Subhashis Hazarika

Subhashis Hazarika

Research Scientist

Peer-reviewed Journal and Conference Articles

  • Subhashis Hazarika, Haruki Hirasawa, Sookyung Kim, Kalai Ramea, Salva R Cachay, Peetak Mitra, Dipti Hingmire, Hansi Singh, Phil J Rasch: “HAiVA: Hybrid AI-assisted Visual Analysis Framework to Study the Effects of Cloud Properties on Climate Patterns”, arXiv preprint arXiv:2305.07859, 2023 (accepted at IEEE Vis 2023)
  • Raman Goyal, Dhrubajit Chowdhury, Subhashis Hazarika, Raj Pradip Khawale, Shubhendu Kumar Singh, Lara Crawford, Rahul Rai: “Hybrid Machine Learning and Autonomous Control assisted Framework for Fault Diagnostics and Mitigation in Diesel Engines”, Artificial Intelligence Applications and Innovations. AIAI 2023. IFIP Advances in Information and Communication Technology, vol 676. Springer, Cham. DOI: 10.1007/978-3-031-34107-6_26
  • Subhashis Hazarika, Ayan Biswas, Earl Lawrence, Phillip J. Wolfram: “Probabilistic Principal Component Analysis Guided Spatial Partitioning of Multivariate Ocean Biogeochemistry Data”, Workshop on Visualization in Environmental Sciences (EnvirVis), EuroVis 2021, DOI: 10.2312/envirvis.20211078.
  • Subhashis Hazarika, Ayan Biswas, Phillip J. Wolfram, Earl Lawrence, Nathan Urban:”Relationship-aware Multivariate Sampling Strategy for Scientific Simulation Data”, 2020 IEEE VisualizationConference (VIS), DOI: 10.1109/VIS47514.2020.00015.
  • Subhashis Hazarika, Haoyu Li, Ko-Chih Wang, Han-Wei Shen, Ching-Shan Chou: “NNVA: NeuralNetwork Assisted Visual Analysis of Yeast Cell Polarization Simulation”, IEEE Transactions on Visualization and Computer Graphics, 26 (1), 34-44 (2020). [Best Paper Honorable Mention Award at IEEE Vis 2019].
  • Piyush Chawla, Subhashis Hazarika, Han-Wei Shen: “Token-wise Sentiment Decomposition for ConvNet: Visualizing a Sentiment Classifier”, Visual Informatics, Elsevier 2468-502X (2020).
  • Subhashis Hazarika, Soumya Dutta, Han-Wei Shen, Jen-Ping Chen: “CoDDA: A Flexible Copula-based Distribution Driven Analysis Framework for Large-Scale Multivariate Datasets”, IEEE Transactions on Visualization and Computer Graphics, 25(1): 1214-1224 (2019).
  • Qun Liu, Subhashis Hazarika, John M Patchett, James Paul Ahrens, Ayan Biswas: “Deep Learning-Based Feature-Aware Data Modeling for Complex Physics Simulations”, International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2019).
  • Junpeng Wang, Subhashis Hazarika, Cheng Li, Han-Wei Shen: “Visualization and Visual Analysis of Ensemble Data: A Survey”, IEEE Transactions on Visualization and Computer Graphics, 25(9): 2853-2872 (2019).
  • Subhashis Hazarika, Ayan Biswas, Han-Wei Shen: “Uncertainty Visualization Using Copula-Based Analysis in Mixed Distribution Models”, IEEE Transactions on Visualization and Computer Graphics,24(1): 934-943 (2018).
  • Subhashis Hazarika, Ayan Biswas, Soumya Dutta, Han-Wei Shen: “Information Guided Exploration of Scalar Values and Isocontours in Ensemble Datasets”, Entropy 2018, 20(7), 540. (Special Issue Information Theory Application in Visualization).
  • Subhashis Hazarika, Soumya Dutta, Han-Wei Shen: “Visualizing the Variations of Ensemble of Isosurfaces”, IEEE Pacific Visualization Symposium (PacificVis), 2016, 209-213.
  • Subhashis Hazarika, Tzu-Hsuan Wei, Rajaditya Mukherjee, Alexandru Barbur: “Visualizing the life and anatomy of dark matter”, IEEE Scientific Visualization Conference (SciVis), 2015, 101-106.
  • Sanjib Sadhu, Subhashis Hazarika, Kapil Jain, Saurav Basu, Tanmay De: “GRP-CH Heuristic for Generating Random Simple Polygon”, 23rd International Workshop on Combinatorial Algorithms 2012:Page 293-302, Springer LNCS Volume.

