DataVisor Tech Talk: Unsupervised Machine Learning at Scale

Information Session | October 7 | 6:30-8 p.m. | Soda Hall, Wozniak Lounge (430)

 Electrical Engineering and Computer Sciences (EECS)

As the world transforms to digital, all forms of every day activities are open to fraud attacks. In this talk, we will explain how DataVisor is able to pioneer Unsupervised Machine Learning and Big Data computational techniques at scale to save companies millions a year and keep their communities safe. With its patented algorithm and an intelligence network of more than 4B user accounts globally, DataVisor protects businesses against financial and reputational damage caused by fake user accounts and account takeovers, promotional abuse and scams, and fraudulent transactions.

Come listen to this talk so you can learn how real world advanced fraud attacks are identified and how advanced AI technologies can detect these attacks automatically without training or labels.

About the Speaker:
Fang Yu is the cofounder and CTO of DataVisor, where her work focuses on big data for security. Previously, she was at Microsoft Research Silicon Valley, where she developed new technologies and systems to help various Microsoft internal teams such as Hotmail, Bing, Xbox etc. Over the past 10 years, Fang has developed algorithms and built systems for identifying various kinds of malicious traffic including worms, spam, bot queries, faked and hijacked account activities, and fraudulent financial transactions. Fang received her PhD degree from the University of California, Berkeley and holds over 20 patents.

Learn more and apply at:
https://www.datavisor.com/about/careers/

Dinner will be provided!

 xrg@eecs.berkeley.edu