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Rahul Ramachandran
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2020 – today
- 2024
- [c47]Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka, Muthukumaran Ramasubramanian, Takuma Udagawa, Iksha Gurung, Nishan Pantha, Rong Zhang, Bharath Dandala, Rahul Ramachandran, Manil Maskey, Kaylin M. Bugbee, Michael Little, Elizabeth Fancher, Irina Gerasimov, Armin Mehrabian, Lauren M. Sanders, Sylvain Costes, Sergi Blanco-Cuaresma, Kelly E. Lockhart, Thomas Allen, Félix Grèzes, Megan Ansdell, Alberto Accomazzi, Yousef El-Kurdi, Davis Wertheimer, Birgit Pfitzmann, Cesar Berrospi Ramis, Michele Dolfi, Rafael Teixeira de Lima, Panagiotis Vagenas, S. Karthik Mukkavilli, Peter W. J. Staar, Sanaz Vahidinia, Ryan McGranaghan, Tsengdar J. Lee:
INDUS: Effective and Efficient Language Models for Scientific Applications. EMNLP (Industry Track) 2024: 98-112 - [c46]Paridhi Parajuli, Rajat Shinde, Iksha Gurung, Manil Maskey, Rahul Ramachandran:
Curating AI-Ready Datasets for Equity and Environmental Justice: A Data-Centric AI Case Study. IGARSS 2024: 483-487 - [c45]Kaylin M. Bugbee, Rahul Ramachandran, Aaron Kaulfus, Jeanné le Roux, Ge Peng, Deborah K. Smith, Iksha Gurung, Ashish Acharya, Jerika Christman:
Enabling Dynamic Data Governance in Science: Design, Implementation, and Future Directions of the Modern Data Governance Framework. IGARSS 2024: 3720-3723 - [c44]Xihao Xie, Chang Liu, Jia Zhang, Rahul Ramachandran, Tsengdar J. Lee, Seungwon Lee:
RANGER: Context-Aware Service Unit of Work Recommendation for Incremental Scientific Workflow Composition. WISE (3) 2024: 206-222 - [i13]Xihao Xie, Jia Zhang, Rahul Ramachandran, Tsengdar J. Lee, Seungwon Lee:
Learning Service Selection Decision Making Behaviors During Scientific Workflow Development. CoRR abs/2404.00420 (2024) - [i12]Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka, Muthukumaran Ramasubramanian, Takuma Udagawa, Iksha Gurung, Rong Zhang, Bharath Dandala, Rahul Ramachandran, Manil Maskey, Kaylin M. Bugbee, Mike Little, Elizabeth Fancher, Lauren M. Sanders, Sylvain V. Costes, Sergi Blanco-Cuaresma, Kelly E. Lockhart, Thomas Allen, Félix Grèzes, Megan Ansdell, Alberto Accomazzi, Yousef El-Kurdi, Davis Wertheimer, Birgit Pfitzmann, Cesar Berrospi Ramis, Michele Dolfi, Rafael Teixeira de Lima, Panagiotis Vagenas, S. Karthik Mukkavilli, Peter W. J. Staar, Sanaz Vahidinia, Ryan McGranaghan
, Armin Mehrabian, Tsengdar J. Lee:
INDUS: Effective and Efficient Language Models for Scientific Applications. CoRR abs/2405.10725 (2024) - [i11]Aman Gupta, Aditi Sheshadri, Sujit Roy, Vishal Gaur, Manil Maskey, Rahul Ramachandran:
Machine Learning Global Simulation of Nonlocal Gravity Wave Propagation. CoRR abs/2406.14775 (2024) - [i10]Rahul Ramachandran, Tejal Kulkarni, Charchit Sharma, Deepak Vijaykeerthy, Vineeth N. Balasubramanian:
On Evaluation of Vision Datasets and Models using Human Competency Frameworks. CoRR abs/2409.04041 (2024) - [i9]Johannes Schmude, Sujit Roy, Will Trojak, Johannes Jakubik, Daniel Salles Civitarese, Shraddha Singh, Julian Kuehnert, Kumar Ankur, Aman Gupta, Christopher Phillips, Romeo Kienzler, Daniela Szwarcman, Vishal Gaur, Rajat Shinde, Rohit Lal, Arlindo Da Silva, Jorge Luis Guevara Diaz, Anne Jones, Simon Pfreundschuh, Amy Lin, Aditi Sheshadri, Udaysankar Nair, Valentine Anantharaj, Hendrik F. Hamann, Campbell D. Watson, Manil Maskey, Tsengdar J. Lee, Juan Bernabé-Moreno, Rahul Ramachandran:
