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Ari Gesher

Ari Gesher
Engineering Ambassador, Palantir Technologies

Website | @alephbass

Ari Gesher is a senior software engineer and engineering ambassador at Palantir Technologies. He is co-author of the upcoming book Architecture of Privacy, about building data systems that responsibly handle sensitive data. Ari can often be found speaking on the topic of privacy protections, big data, and the limits of automated decision making.

At Palantir Technologies, Ari has split his time between working as a design prototyper for the user interface team, a backend engineer on Palantir’s analysis platform, thinking and writing about Palantir’s vision for human-driven information data systems, and moonlighting on both Palantir’s Privacy and Civil Liberties team and Philanthropic engineering team. His current role involves understanding and discussing Palantir’s role in the world of analytics, big data, the future of technology, and its impact on the world.

An alumnus of the University of Illinois computer science department, Ari has worked in the software industry for the past 15 years, including a stint as the lead engineer for the open source software archive.


Ari Gesher (Palantir Technologies)
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Statistical methods tends to fail when there is someone on the other side of a problem actively evading detection. Here we look at three systems successfully used to fight adaptive adversaries engaged in fraud and cyber attacks. Using a combination of big data techniques and interactive human analysis, these systems are protecting commercial banks, pharmaceutical companies, and governments. Read more.
Moderated by:
Jim Stogdill (O'Reilly Media, Inc.)
Brian Behlendorf (The Hyperledger Project at the Linux Foundation), Adrian Cockcroft (AWS), Ari Gesher (Palantir Technologies), Kimberly Stedman (Freelance)
The always-popular Great Debate series returns to Strata. In this Oxford-style debate, two opposing teams take opposing positions. We poll the audience, and the teams try to sway opinions. It’ll be a fast-paced, sometimes irreverent look at some of the core challenges of putting data to work. Read more.