25 citations · 28 across the 9 of their papers we have counts for
9 papers
SWR-Viz: AI-assisted Interactive Visual Analytics Framework for Ship Weather Routing
Subhashis Hazarika, Leonard Lupin-Jimenez, Rohit Vuppala +2
Efficient and sustainable maritime transport increasingly depends on reliable forecasting and adaptive routing, yet operational adoption remains difficult due to forecast latencies…
Simultaneous emulation and downscaling with physically-consistent deep learning-based regional ocean emulators
Leonard Lupin-Jimenez, Moein Darman, Subhashis Hazarika +5
Building on top of the success in AI-based atmospheric emulation, we propose an AI-based ocean emulation and downscaling framework focusing on the high-resolution regional ocean ov…
HAiVA: Hybrid AI-assisted Visual Analysis Framework to Study the Effects of Cloud Properties on Climate Patterns
Subhashis Hazarika, Haruki Hirasawa, Sookyung Kim +6
Clouds have a significant impact on the Earth's climate system. They play a vital role in modulating Earth's radiation budget and driving regional changes in temperature and precip…
Climate Intervention Analysis using AI Model Guided by Statistical Physics Principles
Soo Kyung Kim, Kalai Ramea, Salva Rühling Cachay +6
The availability of training data remains a significant obstacle for the implementation of machine learning in scientific applications. In particular, estimating how a system might…
Accelerating exploration of Marine Cloud Brightening impacts on tipping points Using an AI Implementation of Fluctuation-Dissipation Theorem
Haruki Hirasawa, Sookyung Kim, Peetak Mitra +6
Marine cloud brightening (MCB) is a proposed climate intervention technology to partially offset greenhouse gas warming and possibly avoid crossing climate tipping points. The impa…
Identification of novel organic ferroelectrics: A study combining importance sampling with machine learning
Ayana Ghosh, Dennis P. Trujillo, Subhashis Hazarika +5
Recent advances in the synthesis of polar molecular materials have produced practical alternatives to ferroelectric ceramics, opening up exciting new avenues for their incorporatio…
Relationship-aware Multivariate Sampling Strategy for Scientific Simulation Data
Subhashis Hazarika, Ayan Biswas, Phillip J. Wolfram +2
With the increasing computational power of current supercomputers, the size of data produced by scientific simulations is rapidly growing. To reduce the storage footprint and facil…
Deep Learning-Based Feature-Aware Data Modeling for Complex Physics Simulations
Qun Liu, Subhashis Hazarika, John M. Patchett +2
Data modeling and reduction for in situ is important. Feature-driven methods for in situ data analysis and reduction are a priority for future exascale machines as there are curren…
NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation
Subhashis Hazarika, Haoyu Li, Ko-Chih Wang +2
Complex computational models are often designed to simulate real-world physical phenomena in many scientific disciplines. However, these simulation models tend to be computationall…