Prithvi WxC: Foundation Model for Weather and Climate. CoRR abs/2409.13598 (2024) - [i8]Sujit Roy, Talwinder Singh, Marcus Freitag, Johannes Schmude, Rohit Lal, Dinesha Hegde, Soumya Ranjan, Amy Lin, Vishal Gaur, Etienne Eben Vos, Rinki Ghosal, Badri Narayana Patro, Berkay Aydin, Nikolai Pogorelov, Juan Bernabé-Moreno, Manil Maskey, Rahul Ramachandran:
AI Foundation Model for Heliophysics: Applications, Design, and Implementation. CoRR abs/2410.10841 (2024) - [i7]Nishan Pantha, Muthukumaran Ramasubramanian, Iksha Gurung, Manil Maskey, Rahul Ramachandran:
Challenges in Guardrailing Large Language Models for Science. CoRR abs/2411.08181 (2024) - 2023
- [c43]Suresh Marru, Brian Freitag, Dimuthu Wannipurage, Uday Kumar Bommala, Patrick Pradier, Christophe Demange, Nishan Pantha, Tathagata Mukherjee, Betlem Rosich, Eric Monjoux, Rahul Ramachandran:
Blaze: A High-Performance, Scalable, and Efficient Data Transfer Framework with Configurable and Extensible Features : Principles, Implementation, and Evaluation of a Transatlantic Inter-Cloud Data Transfer Case Study. CLOUD 2023: 58-68 - [c42]Lillianne Thomas, Slesa Adhikari, Iksha Gurung, Aaron Kaulfus, Muthukumaran Ramasubramanian, Manil Maskey, Rahul Ramachandran:
Observing Supraglacial Lakes Using Deep Learning and Planetscope Imagery. IGARSS 2023: 32-35 - [c41]Muthukumaran Ramasubramanian, Iksha Gurung, Leo Thomas, Kathryn Berger, Soumya Ranjan, Heidi Mok, Sowmya Subramanian, Vitor George, Manil Maskey, Rahul Ramachandran:
A Framework for Large Scale Semantic Similarity Search on Satellite Imagery. IGARSS 2023: 1404-1407 - [c40]Sujit Roy, Madhu Sridhar, John Mandel, Brian Freitag, Junchang Ju, Rahul Ramachandran:
Generative Framework Approach to Match Landsat and Sentinel-2 Data. IGARSS 2023: 5101-5104 - [i6]S. Karthik Mukkavilli, Daniel Salles Civitarese, Johannes Schmude, Johannes Jakubik, Anne Jones, Nam Nguyen, Christopher Phillips, Sujit Roy, Shraddha Singh, Campbell D. Watson, Raghu K. Ganti, Hendrik F. Hamann, Udaysankar Nair, Rahul Ramachandran, Kommy Weldemariam:
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation. CoRR abs/2309.10808 (2023) - [i5]Johannes Jakubik, Sujit Roy, C. E. Phillips, Paolo Fraccaro, Denys Godwin, Bianca Zadrozny, Daniela Szwarcman, Carlos Gomes, Gabby Nyirjesy, Blair Edwards, Daiki Kimura, Naomi Simumba, Linsong Chu, S. Karthik Mukkavilli, Devyani Lambhate, Kamal Das, Ranjini Bangalore, Dário A. B. Oliveira, Michal Muszynski, Kumar Ankur, Muthukumaran Ramasubramanian, Iksha Gurung, Sam Khallaghi, Hanxi Li, Michael Cecil, Maryam Ahmadi, Fatemeh Kordi, Hamed Alemohammad
Foundation Models for Generalist Geospatial Artificial Intelligence. CoRR abs/2310.18660 (2023) - 2022
- [c39]Xihao Xie, Jia Zhang, Rahul Ramachandran
Learning Context-Aware Service Representation for Service Recommendation in Workflow Composition. ICIS 2022: 60-65 - [c38]Rahul Ramachandran
Language Model for Earth Science: Exploring Potential Downstream Applications as well as Current Challenges. IGARSS 2022: 4015-4018 - [c37]Manil Maskey, Rahul Ramachandran
Artificial Intelligence Vis-à-Vis Data Systems. IGARSS 2022: 5081-5084 - [c36]Kaylin M. Bugbee, Rahul Ramachandran
