Girl Geek X

Girl Geek X

Bay Area Girl Geek Dinner #156: Sponsored by Stripe

Stripe Girl Geek Dinner

Join Bay Area Girl Geek Dinners at Stripe for a night of “Adversarial Engineering” on Tuesday, December 12th, 2017! Hear from three Stripe engineers on various topics centered around security and machine learning. Join us at 6pm for snacks, drinks, and networking. Talks will start promptly at 6:45pm.

Stripe Girl Geek Dinner Agenda:

6:00pm – 6:45pm – Check-in, Snacks, Mingling!
6:45pm – 7:30pm – Adversarial Engineering Talks – Followed By Q&A
7:30pm – 8:00pm – More Mingling!

Please Follow Us:

Twitter: @Stripe @BayAreaGGD
Event Hashtag: #StripeGirlGeekDinner

Stripe Girl Geek Speaker Bios:

Alyssa Frazee (Machine Learning Engineer, Stripe)

Alyssa Frazee

Alyssa Frazee is a machine learning engineer at Stripe, where she builds models to stop fraud. Before Stripe, she did a PhD in biostatistics and fell in love with programming at the Recurse Center. Follow her on Twitter at @acfrazee.

Talk Topic: “Explaining Decisions From Black-Box Models” by Alyssa Frazee
Machine learning models are often described as “magic” or “black boxes”: the important thing is what goes into them and what comes out, not necessarily how that output is calculated. Sometimes this is what we want: many consumers don’t really need to see inside the sausage factory, as they say—they just want a tasty tubular treat. But other times, a prediction from a box full of magic isn’t satisfying. In Stripe’s production machine learning system that declines high-risk credit card charges, businesses and customers often (rightly) want to know why our decline system made the decision it did. This talk will illustrate how we give reasons for our system’s risk judgments on payments.

Fay Wu (Software Engineer, Stripe)

Fay Wu

Fay Wu is a software engineer at Stripe, helping businesses fight fraud in online payments with Radar. She loves languages and rolled ice cream. Follow her on Twitter at @mfaywu.

Talk Topic: “Building A Simple DSL With Parslet” by Fay Wu
Learn how Stripe’s fraud detection tool evaluates rules to determine the outcome of transactions and build a simple domain-specific language using Parslet, a small Ruby library for constructing PEGs (Parsing Expression Grammars)!

Pamela Vagata (Software Engineer, Stripe)

Pamela Vagata

Pamela Vagata is a software engineer at Stripe working on AI. Prior to joining Stripe she has worked on AI and big data infrastructure at Facebook. She loves dancing and her two silly dogs. Follow her on Twitter at @pam_vagata.

Talk Topic: “Learning Representations Of Merchants” by Pamela Vagata
Come learn how we apply NLP techniques to discover structure in non-textual data and learn vector representations for Stripe’s merchants.

About Stripe:

Stripe is a software platform for starting and running internet businesses. Hundreds of thousands of businesses—from startups to Fortune 500 companies—rely on Stripe’s software tools to accept payments, expand globally, and create new revenue streams. Stripe has been at the forefront of expanding internet commerce, powering new business models, and supporting the latest platforms, from marketplaces to mobile commerce sites. Stripe users include Lyft, Kickstarter, Salesforce, Shopify, Facebook, Slack, UNICEF and many more.

At Stripe, we believe that growing the GDP of the internet is a problem rooted in code and design, not finance. Stripe is built for developers, makers, and creators. We work on solving the hard technical problems necessary to build global economic infrastructure—from designing highly reliable global systems to developing advanced machine learning algorithms to prevent fraud. Learn more at

Event Tickets & Details:

Tickets on sale starting at 12:00pm PST on Monday, November 20th, 2017 at Eventbrite!