HelioWebAnirudh Prabhu
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A[Anirudh Prabhu]
AC["Associated Concepts (16)"]
AW["Authored Works (37)"]
CA["Linked Co-Authors (7)"]
CI["Linked Collaborating Institutions (46)"]
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click AW "#authored-works"
click CA "#co-authors"
click CI "#collaborating-institutions"
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- ORCiD
- https://orcid.org/0000-0002-9921-6084
- OpenAlex ID
- https://openalex.org/A5061829882 (API record)
Associated Concepts [?]
- Computer science
- Biology
- Geology
- Physics
- Chemistry
- Engineering
- Materials science
- Organic chemistry
- Metallurgy
- Geography
- Ecology
- Mathematics
- Astronomy
- Paleontology
- Operating system
- Geochemistry
Authored Works
sorted by decreasing year, and then by display-name
- The creation of a multivariable data set for use in machine learning classification of ungrouped chondritic meteorites
- The Evolution of the Igneous Minerals: A Mineral Informatics Approach
- Semantics of space, time, and mineralogy in the OpenMindat data portal
- Exploring martian geology and habitability via mineral network analysis
- Exploring Olivine in Astromaterials: Classification of Chondritic Components based on Major/Minor Oxides and Oxygen Isotopes.
- Can we use network science to identify planetary biosignatures?
- Mineral network analysis: A multidimensional approach to exploring geological, geochemical, and biological patterns in mineralization
- Mineral Informatics: Analysis and Visualization of Minerals through Time and Space
- Machine learning applications to metal-silicate equilibria and their insights into core formation
- A new way to evaluate association rule mining methods and its applicability to mineral association analysis
- Insights from Knowledge Graphs : Introducing a new formalism
- Affinity analysis of mineral co-occurrence: Predicting unknown mineral occurrences with machine learning
- A machine learning geobarometer for diamond-hosted majoritic garnet inclusions
- Tracking the evolution of our planet using large scale geochemistry and metagenomic data
- Predicting unknown mineral localities based on mineral associations
- Natural kind clustering of presolar silicon carbides and its astrophysical implications
- Natural clustering of pyrite with implications for its formational environment
- Interactive, Web-based Visualizations for Hierarchical Information and Knowledge in Geosciences: An Implementation on the Dana Classification and its Applications
- Exploring carbon mineralogy and mineral evolution through deep time with advanced analytics and visualization
- Exploration of artificial intelligence approaches to Earth observing remote sensing
- Data-driven discovery in mineralogy: Insights from natural kind clustering
- Creating, Managing and Evaluating Data Legacies : Updates on the Global Earth Mineral Inventory.
- Abiotic hydrocarbon formation in serpentinization experiments: network analysis on a comprehensive dataset
- The Census of Deep Life: Metadata Then and Now
- Predicting Multi-Component Mineral Compositions in Gale crater, Mars with Label Distribution Learning
- Network analysis on the correlation of geochemical and biological signatures from Cerro Negro volcano, Nicaragua
- Global Earth Mineral Inventory : A DCO Data Legacy
- Biological Utilization of Cobalt from the Geosphere, and the expanding network of microbial metabolisms in the Archean eon
- Visualizing Complex Environments in the Geo- and BioSciences
- Thermodynamic Data Rescue and Informatics for Deep Carbon Science
- The Importance of Transition Metals in the Expanding Network of Microbial Metabolism in the Archean Eon
- Heterogeniety and Heterarchy: How far can network analyses in Earth and space sciences?
- Data-driven exploration of copper mineralogy and its application to Earth's near-surface oxidation
- The Private Lives of Minerals: Social Network Analysis Applied to Mineralogy and Petrology
- Exploiting mineral data: applications to the diversity, distribution, and social networks of copper mineral
- Deep Time Data Infrastructure: Integrating Our Current Geologic and Biologic Databases
- A Rules-Based Service for Suggesting Visualizations to Analyze Earth Science Phenomena.
Linked Co-Authors
Linked Collaborating Institutions
- Carnegie Institution of Washington
- Carnegie Institution of Washington, Department of Terrestrial Magnetism
- Carnegie Institution of Washington, Geophysical Laboratory
- Columbia University, New York
- Flatiron Institute, New York
- George Mason University, Virginia
- Harvard University, Massachusetts
- IBM New York
- Jet Propulsion Laboratory
- Lunar and Planetary Institute, Houston
- NASA Ames Research Center
- NASA Goddard Space Flight Center, Maryland
- NASA Johnson Space Center
- NASA Marshall Space Flight Center
- New York University Polytechnic Institute
- Oregon State University, Corvallis, College of Oceanic and Atmospheric Sciences
- Pennsylvania State University
- Planetary Science Institute, Arizona
- Purdue University, Indiana
- Rensselaer Polytechnic Institute, New York
- Rutgers University, New Jersey
- SETI Institute, California
- Saint Petersburg State University, Russia
- Southern Illinois University
- U.S. Geological Survey
- Universite Lyon I Claude Bernard
- University College London, Department of Earth Sciences
- University of Alabama, Huntsville
- University of Arizona
- University of Arizona, Department of Geosciences
- University of Calgary, Canada
- University of California, San Francisco
- University of Colorado, Boulder
- University of Hawaii, Manoa
- University of Idaho
- University of Maryland, College Park
- University of Naples Federico II, Italy
- University of Nevada, Las Vegas
- University of North Carolina, Chapel Hill
- University of Notre Dame, Indiana
- University of Tasmania, Australia
- University of Tennessee
- University of Toronto, Canada
- University of Utah
- University of Wyoming, Department of Geology and Geophysics
- Western Washington University
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