Selecting Approaches for Enabling Enterprise Data Search: NASA's Science Mission Directorate (SMD) Catalog. IGARSS 2022: 6836-6839 - [c35]Xihao Xie, Jia Zhang, Rahul Ramachandran, Tsengdar J. Lee, Seungwon Lee:
Goal-Driven Context-Aware Service Recommendation for Mashup Development. SNPD 2022: 19-26 - [i4]Xihao Xie, Jia Zhang, Rahul Ramachandran
Learning Context-Aware Service Representation for Service Recommendation in Workflow Composition. CoRR abs/2205.11771 (2022) - [i3]Xihao Xie, Jia Zhang, Rahul Ramachandran
Goal-Driven Context-Aware Next Service Recommendation for Mashup Composition. CoRR abs/2210.14127 (2022) - 2021
- [c34]Rahul Ramachandran
Augmenting Data Systems with Prediction based Embeddings. IGARSS 2021: 1138-1141 - [c33]Jia Zhang
Graph Convolutional Network-Strengthened Topic Modeling for Scientific Papers. SMDS 2021: 24-32 - 2020
- [j23]Manil Maskey
Deepti: Deep-Learning-Based Tropical Cyclone Intensity Estimation System. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 4271-4281 (2020) - [c32]Manil Maskey, Rahul Ramachandran
Employing Deep Learning to Enable Visual Exploration of Earth Science Events. IGARSS 2020: 2248-2251 - [c31]Katrina Virts, Ashlyn Shirey, George Priftis, Kumar Ankur, Muthukumaran Ramasubramanian, Hassan Muhammad, Ashish Acharya, Rahul Ramachandran
A Quantitative Analysis on the Use of Supervised Machine Learning in Earth Science. IGARSS 2020: 2252-2255 - [c30]Kaylin M. Bugbee, Rahul Ramachandran
Advancing Open Science Through Innovative Data System Solutions: The Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)'s Data Ecosystem. IGARSS 2020: 3097-3100 - [c29]Kaylin M. Bugbee, Aaron Kaulfus, Alyssa Harris, Sean Bailey, Rahul Ramachandran
Standardized Algorithm Documentation for Improved Scientific Data Understanding: The Algorithm Publication Tool Prototype. IGARSS 2020: 3131-3134 - [i2]Rahul Ramachandran
Machine learning model to cluster and map tribocorrosion regimes in feature space. CoRR abs/2006.06252 (2020) - [i1]Rahul Ramachandran
Using neural networks to predict icephobic performance. CoRR abs/2008.00966 (2020)
2010 – 2019
- 2019
- [j22]Iksha Gurung
Deep feature extraction and its application for hailstorm detection in a large collection of radar images. Signal Image Video Process. 13(3): 541-549 (2019) - [j21]Melinda Pullman
Applying Deep Learning to Hail Detection: A Case Study. IEEE Trans. Geosci. Remote. Sens. 57(12): 10218-10225 (2019) - [c28]Kaylin M. Bugbee, Christopher Lynnes, Manil Maskey
Building a Data Ecosystem: A New Data Stewardship Paradigm for the Multi-Mission Algorithm and Analysis Platform (MAAP). IGARSS 2019: 4261-4264 - [c27]Kaylin M. Bugbee, Robert Griffin, Brian Freitag, Jeffrey J. Miller, Rahul Ramachandran
Alternative Datasets for Identification of Earth Science Events and Data. IGARSS 2019: 9510-9513 - [c26]Manil Maskey
Machine Learning Lifecycle for Earth Science Application: A Practical Insight into Production Deployment. IGARSS 2019: 10043-10046 - 2018
- [j20]Rahul Ramachandran
Recommendations to Improve Downloads of Large Earth Observation Data. Data Sci. J. 17: 2 (2018) - [j19]Kaylin M. Bugbee
The art and science of data curation: Lessons learned from constructing a virtual collection. Comput. Geosci. 112: 76-82 (2018) - [j18]Jeffrey J. Miller
Detection of transverse cirrus bands in satellite imagery using deep learning. Comput. Geosci. 118: 79-85 (2018) - [j17]Fangzhou Sun
