for Maximum Matching in Bipartite Graphs." In IEEE 26th International Parallel & Distributed Processing Symposium (IPDPS 2012), May 12-25, 2012, Shanghai, China, 860-872. Los Alamitos, California: IEEE Computer Society. PNNL-SA-83617. doi:10.1109/IPDPS.2012.82
  • Catalyurek U.V., J.T. Feo, A.H. Gebremedhin, M. Halappanavar, and A. Pothen. 2012. "Multithreaded Algorithms for Graph Coloring." Parallel Computing 38, no. 10-11:576-594. PNNL-SA-77886. doi:10.1016/j.parco.2012.07.001
  • Halappanavar M., J.T. Feo, K. Dempsey, H. Ali, and S. Bhowmick. 2012. "A Novel Multithreaded Algorithm For Extracting Maximal Chordal Subgraphs." In 41st International Conference on Parallel Processing (ICPP), September 10-13, 2012, Pittsburgh, Pennsylvania, 58-67. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. PNNL-SA-85602. doi:10.1109/ICPP.2012.10
  • Halappanavar M., J.T. Feo, O. Villa, A. Tumeo, and A. Pothen. 2012. "Approximate Weighted Matching On Emerging Manycore and Multithreaded Architectures." International Journal of High Performance Computing Applications 26, no. 4:413-430. PNNL-SA-78710. doi:10.1177/1094342012452893
  • Halappanavar M., Y. Chen, R.D. Adolf, D.J. Haglin, Z. Huang, and M.J. Rice. 2012. "Towards Efficient N - x Contingency Selection Using Group Betweenness Centrality." In SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC 2012), November 10-16, 2012, Salt Lake City, UT, 273 - 282. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. PNNL-SA-90395. doi:10.1109/SC.Companion.2012.45
  • Khan A., D.F. Gleich, A. Pothen, and M. Halappanavar. 2012. "A Multithreaded Algorithm for Network Alignment Via Approximate Matching." In International Conference for High Performance Computing, Networking, Storage and Analysis (SC), November 10-16, 2012, Salt Lake City, Utah. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. PNNL-SA-87964. doi:10.1109/SC.2012.8
  • Scherrer C., A. Tewari, M. Halappanavar, and D.J. Haglin. 2012. "Feature Clustering for Accelerating Parallel Coordinate Descent." In Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems (NIPS 2012), December 3-6, 2012, Lake Tahoe, Nevada, edited by P. Bartlett, et al, 28-36. La Jolla, California: Neural Information Processing Systems Foundation. PNNL-SA-88340.
  • Scherrer C., M. Halappanavar, A. Tewari, and D.J. Haglin. 2012. "Scaling Up Coordinate Descent Algorithms for Large l1 Regularization Problems." In Proceedings of the 29th International Conference on Machine Learning (ICML 2012), June 26, 2012, Edinburgh, Scotland, edited by J Langford and J Pineau. Madison, Wisconsin: International Machine Learning Society. PNNL-SA-87037.

2011

  • Adolf R.D., D.J. Haglin, M. Halappanavar, Y. Chen, and Z. Huang. 2011. "Techniques for Improving Filters in Power Grid Contingency Analysis." In Proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition (MLDM), August 30-September 3, 2011, New York. Lecture Notes in Computer Science, edited by P Perner, 6871, 599-611. Berlin: Springer-Verlag. PNNL-SA-77563. doi:10.1007/978-3-642-23199-5_44
  • Ali N., S. Krishnamoorthy, M. Halappanavar, and J.A. Daily. 2011. "Tolerating Correlated Failures for Generalized Cartesian Distributions via Bipartite Matching." In Proceedings of the 8th ACM International Conference on Computing Frontiers (CF 2011), May 3-5, 2011, Ischia, Italy. New York, New York: Association for Computing Machinery. PNNL-SA-76095. doi:10.1145/2016604.2016649
  • Catalyurek U., F. Dobrian, A.H. Gebremedhin, M. Halappanavar, and A. Pothen. 2011. "Distributed-memory Parallel Algorithms for Matching and Coloring." In IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW 2011), May 16-20, 2011 Anchorage, Alaska, 1971-1980. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. PNNL-SA-77038. doi:10.1109/IPDPS.2011.360