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Sanjukta Bhowmick

Title: Associate Professor

Department: Computer Science and Engineering

College: College of Engineering

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, Pennsylvania State University, 2004
    Major: Computer Science and Engineering

Current Scheduled Teaching

CSCE 6950.942Doctoral DissertationSpring 2025
CSCE 5170.001Graph TheorySpring 2025
CSCE 6940.942Individual ResearchSpring 2025
CSCE 5150.006Analysis of Computer AlgorithmsFall 2024
CSCE 6950.842Doctoral DissertationFall 2024
CSCE 6940.841Individual ResearchFall 2024

Previous Scheduled Teaching

CSCE 6940.842Individual ResearchSummer 10W 2024
CSCE 6933.001Advanced Topics in Computer Science and EngineeringSpring 2024 SPOT
CSCE 6950.942Doctoral DissertationSpring 2024
CSCE 5170.001Graph TheorySpring 2024 SPOT
CSCE 6940.919Individual ResearchSpring 2024
CSCE 4999.742Senior ThesisSpring 2024
CSCE 5150.006Analysis of Computer AlgorithmsFall 2023 SPOT
CSCE 6950.842Doctoral DissertationFall 2023
CSCE 6940.841Individual ResearchFall 2023
CSCE 6933.001Advanced Topics in Computer Science and EngineeringSpring 2023 SPOT
CSCE 6950.925Doctoral DissertationSpring 2023
CSCE 5170.001Graph TheorySpring 2023 SPOT
CSCE 6940.919Individual ResearchSpring 2023
CSCE 5150.001Analysis of Computer AlgorithmsFall 2022 SPOT
CSCE 6950.842Doctoral DissertationFall 2022
CSCE 6940.841Individual ResearchFall 2022
CSCE 6940.842Individual ResearchFall 8W2 2022
CSCE 4890.742Directed StudySpring 2022
CSCE 6950.925Doctoral DissertationSpring 2022
CSCE 5170.001Graph TheorySpring 2022 SPOT
CSCE 6940.919Individual ResearchSpring 2022
CSCE 6940.742Individual ResearchFall 8W2 2021
CSCE 6900.742Special ProblemsFall 2021
CSCE 4890.742Directed StudySummer 10W 2021
CSCE 6933.742Advanced Topics in Computer Science and EngineeringSpring 2021 SPOT
CSCE 4110.001AlgorithmsSpring 2021 Syllabus SPOT
CSCE 4110.004AlgorithmsSpring 2021 Syllabus SPOT
CSCE 6940.705Individual ResearchSpring 2021
CSCE 4110.001AlgorithmsFall 2020 Syllabus SPOT
CSCE 4110.004AlgorithmsFall 2020 Syllabus SPOT
CSCE 6940.742Individual ResearchFall 2020
CSCE 5950.742Master's ThesisFall 2020
CSCE 4110.001AlgorithmsSpring 2020 Syllabus
CSCE 4110.002AlgorithmsSpring 2020 Syllabus
CSCE 5950.742Master's ThesisSpring 2020
CSCE 6933.001Advanced Topics in Computer Science and EngineeringFall 2019 SPOT
CSCE 4110.001AlgorithmsFall 2019 Syllabus SPOT
CSCE 4110.002AlgorithmsFall 2019 Syllabus SPOT
CSCE 6940.742Individual ResearchFall 8W2 2019
CSCE 4110.001AlgorithmsSpring 2019 Syllabus SPOT
CSCE 4110.002AlgorithmsSpring 2019 Syllabus SPOT
CSCE 4890.805Directed StudySpring 2019
CSCE 4110.001AlgorithmsFall 2018 Syllabus SPOT
CSCE 4110.002AlgorithmsFall 2018 Syllabus SPOT
CSCE 4110.021AlgorithmsSummer 10W 2018 Syllabus SPOT
CSCE 4110.002AlgorithmsSpring 2018 Syllabus SPOT
CSCE 4110.002AlgorithmsFall 2017 Syllabus SPOT
CSCE 4110.001AlgorithmsFall 2016 Syllabus SPOT
CSCE 2110.021Computing Foundations IISummer 10W 2016 Syllabus SPOT
CSCE 2110.201Computing Foundations IISummer 10W 2016 SPOT
CSCE 2110.202Computing Foundations IISummer 10W 2016 SPOT

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).
,
Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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