Sanjukta Bhowmick

Previous Scheduled Teaching

Published Intellectual Contributions

Book Chapter

• Sarkar, S., Kumar, S., Bhowmick, S., Mukherjee, A. (2018). Centrality and Community Scoring Functions in Incomplete Networks: Their Sensitivity, Robustness, and Reliability. Machine Learning Techniques for Online Social Networks. 135--154. Springer, Cham.
• Bhowmick, S., Srinivasan, S. (2013). A template for parallelizing the louvain method for modularity maximization. Dynamics On and Of Complex Networks, Volume 2. 111--124. Birkh\"auser, New York, NY.
• Chatterjee, A., Bhowmick, S., Raghavan, P. (2013). Improving Classifications Through Graph Embeddings. Graph Embedding for Pattern Analysis. 119--138. Springer, New York, NY.
• Bhowmick, S., Rykov, V.V., Ufimtsev, V.V. (2011). ACM SRC poster: a scalable group testing based algorithm for finding d-highest betweenness centrality vertices in large scale networks. Proceedings of the 2011 companion on High Performance Computing Networking, Storage and Analysis Companion. 121--122.
• Bhowmick, S., Eijkhout, V., Freund, Y., Fuentes, E., Keyes, D. (2011). Application of alternating decision trees in selecting sparse linear solvers. Software Automatic Tuning. 153--173. Springer, New York, NY.
• Bansal, S., Bhowmick, S., Paymal, P. (2011). Fast community detection for dynamic complex networks. Complex Networks. 196--207. Springer, Berlin, Heidelberg.
• Bhowmick, S., Hovland, P.D. (2008). A polynomial-time algorithm for detecting directed axial symmetry in Hessian computational graphs. Advances in Automatic Differentiation. 91--102. Springer, Berlin, Heidelberg.
• Norris, B., Bhowmick, S., Kaushik, D., Mclnnes, L.C. (2007). Middleware for dynamic adaptation of component applications. Grid-Based Problem Solving Environments. 127--149. Springer, Boston, MA.
• Bhowmick, S., Kaushik, D., McInnes, L., Norris, B., Raghavan, P. (2006). -Parallel Adaptive Solvers in Compressible PETSc-FUN3D Simulations. Parallel Computational Fluid Dynamics 2005. 277--284.

