I am a Computer Scientist in the Advanced Computing, Mathematics, and Data Division at the Pacific Northwest National Laboratory. I serve as the acting Group Leader of the Data Sciences & Machine Intelligence Group. My research interests broadly include parallel graph algorithms, scientific computing, and artificial intelligence & machine learning. I hold a joint appointment as Research Associate Professor in the School of Electrical Engineering & Computer Science, Washington State University in Pullman, Washington.

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Externally Funded projects:

Roles: Principal Investigator (PI)/Co-PI/Task Lead/Senior Personnel

• Department of Energy-Advanced Scientific Computing Research (DOE-ASCR): “Decision and Control of Complex Systems: A Data Driven Framework.” (FY’2021 – FY’2023)
  
• Department of Energy-Advanced Scientific Computing Research (DOE-ASCR): Exascale Computing Projects. “ExaGraph: Combinatorial Methods for Enabling Exascale Applications Co-Design Center.” (FY’2017 – FY’2021)
• Department of Energy-Advanced Scientific Computing Research (DOE-ASCR): "Center for ARtificial Intelligence-focused ARchitectures and Algorithms (ARIAA)". (FY’2020 – FY’2022)
• Department of Defense-Strategic Environmental Research and Development Program (SERDP). “NICE: Networked Infrastructures under Compound Extremes” (FY’2021 – FY’2023)
• Department of Energy-Office of Science: National Quantum Information Science Research Center "Quantum Science Center." (FY’2021 – FY’2026)
• Department of Energy-Advanced Research Projects Agency-Energy (DOE-ARPAE): GRID DATA Program. Generating Realistic Information for the Development of Distribution and Transmission Algorithms. “Sustainable Data Evolution Technology for Power Grid Optimization" (FY’2017 – FY’2019)
• DARPA Hierarchical Identify Verify Exploit (HIVE) Program: “Hybrid Attributed Generic Graph Library Environment (HAGGLE).” (FY’17-FY20)
• Department of Defense: “HPDA: High Performance Data Analytics.” (FY’2016 – FY’2017)
• Department of Energy-Advanced Scientific Computing Research (DOE-ASCR). “M2ACS: Multifaceted Mathematics for Complex Energy Systems.” (FY’2012 – FY’2017)
• Department of Energy-Advanced Scientific Computing Research (DOE-ASCR). “IPPD: Integrated End-to-End Performance Prediction and Diagnosis for Extreme Scientific Workflows.” (FY’2015 – FY2018 ---- FY'19-FY'21)
• Department of Defense: “CASS-MT: Center for Adaptive Supercomputing Software-Multithreaded.” (FY’2009 – FY’2015)

Pacific Northwest National Laboratory Laboratory Directed Research and Development Projects:

Roles: Principal Investigator (PI)/Co-PI/Senior Personnel

• LDRD Seed: Exploration of Domain Aware Machine Learning for Grid Analytics (FY’19 – FY’20)
• LDRD Seed: Towards Automated Vulnerability and Mitigation of Critical Infrastructure (FY’18)
• NSD LDRD: Cyber-based Contingency Analysis of Interdependent Infrastructure Networks under Uncertainty (FY’2019 to FY’2020)
• MinT-Net: Novel and Scalable Network-enabled Comparative Tools for Stress Studies of Microbiomes in Transition (FY’2017)
• Rendezvous: Optimization and Stochastic Algorithms for Asymmetric Resilient Infrastructure (FY’2015 to FY’2017)
• Concurrent Design and Control of Complex Systems: Controllability, Observability and Performance Metrics (FY’2017 to FY’2018)
• Resilience in Large-Scale Distributed Control Systems (FY’2015 to FY’2018)
• LDRD Seed: Scaling Multisubject Cortical Parcellation (FY’2016)
• M&Ms4Graphs: A Multi-scale, Multi-Dimensional Graph Analytics Framework for Cyber Security (FY’2013 to FY’2016)
• Shyre: Streaming Hypothesis Reasoning (FY’2014 to FY’2015)
• Theory of Resilience (FY’2014 to FY’2015)
• Future Power Grid Control Paradigm (FY’2012 to FY’2015)
• Linear Algebra Solvers and Associated Matrix-Vector Kernels for Power Grid Simulations (FY’2010 to FY’2015)
• Comparing Performance on Different High-Performance Computing Architectures (FY’2010)

