Coding an app for multiple platforms has never been easier thanks to cross-platform toolkits like Flutter. Similarly, thanks to backend-as-a-service platforms like Firebase, building a multi-user experience on a secure, serverless, scalable infrastructure can be done quickly and simply. In this talk we'll build an app from scratch that allows you to run live polls of your users. To make this talk even more exciting, while we're building this app, we will run polls from our app for you, our awesome viewers, to interact with live. We're looking forward to all of you coming to join us live to learn something new and cast your votes with Flutter and Firebase.

Frank van Puffelen

Frank van Puffelen

Firebase Engineer

Frank (or Puf) is an engineer for Firebase at Google, and has been the host of the Firebase Summit for the past 5 years. He helps developers build extraordinary apps that use Firebase as their back-end. If you've ever asked a Firebase question on StackOverflow, you've probably met Frank already.

Paul Ruiz

Paul Ruiz

Developer Programs Engineer

Paul has a background in Android and IoT development. Outside of work he makes movie props as a hobby, and is a member of a Star Wars costuming charity where he volunteers at events as various movie characters including an Imperial Snowtrooper, X-Wing Pilot, or Tusken Raider. Before getting into tech Paul was a zookeeper, so feel free to ask any giraffe-related questions.

One of the best ways of delivering a great experience to your users is to change the app dynamically based on each user's attributes and behavior. We'll show you new updates in Firebase that make it easy to customize your app experiences for different groups of your users on the fly, and measure and adjust them dynamically to optimize the user journey.

Steve Wilber

Steve Wilber

Engineering Manager

Steve is an engineer working on Firebase Remote Config and A/B Testing. He was previously at Twitter where he worked on Crashlytics and was part of the team that launched Fabric. He is originally from Santa Cruz, CA where he developed a love for surfing and mountain biking. He also started his career there, working at Borland Software and building an early Java IDE called JBuilder.

Karen Zeng

Karen Zeng

Software Engineer

Karen is a Software Engineer working on Firebase Growth products, primarily Firebase Remote Config. Prior to Firebase she worked on building advertiser tools at Instagram. Outside of work she enjoys traveling and photography, and can often be found exploring the streets of San Francisco on her skateboard.

Using secure design principles as our guide, we will cover the default security of Firebase services and what developers need to do to configure and secure their applications. Walking through a simple serverless application built with Firebase backend products, we will discuss different security threats, from malicious actors to user error. As we go, we'll build a checklist that you can use to audit your own app's security and protect yourself and your users.

Rachel Myers

Rachel Myers

Developer Programs Engineer

Rachel is an engineer on Firebase Security Rules, Cloud Eventing, and Cloud Policy. At Firebase she focuses on helping developers build secure systems that protect users' privacy. On Google Cloud, she contributes to the CloudEvents Specification. Before joining Google, Rachel founded Opsolutely, was an engineer at GitHub, and was an engineer at online retailer ModCloth. In her free time she enjoys backpacking and board games.

Jon Skrip

Jon Skrip

Software Engineer

Jon is a software engineer on Firebase's Growth platform, with a specific focus on A/B Testing and Remote Config services. His career before Google consisted primarily of backend and systems engineering work, with an emphasis on cloud computing and distributed architecture. Jon has a passion for learning, and is currently studying Information Security topics in his free time. Outside of work, Jon likes to hike, ski, and generally wander aimlessly through nature.

As a developer, ML can help you build better apps. In this session we'll guide you through simple steps to build and train a TensorFlow model that does on-device recommendations based on content that the user has shown interest in. You'll then convert the model to TensorFlow Lite to run on mobile and deploy it on Firebase.

Ibrahim Ulukaya

Ibrahim Ulukaya

Developer Programs Engineer

Ibrahim helps developers make great apps with Firebase ML and AppQuality tools. He is passionate about iOS development and has published multiple apps. He's been working on Firebase for the past 5 years and previously worked on YouTube. Prior to that he was a Big Data Engineer and founded multiple startups. If not at work, you'll find him on a bike, kiteboard or playing beach volleyball.