Conference Proceeding

• Srinivasan, S., Khanda, A., Pandey, A., Das, S., Bhowmick, S., Norris, B. (2023). A Distributed Algorithm for Identifying Strongly Connected Components on Incremental Graphs. 2023 IEEE 35th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD). 109--118.
• Alexander, M., Bhowmick, S., Bogale, B., Diaz, G., Elster, A.C., Ellsworth, D.A., Hernandez, C.J., Jaffe, E., Marquez, J., Melton, A., others. (2023). EduHPC Lightning Talk Summary. Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis. 374--378.
• Tan, N., Luettgau, J., Marquez, J., Teranishi, K., Morales, N., Bhowmick, S., Cappello, F., Taufer, M., Nicolae, B. (2023). Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication. Proceedings of the 52nd International Conference on Parallel Processing. 665--674.
• Bell, P., Suarez, K., Fossum, B., Chapp, D., Bhowmick, S., Taufer, M. (2022). A Research-Based Course Module to Study Non-determinism in High Performance Applications. 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). 346--353.
• Khanda, A., Bhowmick, S., Liang, X., Das, S.K. (2022). Parallel Vertex Color Update on Large Dynamic Networks. 2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC). 115--124.
• Khanda, A., Bhowmick, S., Liang, X., Das, S. Parallel Vertex Coloring on Large Dynamic Networks. International Conference on High-Performance Computing, Data, and Analytics.
• Chowdhury, A., Srinivasan, S., Ghosh, K., Bhowmick, S., Mukherjee, A. (2021). Constant community identification in million scale networks using image thresholding algorithms. ASONAM '21: Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.
• Dockendorf, M., Dantu, P., Morozov, K., Bhowmick, S. (2021). Investing Data with Untrusted Parties using HE. 845-853. Richardson, SECRYPT 2021.
• Qian, W., Bhowmick, S., Mikler, A.R., O'Neill II, M., Ramisetty-Mikler, S. (2020). A Probabilistic Infection Model for Efficient Trace-Prediction of Disease Outbreaks in Contact Networks. International Conference on Computational Science 2020.
• Gasper, W., Cooper, K., Cornelius, N., Ali, H., Bhowmick, S. (2020). Characterization of S. cerevisiae Protein Complexes by Representative DDI Graph Planarity. Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. 1--6.
• Komar, K.S., Santra, A., Bhowmick, S., Chakravarthy, S. (2020). EER MLN: EER Approach for Modeling, Mapping, and Analyzing Complex Data Using Multilayer Networks (MLNs). Conceptual Modeling: 39th International Conference, ER 2020, Vienna, Austria, November 3--6, 2020, Proceedings. 555--572.
• Cooper, K., Cornelius, N., Gasper, W., Bhowmick, S., Ali, H. (2020). On the Planarity of Validated Complexes of Model Organisms in Protein-Protein Interaction Networks. International Conference on Computational Science. 652--666.
• Bhowmick, S., Srinivasan, S., Riazi, S., Das, S., Norris, B. (2018). A Shared-Memory Parallel Algorithm for Updating Single Source Shortest Paths in Weighted Dynamic Graphs. International Conference of High Performance Computing.
• Sarkar, S., Bhowmick, S., Mukherjee, A. (2018). On Rich Clubs of Path-Based Centralities in Networks. Proceedings of the 27th ACM International Conference on Information and Knowledge Management. 567--576.
• Parsinia, M., Peng, Q., Bhowmick, S., Matyjas, J.D., Kumar, S. (2017). Gender Assignment for Directional Full-Duplex FDD Nodes in a Multihop Wireless Network. Ad Hoc Networks. 390--401. Springer, Cham.
• Santra, A., Bhowmick, S. (2017). Holistic Analysis of Multi-source, Multi-feature Data: Modeling and Computation Challenges. International Conference on Big Data Analytics. 59--68.
• Santra, A., Bhowmick, S., Chakravarthy, S. (2017). Hubify: efficient estimation of central entities across multiplex layer compositions. Data Mining Workshops (ICDMW), 2017 IEEE International Conference on. 142--149.
