Subhashis Hazarika

Subhashis Hazarika

Research Scientist

Peer-reviewed Journal and Conference Articles

  • 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: 19th AIAI 2023, León, Spain (DOI: coming soon)
  • 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

  • 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 (under review)
  • 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