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Awards:

• Best Conference Papers on Power System Modeling and Analysis submitted to the 2018 Power & Energy Society General Meeting. “Synthetic Power Grids from Real World Models.” IEEE Power & Energy Society (PES) General Meeting. August 5 - 9, 2018, Portland, OR
• MIT/Amazon Graph Challenge Champions. "TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure." IEEE High Performance Extreme Computing Conference (HPEC), Virtual, 22-24 Sept. 2020
• DARPA/Amazon Graph Challenge Champions. "Scalable static and dynamic community detection using Grappolo." IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, 2017
• Amazon Graph Challenge Student Innovation Award. "Scalable Community Detection Using Vite." IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, 2018
• Best paper award in the Attack and Disaster track. " Quantitative Assessment of Transportation Network Vulnerability with Dynamic Traffic Simulation Methods." IEEE Conference on Technologies for Homeland Security, Waltham, MA, 25 – 26 April, 2017
• Best paper award. “On Stable Marriages and Greedy Matchings,” Society for Industrial and Applied Mathematics (SIAM) Workshop on Combinatorial Scientific Computing. Albuquerque, New Mexico. 10 – 12 October, 2016
• Best paper award in the Cyber Security track. "Quantifying Mixed Uncertainties in Cyber Attacker Payoffs." IEEE Conference on Technologies for Homeland Security, Waltham, MA, 14 – 16 April, 2015
• Best paper award in the Cyber Security track. "Towards A Theory of Autonomous Reconstitution of Compromised Cyber-Systems." IEEE Conference on Technologies for Homeland Security, Waltham, MA, 12 – 14 Nov, 2013
• Amazon Graph Challenge Innovation Award. “Scaling and Quality of Modularity Optimization Methods for Graph Clustering.” IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, 2019
• Amazon Graph Challenge Innovation Award. “Direction-Optimizing Label Propagation Algorithm.” IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, 2019
• Society for Risk Analysis (SRA) Best Poster Award. “Cyber-Based Interdependent Infrastructure Network Resilience Analysis.” 2019
• Old Dominion University's Office of Graduate Studies University Graduate Fellowships, valued at $20,000 for the 2005-2006 academic year

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Short Bio:

Dr. Halappanavar is a computer scientist at the Pacific Northwest National Laboratory. He serves as the acting Group Leader of the Data Sciences and Machine Intelligence Group, and holds a joint appointment as Research Associate Professor in the School of Electrical Engineering & Computer Science, Washington State University in Pullman, Washington. His research has spanned multiple technical foci and includes combinatorial scientific computing, parallel graph algorithms, machine learning, and 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 85 technical publications for peer-reviewed journals, conferences, and workshops. He is a Senior Member of the Association for Computing Machinery, Senior Member of the Institute of Electrical and Electronics Engineers, and member of the Society for Industrial and Applied Mathematics.

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Erdös number:
My Erdös number is 3: Halappanavar --> Manne --> Hedetniemi --> Erdös

1. Langguth, Johannes; Azad, Ariful; Halappanavar, Mahantesh; Manne, Fredrik. "On Parallel Push-Relabel Algorithms for Bipartite Maximum Matching." Elsevier Journal of Parallel Computing: Systems and Applications. 40, 7 (July 2014), 289 -- 308.
2. Blair, Jean; Goddard, Wayne; Hedetniemi, Sandra M.; Hedetniemi, Stephen T.; Manne, Fredrik; Rall, Douglas. "Emergency response sets in graphs." J. Combin. Math.  and Combin. Comput. 68 (2009), 225 -- 243.
3. Erdös, P.; Hare, W. R.; Hedetniemi, S. T.; Laskar, R. "On the equality of the Grundy and chromatic numbers of a graph." J. Graph Theory 11 (1987), no. 2, 157 -- 159.

Source: American Mathematical Society MathSciNet.

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Genealogy:
Source: Mathematics Genealogy Project