• Srinivasan, S., Bhowmick, S., Das, S. (2016). Application of Graph Sparsification in Developing Parallel Algorithms for Updating Connected Components. 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). 885--891.
• Sarkar, S., Kumar, S., Bhowmick, S., Mukherjee, A. (2016). Sensitivity and reliability in incomplete networks: Centrality metrics to community scoring functions. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 69--72.
• Ufimtsev, V., Sarkar, S., Mukherjee, A., Bhowmick, S. (2016). Understanding stability of noisy networks through centrality measures and local connections. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. 2347--2352.
• Ufimtsev, V., Bhowmick, S. (2014). An extremely fast algorithm for identifying high closeness centrality vertices in large-scale networks. Proceedings of the 4th Workshop on Irregular Applications: Architectures and Algorithms. 53--56.
• Ufimtsev, V., Bhowmick, S., Rajamanickam, S. (2014). Building blocks for graph based network analysis. High Performance Extreme Computing Conference (HPEC), 2014 IEEE. 1--6.
• Ufimtsev, V., Bhowmick, S. (2014). Finding high betweenness centrality vertices in large networks. CSC14: The Sixth SIAM Workshop on Combinatorial Scientific Computing. 45.
• Chakraborty, T., Srinivasan, S., Ganguly, N., Mukherjee, A., Bhowmick, S. (2014). On the permanence of vertices in network communities. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. 1396--1405.
• Dempsey, K., Chen, T., Srinivasan, S., Bhowmick, S., Ali, H. (2013). A structure-preserving hybrid-chordal filter for sampling in correlation networks. High Performance Computing and Simulation (HPCS), 2013 International Conference on. 243--250.
• West, S., Dempsey, K., Bhowmick, S., Ali, H. (2013). Analysis of incrementally generated clusters in biological networks using graph-theoretic filters and ontology enrichment. Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on. 584--591.
• Ufimtsev, V., Bhowmick, S. (2013). Application of group testing in identifying high betweenness centrality vertices in complex networks. Eleventh Workshop on Mining and Learning with Graphs. 1--8.
• Ufimtsev, V., Bhowmick, S. (2013). Identifying high betweenness centrality vertices in large noisy networks. Parallel and Distributed Processing Symposium Workshops \& PhD Forum (IPDPSW), 2013 IEEE 27th International. 2234--2237.
• Dasgupta, P., Bhowmick, S. (2013). Towards Context-Aware, Real Time and Autonomous Decision Making Using Information Aggregation and Network Analytics.. STIDS. 166--169.
• Thapa, I., Bhowmick, S., Bastola, D.R. (2012). A comparison between hierarchical clustering and community detection method in the collection of gene targets for molecular identification of pathogenic fungi. 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops. 756--761.
• Bastola, D.R., McGrath, S., Bhowmick, S., Thapa, I. (2012). A Comparison of Computational Approaches in the Molecular Identification of Pathogenic Organisms. Healthcare Informatics, Imaging and Systems Biology (HISB), 2012 IEEE Second International Conference on. 73--73.
• Halappanavar, M., Feo, J., Dempsey, K., Ali, H., Bhowmick, S. (2012). A novel multithreaded algorithm for extracting maximal chordal subgraphs. Parallel Processing (ICPP), 2012 41st International Conference on. 58--67.
• Lee, K.L., Stotts, D. (2012). Composition of bioinformatics model federations using communication aspects. Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on. 1--5.
• Dempsey, K., Duraisamy, K., Bhowmick, S., Ali, H. (2012). The development of parallel adaptive sampling algorithms for analyzing biological networks. 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops \& PhD Forum. 725--734.