Biomass feedstock supply chain design - a taxonomic review and a decomposition-based methodology. Int. J. Prod. Res. 56(17): 5626-5659 (2018) - [j16]Ritesh Pradhan
Tropical Cyclone Intensity Estimation Using a Deep Convolutional Neural Network. IEEE Trans. Image Process. 27(2): 692-702 (2018) - [c25]Jia Zhang
Facilitating Data-Centric Recommendation in Knowledge Graph. CIC 2018: 207-216 - [c24]Xiaoyi Duan, Jia Zhang
A Neural Network-Powered Cognitive Method of Identifying Semantic Entities in Earth Science Papers. ICCC 2018: 9-16 - [c23]Christopher Lynnes
Generalizing a Data Analysis Pipeline in the Cloud to Handle Diverse Use Cases in NASA's EOSDIS. IGARSS 2018: 422-425 - [c22]Manil Maskey, Rahul Ramachandran
Earth Science Deep Learning: Applications and Lessons Learned. IGARSS 2018: 1760-1763 - [c21]Clement Albinet, Amanda S. Whitehurst, Henri Laur, Kevin J. Murphy, Bjorn Frommknecht, Klaus Scipal, Andrew E. Mitchell, Benhan Jai, Rahul Ramachandran
ESA-NASA Multi-Mission Analysis Platform for Improving Global Aboveground Terrestrial Carbon Dynamics. IGARSS 2018: 5282-5284 - 2017
- [j15]Manil Maskey
A relevancy algorithm for curating earth science data around phenomenon. Comput. Geosci. 106: 164-170 (2017) - [c20]Xiaoyi Duan, Jia Zhang, Qihao Bao, Rahul Ramachandran
Linking Design-Time and Run-Time: A Graph-Based Uniform Workflow Provenance Model. ICWS 2017: 97-105 - [c19]Qihao Bao, Jia Zhang, Xiaoyi Duan, Rahul Ramachandran
A Fine-Grained API Link Prediction Approach Supporting Mashup Recommendation. ICWS 2017: 220-228 - [c18]Rahul Ramachandran
CUMULUS: NASA's cloud based distributed active archive center prototype. IGARSS 2017: 369-372 - 2016
- [j14]Rahul Ramachandran, Marina Kozhukhova
Anti-Icing Superhydrophobic Surfaces: Controlling Entropic Molecular Interactions to Design Novel Icephobic Concrete. Entropy 18(4): 132 (2016) - [j13]Rahul Ramachandran
Climate data initiative: A geocuration effort to support climate resilience. Comput. Geosci. 88: 22-29 (2016) - [c17]Rahul Ramachandran
Exploiting dark information resources to create new value added services to study Earth science phenomena. IGARSS 2016: 182-185 - [c16]Kwo-Sen Kuo, Kush Shrestha, Amy Lin, Rahul Ramachandran
Snowstorm climatology derived from NASA MERRA reanalysis as an example for event-based virtual collections. IGARSS 2016: 2177-2180 - 2015
- [j12]Michael Nosonovsky
Geometric Interpretation of Surface Tension Equilibrium in Superhydrophobic Systems. Entropy 17(7): 4684-4700 (2015) - [j11]Peng Yue, Rahul Ramachandran
Editorial: intelligent GIServices. Earth Sci. Informatics 8(3): 461-462 (2015) - [c15]Curt Tilmes, Ana Pinheiro Privette, Jeffrey Chen, Rahul Ramachandran
Linking from observations to data to actionable science in the climate data initiative. IGARSS 2015: 1354-1357 - [p1]Rahul Ramachandran
Use of Semantic Technology to Create Curated Data Albums. Semantic Web Enabled Software Engineering 2015: 107-125 - 2013
- [j10]Rahul Ramachandran
Data Prospecting-A Step Towards Data Intensive Science. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 6(3): 1233-1241 (2013) - [j9]Helen Conover, Rahul Ramachandran
Introducing Provenance Capture into a Legacy Data System. IEEE Trans. Geosci. Remote. Sens. 51(11): 5098-5104 (2013) - 2012
- [j8]Rahul Ramachandran
