Data Science

Rebecca Gelles

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Rebecca Gelles is a Data Scientist at Georgetown’s Center for Security and Emerging Technology. Previously, she spent almost seven years at the National Security Agency, where she graduated from the Director’s Summer Program (DSP) and the Cryptanalytic Computer Network Operations Development Program (C2DP) and worked on topics ranging from cryptography to data science to natural language processing to high performance computing. Rebecca holds a B.A. in Computer Science and Linguistics from Carleton College and an M.S. in Computer Science from University of Maryland College Park, where her research focused on how the media influences users’ computer security postures and on new techniques for defending IoT devices from cyber attacks.

Related Content

Artificial intelligence models have become increasingly adept at generating computer code. They are powerful and promising tools for software development across many industries, but they can also pose direct and indirect cybersecurity risks. This report… Read More

Ngor Luong and Zachary Arnold provided their expert insights in an article published by Nature that discusses new data from PARAT, the Private-sector AI-Related Activity Tracker. Read More

CSET submitted the following comment in response to a Request for Information (RFI) from the Department of Commerce regarding 89 FR 27411. Read More

The National Artificial Intelligence Research Resource (NAIRR) pilot provides federal infrastructure, including computational resources, to U.S. AI researchers. This blog post estimates the compute provided through the pilot’s initial six resources. We find that the… Read More

Translation

한국 AI 생태계 분석

August 2023

This is a Korean translation of the August 2023 CSET Data Brief "Assessing South Korea's AI Ecosystem."… Read More

This data brief examines South Korea’s progress in its development of artificial intelligence. The authors find that the country excels in semiconductor manufacturing, is a global leader in the production of AI patents, and is… Read More

This data brief uses procurement records published by the U.S. Department of Defense and China’s People’s Liberation Army between April and November of 2020 to assess, and, where appropriate, compare what each military is buying… Read More

Data Brief

“The Main Resource is the Human”

April 2023

Progress in artificial intelligence (AI) depends on talented researchers, well-designed algorithms, quality datasets, and powerful hardware. The relative importance of these factors is often debated, with many recent “notable” models requiring massive expenditures of advanced… Read More

Data Brief

Measuring AI Development

December 2021

By combining a versatile and frequently updated bibliometrics tool — the CSET Map of Science — with more hands-on analyses of technical developments, this brief outlines a methodology for measuring the publication growth of AI-related… Read More

Militaries around the world have often relied on the largest global defense companies to acquire and integrate cutting-edge technologies. This issue brief examines the investment and mergers and acquisition activities in artificial intelligence of the… Read More

CSET’s Private-sector AI-Related Activity Tracker (PARAT) collects data related to companies’ AI research and development to inform analysis of the global AI sector. The global AI market is already expanding rapidly and is likely to… Read More

Analysis

Contending Frames

May 2021

The narrative of an artificial intelligence “arms race” among the great powers has become shorthand to describe evolving dynamics in the field. Narratives about AI matter because they reflect and shape public perceptions of the… Read More

Leading U.S. companies are investing in the broad research field of artificial intelligence (AI), but where, specifically, are they making these investments? This data brief provides an analysis of the research papers published by Amazon,… Read More

Foreign investors comprise a significant portion of investors in top U.S. AI startups, with China as the leading location. The authors analyze investment data in the U.S. AI startup ecosystem both domestically and abroad, outlining… Read More

Corporate investors are a significant player in the U.S. AI startup ecosystem, funding 71 percent of top U.S. AI startups. The authors analyze the trends in top corporate funders and the startups receiving corporate money. Read More

Based on news coverage alone, it can seem as if corporations dominate the research on artificial intelligence and machine learning when compared to the work of universities and academia. Authors Simon Rodriguez, Tim Hwang and… Read More

Are great powers engaged in an artificial intelligence arms race? This issue brief explores the rhetorical framing of AI by analyzing more than 4,000 English-language articles over a seven-year period. Among its findings: a growing… Read More

Data Brief

Identifying AI-Related Companies

July 2020

Artificial intelligence is of increasing interest to the private sector, but what exactly constitutes an “AI company?” This data brief offers a flexible, data-driven framework for identifying the companies most relevant in this field at… Read More