• Duraisamy, K., Dempsey, K., Ali, H., Bhowmick, S. (2011). A noise reducing sampling approach for uncovering critical properties in large scale biological networks. High Performance Computing and Simulation (HPCS), 2011 International Conference on. 721--728.
• Paymal, P., Patil, R., Bhowmick, S., Siy, H. (2011). Measuring disruption from software evolution activities using graph-based metrics. Software Maintenance (ICSM), 2011 27th IEEE International Conference on. 532--535.
• Aluru, S., Bader, D.A., Kalyanaraman, A., Agarwal, G., Aubanel, E., Bhowmick, S., \cCataly\"urek, \"Umit, Chaudhary, V., Clement, M., Feng, W., others. (2011). Message from the workshop chairs. IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum. 426.
• Bhowmick, S., Shafiullah, M., Rai, H., Bastola, D. (2010). A Parallel Non-Alignment Based Approach to Efficient Sequence Comparison using Longest Common Subsequences. Journal of Physics: Conference Series. 256 (1) 012012.
• Chatterjee, A., Bhowmick, S., Raghavan, P. (2010). Feature subspace transformations for enhancing k-means clustering. Proceedings of the 19th ACM international conference on Information and knowledge management. 1801--1804.
• Mclnnes, L.C., Kaushik, D., Norris, B., Bhowmick, S. (2010). Middleware for Dynamic Adaptation of Component Applications. IFIP International Federation for Information Processing. 239 (1)
• Bhowmick, S., Toth, B., Raghavan, P. (2009). Towards low-cost, high-accuracy classifiers for linear solver selection. International Conference on Computational Science. 463--472.
• Chatterjee, A., Bhowmick, S., Raghavan, P. (2008). FAST: Force-directed approximate subspace transformation to improve unsupervised document classification. Proceedings of 6th Text Mining Workshop held in Conjunction with SIAM International Conference on Data Mining, Atlanta, GA, USA.
• Bhowmick, S., Hovland, P.D. (2008). Improving the performance of graph coloring algorithms through backtracking. International Conference on Computational Science. 873--882.
• Norris, B., McInnes, L.C., Bhowmick, S., Li, L. (2007). Adaptive numerical components for PDE-based simulations. PAMM: Proceedings in Applied Mathematics and Mechanics. 7 (1) 1140509--1140510.
• Eijkhout, V., Fuentes, E., Ramakrishnan, N., Kang, P., Bhowmick, S., Keyes, D., Freund, Y. (2006). A self-adapting system for linear solver selection. Proc. 1st int’l workshop on automatic performance tuning (iWAPT2006). 44--53.
• Bhowmick, S., Boman, E.G., Devine, K., Gebremedhin, A., Hendrickson, B., Hovland, P., Munson, T., Pothen, A. (2006). Combinatorial algorithms enabling computational science: tales from the front. Journal of Physics: Conference Series. 46 (1) 453.
• Bhowmick, S., Hovland, P. (2005). A backtracking correction heuristic for improving performance of graph coloring algorithms. Proceedings of the Second International Workshop on Combinatorial Scientific Computing.
• Hovland, P.D., Norris, B., Strout, M.M., Bhowmick, S., Utke, J. (2005). Sensitivity analysis and design optimization through automatic differentiation. Journal of Physics: Conference Series. 16 (1) 466.
• Bhowmick, S., McInnes, L., Norris, B., Raghavan, P. (2004). Robust algorithms and software for parallel PDE-based simulations. Proceedings of the Advanced Simulation Technologies Conference, ASTC. 4 18--22.
• McInnes, L., Norris, B., Bhowmick, S., Raghavan, P. (2003). Adaptive sparse linear solvers for implicit CFD using Newton-Krylov algorithms. Proceedings of the Second MIT Conference on Computational Fluid and Solid Mechanics. 2 1024--1028.
• Bhowmick, S., McInnes, L., Norris, B., Raghavan, P. (2003). The role of multi-method linear solvers in PDE-based simulations. International Conference on Computational Science and Its Applications. 828--839.
• Bhowmick, S., Raghavan, P., Teranishi, K. (2002). A combinatorial scheme for developing efficient composite solvers. International Conference on Computational Science. 325--334.

