Analysis,
Data Science

Sara Abdulla

Data Research Analyst Print Bio

Sara Abdulla is a Data Research Analyst at Georgetown’s Center for Security and Emerging Technology (CSET). Previously, she worked as a research assistant for the CDC supporting enteric disease health surveillance. Additionally, she has written about the ethical implications of neurotechnology on the criminal justice system and on far-right men’s movements. Sara earned a B.S. in Neuroscience with a minor in Philosophy from Georgia State University in Atlanta.

Biosafety Level-3 laboratories (BSL-3) are an essential part of research infrastructure and are used to develop vaccines and therapies. The research conducted in them provides insights into host-pathogen interactions that may help prevent future pandemics. However, these facilities also potentially pose a risk to society through lab accidents or misuse. Despite their importance, there is no comprehensive list of BSL-3 facilities, or the institutions in which they are housed. By systematically assessing PubMed articles published in English from 2006-2021, this paper maps institutions that host BSL-3 labs by their locations, augmenting current knowledge of where high-containment research is conducted globally.

CSET’s CAT presents data related to countries' artificial intelligence ecosystems to give an overview of domestic capabilities, as well as insights on competitiveness and collaboration globally. It presents metrics on AI research, patents, and investment-related activities for AI overall and its various subfields.

Quad AI

May 2022

Through the Quad forum, the United States, Australia, Japan and India have committed to pursuing an open, accessible and secure technology ecosystem and offering a democratic alternative to China’s techno-authoritarian model. This report assesses artificial intelligence collaboration across the Quad and finds that while Australia, Japan and India each have close AI-related research and investment ties to both the United States and China, they collaborate far less with one another.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the fifth in a series of Snapshots exploring CSET’s Private-sector AI-Related Activity Tracker (PARAT). Check in every two weeks to see our newest Snapshot, and explore PARAT, which collects data related to companies’ AI research and development to inform analysis of the global AI sector.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the fourth in a series of Snapshots exploring CSET’s Private-sector AI-Related Activity Tracker (PARAT). Check in every two weeks to see our newest Snapshot, and explore PARAT, which collects data related to companies’ AI research and development to inform analysis of the global AI sector.

Exploring CSET’s PARAT

February 2022

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the first in a series of Snapshots exploring CSET’s Private-sector AI-Related Activity Tracker (PARAT). Check in every two weeks to see our newest Snapshot, and explore PARAT, which collects data related to companies’ AI research and development to inform analysis of the global AI sector.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Our first series of Snapshots introduced CSET’s Map of Science and explored the underlying data and analytic utility of this new tool, which enables users to interact with the Map directly.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Our first series of Snapshots introduced CSET’s Map of Science and explored the underlying data and analytic utility of this new tool, which enables users to interact with the Map directly.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Our first series of Snapshots introduced CSET’s Map of Science and explored the underlying data and analytic utility of this new tool, which enables users to interact with the Map directly.

Advances in robotics technology are having a transformative effect on how people work, travel, communicate, and fight wars. This data brief provides an overview of global trends in robotics patents between 2005 and 2019, focusing in particular on the state of robotics patenting in Russia, as well as developments in military robotics patents both in Russia and across the globe.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Our first series of Snapshots introduced CSET’s Map of Science and explored the underlying data and analytic utility of this new tool, which enables users to interact with the Map directly.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Our first series of Snapshots introduced CSET’s Map of Science and explored the underlying data and analytic utility of this new tool, which enables users to interact with the Map directly.

Since 2011, China has dramatically grown its robotics sector as part of its mission to achieve technological leadership. The Chinese government has encouraged this growth through incentives and, in some cases, subsidies. Patents in robotics have surged, particularly at Chinese universities; by contrast, private companies comprise the bulk of robotics patent filers around the world. China has also seen a corresponding growth in robotics purchasing and active robotics stock. This data brief explores the trends in robotics patent families published from China as a measure of robotics advancement and finds that China is on track to emerge as a world leader in robotics.

With its massive information technology workforce, thriving research community and a growing technology ecosystem, India has a significant stake in the development of artificial intelligence globally. Drawing from a variety of original CSET datasets, the authors evaluate India’s potential for AI by examining its progress across five categories of indicators pertinent to AI development: talent, research, patents, companies and investments, and compute.