Dawn Song

Professor

Division of Computer Science (EECS)

Faculty URL

http://www.cs.berkeley.edu/~dawnsong/

Contact

dawnsong@cs.berkeley.edu

(510) 642-8282

(510) 642-5615

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Research Expertise and Interest

privacy, computer security, artificial intelligence

Research Description

Deep learning, security, and blockchain. Deep learning and program synthesis and analysis. Secure deep learning and artificial intelligence. Blockchain and decentralized systems. Computer security, privacy, and applied cryptography, including security and privacy issues in systems, software, networking, and databases. Using program analysis, algorithms design, and machine learning for security and privacy.

In the News

Dawn Song standing with window reflections in background

A New Vision for Data Security

Dawn Song, a 2022 Fellow with the UC Noyce Initiative, studies how to keep online data safe, fair and accessible.

Stock image of ones and zeros with a lock shape highlighted

UC Berkeley Joins NSF-Backed AI Institute for Cybersecurity

Five UC Berkeley faculty members will join the AI Institute for Agent-based Cyber Threat Intelligence and Operation (ACTION).

Dawn Song and David Wagner Win ACM CCS Test-of-Time Award

Computer Science Profs. Dawn Song and David Wagner have won the Association for Computing Machinery (ACM) Special Interest Group on Security, Audit and Control (SIGSAC) Test-of-Time Award.

Crypto industry leaders, scholars, government and consumer groups collaborated on blockchain policy and regulations at a summit last week hosted by Berkeley’s Center for Responsible, Decentralized Intelligence and the California Department of Financial Protection and Innovation.

Berkeley Web3 and Crypto Summit Tackles Financial Inclusion, Climate Issue

How do we incentivize the use of climate-friendly blockchains? Should lawmakers play a key role in creating opportunities for underserved communities via crypto assets and Web3? And what can the crypto asset industry do to ensure wealth-building opportunities are accessible to historically excluded communities?

Security for data analytics – gaining a grip on the two-edged sword

In the world of data analytics, privacy restrictions can get in the way of analysis. It’s a classic two-edged sword, and finding a flexible but secure solution to assure both privacy and deep data access has been difficult to achieve.

Security for Data Analytics - Gaining a Grip on the Two-Edged Sword

In the information age, data is power, and the ability to mine it can boost business profits, save patients’ lives and aid government security.

Two young faculty members named MacArthur 'genius' fellows

Two UC Berkeley faculty members, economist Emmanuel Saez and computer scientist Dawn Song, have been named MacArthur "genius" Fellows. They are among 23 recipients to receive the prestigious award – $500,000 in unrestricted funds over the next five years – announced Sept. 28 by the John D. and Catherine T. MacArthur Foundation.

Five professors win Guggenheims

Five Berkeley professors have been named 2010 Guggenheim fellows, an award conferred for "achievement and exceptional promise."

Featured in the Media

Please note: The views and opinions expressed in these articles are those of the authors and do not necessarily reflect the official policy or positions of UC Berkeley.

October 16, 2019

WIRED25: Stories of People Who Are Racing to Save Us

WIRED

Electrical engineering and computer sciences professor Dawn Song and information and electrical engineering and computer sciences professor Hany Farid are honored in this WIRED list of 25 people who are working to solve some of humanity's most challenging problems. Professor Song is exploring ways to help people protect their privacy and control and profit from their data. "I think most people don't even know that their data can be valuable,' she says. Professor Farid's profile indicates that he's "one of the leading authorities on detecting fake photos." He says: "This used to be a boutique little field, but now we're defending democracy. ... What happens when more than half the content you see and hear online is fake?"

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