Journal Article

• Chakraborty, T., Kumar, S., Ganguly, N., Mukherjee, A., Bhowmick, S. GenPerm: A Unified Method for Detecting Non-overlapping and Overlapping Communities Accepted in IEEE TKDE.
• Bhowmick, S., Shontz, S. Obtaining High-Quality Untangled Meshes Through Force-Directed Graph Embedding.
• Zhu, Q., Bhowmick, S. The Intelligent Data Brokerage: A Utility-Enhancing Architecture for Algorithmic Anonymity Measures Nolan Hemmatazad Robin Gandhi.
• Chowdhury, A., Srinivasan, S., Mukherjee, A., Bhowmick, S., Ghosh, K. (2023). Improving Node Classification Accuracy of GNN through Input and Output Intervention. Other. 18 (1) 1--31. ACM New York, NY.
• Khanda, A., Srinivasan, S., Bhowmick, S., Norris, B., Das, S. (2022). A Parallel Algorithm Template for Updating Single-Source Shortest Paths in Large-Scale Dynamic Networks. Other. 33 (4) 929--940.
• Chowdhury, A., Srinivasan, S., Bhowmick, S., Mukherjee, A., Ghosh, K. (2022). Constant community identification in million-scale networks. Other. 12 (1) 70. Springer Vienna Vienna.
• Khanda, A., Srinivasan, S., Bhowmick, S., Norris, B., Das, S. (2022). Efficient Parallel Algorithm for Shortest Path Updates in Dynamic Networks at Scale. Other. 33 (4) 929--940.
• Santra, A., Komar, K., Bhowmick, S., Chakravarthy, S. (2022). From base data to knowledge discovery--A life cycle approach--Using multilayer networks. Other. 141 North-Holland.
• Wendt, J., Phillips, C., Field, R., Prasadan, A., Soundarajan, S., Bhowmick, S., Wilson, T. Partitioning Communication Streams into Graph Snapshots.. IEEE Transactions on Network Science and Engineering.
• Khanda, A., Srinivasan, S., Norris, B., Bhowmick, S., Das, S. (2021). A Parallel Algorithm Template for Updating Single-Source Shortest Paths in Large-Scale Dynamic Networks. IEEE Transactions on Parallel and Distributed Systems.
• Bell, P., Suarez, K., Chapp, D., Tran, N., Bhowmick, S., Taufer, M. (2021). ANACIN-X: A software framework for studying non-determinism in MPI applications. Software Impacts.
• Chapp, D., Tan, N., Bhowmick, S., Taufer, M. (2021). Identifying degree and sources of non-determinism in MPI applications via graph kernels. IEEE Transactions on Parallel and Distributed Systems.
• Qian, W., Bhowmick, S., O'Neill, M., Ramisetty-Mikler, S., Mikler, A.R. (2021). Applying a Probabilistic Infection Model for studying contagion processes in contact networks. Journal of Computational Science. 54 Elsevier. https://www.sciencedirect.com/science/article/abs/pii/S1877750321001046?via%3Dihub
• Santra, A., Komar, K.S., Bhowmick, S., Chakravarthy, S. (2020). A new community definition for multilayer networks and a novel approach for its efficient computation. Other.
• Santra, A., Komar, K.S., Bhowmick, S., Chakravarthy, S. (2019). An Efficient Framework for Computing Structure-And Semantics-Preserving Community in a Heterogeneous Multilayer Network. Other.
• Santra, A., Komar, K.S., Bhowmick, S., Chakravarthy, S. (2019). Making a case for mlns for data-driven analysis: Modeling, efficiency, and versatility. Other.
• Santra, A., Komar, K.S., Bhowmick, S., Chakravarthy, S. (2019). Structure-preserving community in a multilayer network: definition, detection, and analysis. Other.
• Srinivasan, S., Pollard, S., Das, S.K., Norris, B., Bhowmick, S. (2018). A Shared-Memory Algorithm for Updating Tree-Based Properties of Large Dynamic Networks. Other. IEEE.
• Sarkar, S., Sikdar, S., Bhowmick, S., Mukherjee, A. (2018). Using core-periphery structure to predict high centrality nodes in time-varying networks. Other. 32 (5) 1368--1396. Springer US.
• Santra, A., Bhowmick, S., Chakravarthy, S. (2017). Efficient community re-creation in multilayer networks using boolean operations. Procedia Computer Science. 108 58--67. Elsevier.
• Kepner, J., Bhowmick, S., Bulu\cc, Ayd\in, Caceres, R., Crouser, R.J., Gadepally, V., Miller, B., Webster, J. (2017). SIAM Data Mining" Brings It" to Annual Meeting. Other.