Book Chapters

  • Soumya Dutta, Subhashis Hazarika, Han-Wei Shen: “In Situ Statistical Distribution-based Data Summarization and Visual Analysis”, In Situ Visualization for Computational Science, 2021. Publisher:Springer.

Preprints, Abstracts and White Papers

  • Soo Kyung Kim, Kalai Ramea, Salva Rühling Cachay, Haruki Hirasawa, Subhashis Hazarika, Dipti Hingmire, Peetak Mitra, Philip J Rasch, Hansi A Singh: “Climate Intervention Analysis using AI Model Guided by Statistical Physics Principles”, arXiv preprint arXiv:2302.03258, 2023 (under review)
  • Haruki Hirasawa, Sookyung Kim, Peetak Mitra, Subhashis Hazarika, Salva Ruhling-Cachay, Dipti Hingmire, Kalai Ramea, Hansi Singh, Philip J Rasch: “Accelerating exploration of Marine Cloud Brightening impacts on tipping points Using an AI Implementation of Fluctuation-Dissipation Theorem”, arXiv preprint arXiv:2302.01957, 2023
  • Dipti Swapnil Hingmire, Hansi Alice Singh, Haruki Hirasawa, Phil Rasch, Linda Hedges, Brian Dobbins, Peetak Mitra, Subhashis Hazarika, Soo Kyung Kim, Kalai Ramea: “Will correcting cloud radiative biases over the Southern Ocean improve precipitation biases over the Indian subcontinent in CESM2 simulations?”: AGU Fall Meeting 2022
  • Subhashis Hazarika, Kalai Ramea, Soo Kyung Kim, Peetak Mitra, Salva Ruhling Cachay, Haruki Hirasawa, Dipti Swapnil Hingmire, Hansi Alice Singh, Phil Rasch: “Interactive Visual Analytics to Study the Impacts of Cloud Radiative Properties on Climate Patterns”, AGU Fall Meeting 2022
  • Dipti Swapnil Hingmire, Haruki Hirasawa, Hansi Alice Singh, Salva Ruhling Cachay, Soo Kyung Kim, Peetak Mitra, Subhashis Hazarika, Kalai Ramea, Phil Rasch: “AI assisted evaluation of ESMs in simulating observed cloud climate interactions”, AGU Fall Meeting 2022
  • Peetak Mitra, Salva Ruhling Cachay, Soo Kyung Kim, Subhashis Hazarika, Kalai Ramea, Dipti Swapnil Hingmire, Haruki Hirasawa, Phil Rasch, Hansi Alice Singh: “ClimFormer: building an attention-based climate emulator”, AGU Fall Meeting 2022
  • Hansi Alice Singh, Haruki Hirasawa, Dipti Hingmire, Subhashis Hazarika, Soo Kyung Kim, Salva Ruhling Cachay, Peetak Mitra, Kalai Ramea, Phil Rasch: “Marine Cloud Brightening Intervention Optimization using a Hybrid AI Approach”, AGU Fall Meeting 2022
  • Haruki Hirasawa, Dipti Hingmire, Hansi Alice Singh, Phil Rasch, Linda Hedges, Brian Dobbins, Peetak Mitra, Subhashis Hazarika, Soo Kyung Kim, Kalai Ramea: “Marine Cloud Brightening Forcing and Climate Response in the Community Earth System Model 2”, AGU Fall Meeting 2022
  • Peetak Mitra, Dipti Swapnil Hingmire, Haruki Hirasawa, Salva Ruhling Cachay, Subhashis Hazarika, Soo Kyung Kim, Phil Rasch, Hansi Alice Singh, Kalai Ramea: “On incorporating first principles based physical conservation laws into global climate emulators”, AGU Fall Meeting 2022
  • Aditi Mishra, Subhashis Hazarika, Ayan Biswas, Chris Bryan: “Filling the Void: Deep Learning-based Reconstruction of Sampled Spatiotemporal Scientific Simulation Data”, OSF Preprints, 2022
  • Steven Morley, Natalie Klein, Divya Banesh, Subhashis Hazarika, Vania Jordanova, Michael Henderson, Earl Lawrence, Ayan Biswas: “Objective and scalable feature identification and analysis in high-resolution simulations: Application to bursty bulk flows”, AGU Fall Meeting 2021
  • Ayana Ghosh, Dennis P Trujillo, Subhashis Hazarika, Elizabeth Schiesser, Jian-Xin Zhu, Serge Nakhmanson: “Identification of novel organic ferroelectrics: A study combining importance sampling with machine learning”, arXiv preprint arXiv:2108.13206, 2021