Talkoot: software tool to create collaboratories for earth science. Earth Sci. Informatics 5(1): 33-41 (2012) - [j7]Kwo-Sen Kuo, Christopher Lynnes, Rahul Ramachandran
A Proposed Earth Science Collaboratory for Remote Sensing Data Analysis. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 5(6): 1612-1616 (2012) - [c14]Sara J. Graves, Rahul Ramachandran
Using GLIDER for Knowledge Discovery in Climate Science to Visualize, Analyze and Mine Satellite Imagery. SC Companion 2012: 488-494
2000 – 2009
- 2009
- [c13]Rahul Ramachandran
Talkoot Software Appliance for Collaborative Science. IGARSS (5) 2009: 378-381 - [c12]Rahul Ramachandran
GLIDER: A Comprehensive Software Tool to Visualize, Analyze and Mine Satellite Imagery. IGARSS (3) 2009: 781-784 - 2008
- [j6]Xiang Li, Beth Plale
Real-time storm detection and weather forecast activation through data mining and events processing. Earth Sci. Informatics 1(2): 49-57 (2008) - [c11]Sara J. Graves, Rahul Ramachandran
Mining Scientific Data using the Internet as the Computer. IGARSS (4) 2008: 283-286 - [c10]Bradley Zavodsky, Steven Lazarus
Intelligent Data Thinning Algorithms for Satellite Imagery. IGARSS (3) 2008: 644-647 - [c9]Sunil Movva, Rahul Ramachandran
Customizable Search Engine with Semantic and Resource Aggregation Capability. CEC/EEE 2008: 376-381 - 2006
- [c8]Rahul Ramachandran
A Simple and Efficient Feature Extraction Algorithm for Geophysical Phenomena. IGARSS 2006: 5-8 - [c7]Nithya N. Vijayakumar, Beth Plale
Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting. IGARSS 2006: 2449-2452 - 2005
- [j5]Kelvin Droegemeier
Service-oriented environments for dynamically interacting with mesoscale weather. Comput. Sci. Eng. 7(6): 12-29 (2005) - [j4]John A. Rushing, Rahul Ramachandran
ADaM: a data mining toolkit for scientists and engineers. Comput. Geosci. 31(5): 607-618 (2005) - [j3]Hassan A. Babaie, Rahul Ramachandran
Application of XML in the geosciences. Comput. Geosci. 31(9): 1079-1080 (2005) - [j2]Sunil Movva, Rahul Ramachandran
Syntactic and semantic metadata integration for science data use. Comput. Geosci. 31(9): 1126-1134 (2005) - [c6]Xiang Li, Rahul Ramachandran
Automated detection of frontal systems from numerical model-generated data. KDD 2005: 782-787 - 2004
- [j1]Rahul Ramachandran
Earth Science Markup Language (ESML): : a solution for scientific data-application interoperability problem. Comput. Geosci. 30(1): 117-124 (2004) - [c5]Rahul Ramachandran, Sara J. Graves, Sunil Movva, Xiang Li:
Agent framework for intelligent data processing. IGARSS 2004: 51 - [c4]Xiang Li, Rahul Ramachandran, Sunil Movva, Sara J. Graves, Glynn A. Germany, Wladislaw Lyatsky, Arjun Tan:
Dayglow removal from FUV auroral images. IGARSS 2004: 3774-3777 - [c3]Xiang Li, Rahul Ramachandran
Comparing Different Thresholding Algorithms for Segmenting Auroras. ITCC (2) 2004: 594-601 - 2002
- [c2]Rahul Ramachandran, Helen Conover, Sara J. Graves, Ken Keiser:
Interchange technology for applications to facilitate generic access to heterogenous data formats. IGARSS 2002: 266-268 - 2000
- [c1]Rahul Ramachandran, Helen Conover, Sara J. Graves, Ken Keiser:
Challenges and solutions to mining Earth science data. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2000: 259-264
Coauthor Index
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