• Chakraborty, T., Kumar, S., Ganguly, N., Mukherjee, A., Bhowmick, S. (2016). GenPerm: a unified method for detecting non-overlapping and overlapping communities. Other. 28 (8) 2101--2114. IEEE.
• Weinbub, J., Baboulin, M., Thacker, W., Polok, L., Bhowmick, S. (2016). High performance computing symposium (HPC'16). Other. 48 (4)
• Chakraborty, T., Srinivasan, S., Ganguly, N., Mukherjee, A., Bhowmick, S. (2016). Permanence and community structure in complex networks. Other. 11 (2) 14. ACM.
• Santra, A., Bhowmick, S., Chakravarthy, S. (2016). Scalable Holistic Analysis of Multi-Source, Data-Intensive Problems Using Multilayered Networks. Other.
• Bhowmick, S., Chen, T., Halappanavar, M. (2015). A new augmentation based algorithm for extracting maximal chordal subgraphs. Other. 76 132--144. Academic Press.
• Dempsey, K., Ufimtsev, V., Bhowmick, S., Ali, H. (2014). A parallel template for implementing filters for biological correlation networks. Other. 12 (4) 285--297.
• Meyer, P., Siy, H., Bhowmick, S. (2014). Identifying important classes of large software systems through k-core decomposition. Other. 17 (07n08) 1550004. World Scientific Publishing Company.
• Hemmatazad, N., Gandhi, R., Zhu, Q., Bhowmick, S. (2014). The Intelligent Data Brokerage: A Utility-Enhancing Architecture for Algorithmic Anonymity Measures. Other. 2 (1) 22--33. IGI Global.
• Cooper, K.D., Ufimtsev, V., Bhowmick, S., Ali, H. (2013). A Parallel Template for Implementing Filters for Biological Correlation Networks.
• Cooper, K.D., Chen, T., Srinivasan, S., Bhowmick, S., Ali, H. (2013). A structure-preserving hybrid-chordal filter for sampling in correlation networksA structure-preserving hybrid-chordal filter for sampling in correlation networks.
• Chakraborty, T., Srinivasan, S., Ganguly, N., Bhowmick, S., Mukherjee, A. (2013). Constant communities in complex networks. Scientific Reports. 3 1825. Nature Publishing Group.
• Ufimtsev, V.V., Bhowmick, S., Rykov, V.V. (2012). A Scalable Group Testing Based Algorithm for Finding d-highest Betweenness Centrality Vertices in Large Scale Networks.
• Dempsey, K., Bhowmick, S., Ali, H. (2012). Function-preserving filters for sampling in biological networks. Procedia Computer Science. 9 587--595. Elsevier.
• Srinivasan, S., Chakraborty, T., Bhowmick, S. (2012). Identifying base clusters and their application to maximizing modularity.. Other. 588 82.
• Cooper, K.D., Chen, T., Bhowmick, S., Ali, H. (2012). On the design of advanced filters for biological networks using graph theoretic properties.
• Cooper, K.D., Duraisamy, K., Bhowmick, S., Ali, H. (2012). The Development of Parallel Adaptive Sampling Algorithms for Analyzing Biological Networks.
• Srinivasan, S., Bhowmick, S. (2012). Using stable communities for maximizing modularity. Other. DIMACS Atlanta, Georgia.
• Cooper, K.D., Duraisamy, K., Ali, H., Bhowmick, S. (2011). A parallel graph sampling algorithm for analyzing gene correlation networks. Procedia Computer Science. 4 (2011) 136.
• Paymal, P., Patil, R., Bhomwick, S., Siy, H. (2011). Empirical study of software evolution using community detection. Other.
• Bhowmick, S. (2010). Novel Applications of Graph Embedding Techniques. Georgia Institute of Technology.
• Bhowmick, S., Shontz, S.M. (2010). Towards high-quality, untangled meshes via a force-directed graph embedding approach. Procedia Computer Science. 1 (1) 357--366. Elsevier.
• Bhowmick, S., Hovland, P. (2007). Exploiting Symmetry for Hessian Computation.
• Bhowmick, S., Eijkhout, V., Freund, Y., Fuentes, E., Keyes, D. (2006). Application of machine learning to the selection of sparse linear solvers. Other.
• Bhowmick, S., Raghavan, P., McInnes, L., Norris, B. (2004). Faster PDE-based simulations using robust composite linear solvers. Other. 20 (3) 373--387. North-Holland.

