Publications (18)
SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction
Sujit Roy, Dinesha V. Hegde, Johannes Schmude +22
This paper introduces a high resolution, machine learning-ready heliophysics dataset derived from NASA's Solar Dynamics Observatory (SDO), specifically designed to advance machine…
AI Foundation Model for Heliophysics: Applications, Design, and Implementation
Sujit Roy, Talwinder Singh, Marcus Freitag +14
Deep learning-based methods have been widely researched in the areas of language and vision, demonstrating their capacity to understand long sequences of data and their usefulness…
CLUE: Contextualised Unified Explainable Learning of User Engagement in Video Lectures
Sujit Roy, Gnaneswara Rao Gorle, Vishal Gaur +2
Predicting contextualised engagement in videos is a long-standing problem that has been popularly attempted by exploiting the number of views or the associated likes using differen…
Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves
Aman Gupta, Aditi Sheshadri, Sujit Roy +5
Global climate models parameterize a range of atmospheric-oceanic processes like gravity waves, clouds, moist convection, and turbulence that cannot be sufficiently resolved. These…
Landslide Hazard Mapping with Geospatial Foundation Models: Geographical Generalizability, Data Scarcity, and Band Adaptability
Wenwen Li, Sizhe Wang, Hyunho Lee +4
Landslides cause severe damage to lives, infrastructure, and the environment, making accurate and timely mapping essential for disaster preparedness and response. However, conventi…
A Data-Driven Framework for Identifying Investment Opportunities in Private Equity
Samantha Petersone, Alwin Tan, Richard Allmendinger +2
The core activity of a Private Equity (PE) firm is to invest into companies in order to provide the investors with profit, usually within 4-7 years. To invest into a company or not…
Towards High-Resolution Alignment and Super-Resolution of Multi-Sensor Satellite Imagery
Philip Wootaek Shin, Vishal Gaur, Rahul Ramachandran +4
High-resolution satellite imagery is essential for geospatial analysis, yet differences in spatial resolution across satellite sensors present challenges for data fusion and downst…
Towards a Foundation Model for the Martian Atmosphere
Sujit Roy, Udayshankar Nair, Yuling Wu +16
The martian atmosphere hosts dynamical phenomena ranging from planet-encircling dust storms to mesoscale orographic clouds and nocturnal low-level jets. General circulation model s…
WxC-Bench: A Novel Dataset for Weather and Climate Downstream Tasks
Rajat Shinde, Christopher E. Phillips, Kumar Ankur +10
High-quality machine learning (ML)-ready datasets play a foundational role in developing new artificial intelligence (AI) models or fine-tuning existing models for scientific appli…
Machine Learning Global Simulation of Nonlocal Gravity Wave Propagation
Aman Gupta, Aditi Sheshadri, Sujit Roy +3
Global climate models typically operate at a grid resolution of hundreds of kilometers and fail to resolve atmospheric mesoscale processes, e.g., clouds, precipitation, and gravity…
Recognition of Frequencies of Short-Time SSVEP Signals Utilizing an SSCCA-Based Spatio-Spectral Feature Fusion Framework
Saif Bashar, Samia Nasir Nira, Shabbir Mahmood +3
A brain-computer interface (BCI) facilitates direct communication between the brain and external equipment through EEG, which is preferred for its superior temporal resolution. Amo…
Prithvi WxC: Foundation Model for Weather and Climate
Johannes Schmude, Sujit Roy, Will Trojak +26
Triggered by the realization that AI emulators can rival the performance of traditional numerical weather prediction models running on HPC systems, there is now an increasing numbe…
Foundation Models for Generalist Geospatial Artificial Intelligence
Johannes Jakubik, Sujit Roy, C. E. Phillips +30
Significant progress in the development of highly adaptable and reusable Artificial Intelligence (AI) models is expected to have a significant impact on Earth science and remote se…
PDE foundation models are skillful AI weather emulators for the Martian atmosphere
Johannes Schmude, Sujit Roy, Liping Wang +10
We show that AI foundation models that are pretrained on numerical solutions to a diverse corpus of partial differential equations can be adapted and fine-tuned to obtain skillful…
Prithvi-Precip: Integrating Satellite Observations into an Atmospheric AI Foundation Model for Precipitation Forecasting
Simon Pfreundschuh, Christian D. Kummerow, Johannes Schmude +5
Accurate precipitation forecasting remains one of the most challenging problems in weather prediction. While recent AI weather prediction (AIWP) systems have achieved substantial i…
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications
Daniela Szwarcman, Sujit Roy, Paolo Fraccaro +33
This paper presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2 million global time…
Surya: Foundation Model for Heliophysics
Sujit Roy, Johannes Schmude, Rohit Lal +30
Heliophysics is central to understanding and forecasting space weather events and solar activity. Despite decades of high-resolution observations from the Solar Dynamics Observator…
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation
S. Karthik Mukkavilli, Daniel Salles Civitarese, Johannes Schmude +12
Machine learning and deep learning methods have been widely explored in understanding the chaotic behavior of the atmosphere and furthering weather forecasting. There has been incr…