activity
20202026
most citedGoogle COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description (version 1.0)

16 citations · 30 across the 9 of their papers we have counts for

collaborators

11 papers

cs.AI2026

Google Earth AI Geospatial Reasoning Agent: Capabilities and a Systematic Evaluation

Noam Slonim, Aviv Slobodkin, Gil Fidel +34

Google Earth AI is a family of geospatial AI models, together with an agent that orchestrates them. We present this agent, Google Earth AI's Geospatial Reasoning agent (GRA), a Gem…

cs.LG2026

Planetary Geospatial Foundation Models: A New Paradigm for Global Public Health

Arbaaz Muslim, Aviv Slobodkin, Katherine Wheeler-Martin +35

The efficacy of traditional disease prediction is limited by spatial gaps and temporal lags, which impact the timing and targets of resource deployments. Outbreaks escalate undetec…

cs.AI2026

Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embeddings

Evelyn Ma, Rama Kumar Pasumarthi, Kishwar Shafin +26

Addressing critical global challenges, from food security and disaster risk to disease outbreaks and socio-economic vulnerability, demands high-fidelity geospatial modeling. Howeve…

cs.LG2025

Application and Validation of Geospatial Foundation Model Data for the Prediction of Health Facility Programmatic Outputs -- A Case Study in Malawi

Lynn Metz, Rachel Haggard, Michael Moszczynski +14

The reliability of routine health data in low and middle-income countries (LMICs) is often constrained by reporting delays and incomplete coverage, necessitating the exploration of…

cs.AI2025★ 3 cited

Earth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning

Aaron Bell, Amit Aides, Amr Helmy +57

Geospatial data offers immense potential for understanding our planet. However, the sheer volume and diversity of this data along with its varied resolutions, timescales, and spars…

cs.LG2024★ 3 cited

General Geospatial Inference with a Population Dynamics Foundation Model

Mohit Agarwal, Mimi Sun, Chaitanya Kamath +31

Supporting the health and well-being of dynamic populations around the world requires governmental agencies, organizations and researchers to understand and reason over complex rel…

cs.LG2024

Community search signatures as foundation features for human-centered geospatial modeling

Mimi Sun, Chaitanya Kamath, Mohit Agarwal +7

Aggregated relative search frequencies offer a unique composite signal reflecting people's habits, concerns, interests, intents, and general information needs, which are not found…

cs.IR2022

Dense Feature Memory Augmented Transformers for COVID-19 Vaccination Search Classification

Jai Gupta, Yi Tay, Chaitanya Kamath +5

With the devastating outbreak of COVID-19, vaccines are one of the crucial lines of defense against mass infection in this global pandemic. Given the protection they provide, vacci…

cs.SI2021

Vaccine Search Patterns Provide Insights into Vaccination Intent

Sean Malahy, Mimi Sun, Keith Spangler +20

Despite ample supply of COVID-19 vaccines, the proportion of fully vaccinated individuals remains suboptimal across much of the US. Rapid vaccination of additional people will prev…

cs.CR2021★ 8 cited

Google COVID-19 Vaccination Search Insights: Anonymization Process Description

Shailesh Bavadekar, Adam Boulanger, John Davis +22

This report describes the aggregation and anonymization process applied to the COVID-19 Vaccination Search Insights (published at http://goo.gle/covid19vaccinationinsights), a publ…

cs.CR2020★ 16 cited

Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description (version 1.0)

Shailesh Bavadekar, Andrew Dai, John Davis +27

This report describes the aggregation and anonymization process applied to the initial version of COVID-19 Search Trends symptoms dataset (published at https://goo.gle/covid19sympt…