Newspaper

• Bhowmick, S., Buluc, A., Kepner, J., Miller, B., Caceres, R., Gadepally, V., Crouser, J., Webster, J. (2016). Data Mining Brings IT to SIAM Annual Meeting.

Ph.D. Thesis

• Thotakuri, V. (2014). Analyzing Shakespeare's Plays in a Network Perspective. University of Nebraska at Omaha.
• Bhowmick, S. (2005). Multimethod solvers: algorithms, applications and software. The Pennsylvania State University.

Technical Report

• Tan, N., Nicolae, B., Morales, N., Teranishi, K., Bhowmick, S., Cappello, F., Taufer, M. (2022). Towards Access Pattern Aware Checkpointing For Kokkos Applications.. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).
• Field, Jr, R.V., Wendt, J.D., Phillips, C.A., Wilson, T., Soundarajan, S., Bhowmick, S. (2020). Partitioning Communication Streams into Graph Snapshots.. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).
• Rajamanickam, S., Bhowmick, S. (2014). BASIC BRICKS OR MINDSTORMS: GRAPH BUILDING BLOCKS.. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).
• Rajamanickam, S., Ufimtsev, V., Bhowmick, S. (2014). Building Blocks for Graph Based Network Analysis.. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).
• Berry, J.W., Leung, V.J., Phillips, C.A., Pinar, A., Robinson, D.G., Berger-Wolf, T., Bhowmick, S., Casleton, E., Kaiser, M., Nordman, D.J., others. (2014). Statistically significant relational data mining. Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States).
• Berger-Wolf, T., Berry, J., Bhowmick, S., Casleton, E., Kaiser, M., Leung, V., Nordman, D., Phillips, C., Pinar, A., Robinson, D., others. (2014). Statistically significant relational data mining: LDRD report. Tech. Rep. SAND2014-1105. February.
• Bhowmick, S., Hovland, P. (2006). A Polynomial Time Algorithm for the Detection of Axial Symmetry in Directed Acyclic Graphs. ANL/MCS-P1314-0106, Argonne National Laboratory, Illinois.

Contracts, Grants and Sponsored Research

Grant - Research

• Ji, Y. (Principal), Bhowmick, S. (Co-Principal), "Collaborative Research: SHF: Small: LEGAS: Learning Evolving Graphs At Scale," sponsored by National Science Foundation, Federal, $308739 Funded. (2024 - 2026).
• Bhowmick, S. (Principal), Das, S. (Principal), Norris, B. (Principal), "Framework: CSSI:CANDY: Cyberinfrastructure for Accelerating Innovation of Network Dynamics," sponsored by NSF, Federal, $449000 Funded. (2021 - 2025).
• Compson, Z.G. (Principal), Bhowmick, S. (Co-Principal), Lichtenberg, E.M. (Co-Principal), Bohenek, J. (Co-Principal), "GRAPH-N: Generating Rapid Applications for Predicting Heuristic Networks," sponsored by COS & COE, University of North Texas, $10000 Funded. (2023 - 2024).
• Dantu, R. (Principal), Morozov, K. (Co-Principal), Dantu, S. (Co-Principal), "PrivacyPreserving Analytics on a Data Cooperative for Comprehensive Threat Prevention," sponsored by National Security Agency, Federal, $750000 Funded. (2021 - 2024).
• Bhowmick, S. (Principal), Madduri, K. (Principal), Chakravarthy, S. (Principal), "NetSplicer," sponsored by NSF, Federal, $320043 Funded. (2019 - 2023).
• Dantu, R. (Principal), Morozov, K., Bhowmick, S. (Co-Principal), "Locating Super-Spreaders Through Partnership of Anonymization and Encryption," sponsored by NSA, Federal, $299944 Funded. (2020 - 2023).
• Bhowmick, S. (Principal), Chakravarthy, S. (Principal), Madduri, K. (Principal), "Collaborative Research:CCRI:Planning: A Multilayer Network (MLN) CommunityInfrastructure forData,Interaction,Visualization, and softwarE(MLN-DIVE)," sponsored by NSF, Federal, $30151 Funded. (2021 - 2022).
• Bhowmick, S. (Principal), Taufer, M. (Principal), Jagode, H. (Co-Principal), "ANACIN-X: Analysis and modeling of Nondeterminism and Associated Costs in eXtreme scale applications," sponsored by NSF, Federal, $300000 Funded. (2019 - 2022).
• Bhowmick, S., "REU for Collaborative Research: SHF: Medium: NetSplicer: Scalable Decoupling-based Algorithms for Multilayer Network Analysis," sponsored by NSF, Federal, $16000 Funded. (2021 - 2022).
• Bhowmick, S. (Principal), Das, S. (Principal), Norris, B. (Principal), "SPX: Collaborative Research: SANDY: Sparsification-Based Approach for Analyzing Network Dynamics," sponsored by NSF, Federal, $225000 Funded. (2017 - 2020).
• Bhowmick, S., Das, S. (Principal), "XPS: EXPL: FP: Collaborative Research: SPANDAN: Scalable Parallel Algorithms for Network Dynamics Analysis," sponsored by NSF, Federal, $146000 Funded. (2015 - 2019).
• Bhowmick, S. (Principal), "Collaborative Research: Framework Implementations: CSSI: CANDY: Cyberinfrastructure for Accelerating Innovation in Network Dynamics," sponsored by National Science Foundation, FED, Funded. (2021 - 2025).
• Morozov, K. (Co-Principal), Dantu, R. (Principal), Bhowmick, S. (Co-Principal), "2021 NCAE-C-002- University of North Texas," sponsored by National Security Agency, FED, Funded. (2021 - 2024).
• Bhowmick, S. (Principal), Madduri, K. (Principal), Chakravarthy, S. (Principal), "NetSplicer," sponsored by NSF, Federal, Funded. (2019 - 2023).
• Bhowmick, S. (Principal), "Collaborative Research: SHF Core: Medium: NetSplicer: Scalable Decoupling-based Algorithms for Multilayer Network Analysis," sponsored by National Science Foundation, FED, Funded. (2020 - 2023).
• Bhowmick, S. (Co-Principal), Dantu, R. (Principal), Morozov, K., "Locating Super-Spreaders Through Partnership of Anonymization and Encryption," sponsored by NSA, Federal, Funded. (2020 - 2022).
• Bhowmick, S. (Principal), "Collaborative Research:CCRI:Planning: A Multilayer Network (MLN) CommunityInfrastructure forData,Interaction,Visualization, and softwarE(MLN-DIVE)," sponsored by National Science Foundation, FED, Funded. (2021 - 2022).
• Morozov, K. (Co-Principal), Dantu, R. (Principal), Bhowmick, S. (Co-Principal), "2020 University of North Texas NCAE- C Research Grant," sponsored by National Security Agency, FED, Funded. (2020 - 2022).
• Bhowmick, S. (Principal), Taufer, M. (Principal), Jagode, H. (Co-Principal), "ANACIN-X: Analysis and modeling of Nondeterminism and Associated Costs in eXtreme scale applications," sponsored by NSF, Federal, Funded. (2019 - 2022).
• Bhowmick, S. (Principal), "SANDY: Sparsification-Based Approach for Analyzing Network Dynamics," sponsored by National Science Foundation, FED, Funded. (2018 - 2022).
• Bhowmick, S. (Principal), "SHF: Medium: Collaborative Research: ANACIN-X: Analysis and modeling of Non-determinism and Associated Costs in eXtreme scale applications," sponsored by National Science Foundation, FED, Funded. (2019 - 2022).
• Bhowmick, S. (Principal), Das, S. (Principal), Norris, B. (Principal), "SPX: Collaborative Research: SANDY: Sparsification-Based Approach for Analyzing Network Dynamics," sponsored by NSF, Federal, Funded. (2017 - 2020).
• Bhowmick, S. (Principal), "XPS: EXPL: FP: Collaborative Research: SPANDAN: Scalable Parallel Algorithms for Network Dynamics Analysis," sponsored by National Science Foundation, FED, Funded. (2018 - 2019).
• Bhowmick, S., Das, S. (Principal), "XPS: EXPL: FP: Collaborative Research: SPANDAN: Scalable Parallel Algorithms for Network Dynamics Analysis," sponsored by NSF, Federal, Funded. (2015 - 2019).

Grant - Teaching

• Caino-Lorres, S. (Principal), Bell, P. (Co-Principal), Bhowmick, S. (Co-Principal), "Training Next-Generation Data Scientists in Non-Deterministic Scientific Data Generation," sponsored by South Big Data Hub, Federal, $49998 Funded. (2023).