Sillicon Valley
Presentations about Sillicon Valley

Incrementally Refactoring Your Habits With Psychology

Connecting, Managing, Observing, and Securing Services
Caching Beyond RAM: The Case for NVMe

Yes, I Test In Production (And So Do You)

Patterns of Streaming Applications

Human-Centric Machine Learning Infrastructure @Netflix

Artwork Personalization @Netflix

Machine Learning for Handwriting and Sketch Recognition

Machine Learning for Handwriting and Sketch Recognition

Full Cycle Developers @Netflix

Service Ownership @Slack

Transaction Processing in FoundationDB

Whispers in the Chaos: Monitoring Weak Signals

Netflix Play API - An Evolutionary Architecture

Software Love Languages (On Passion & Product)

Building Resilience in Production Migrations

Dropping The Work-Life Balancing Act

Capacity Planning for Crypto Mania

Capacity Planning for Crypto Mania

Deep Representation: Building a Semantic Image Search Engine

Airbnb's Great Migration: From Monolith to Service-Oriented

Chaos Engineering with Containers

3 Things I Wish I Knew When I Started Designing Languages

Evolving Continuous Integration: Applying CI to CI Strategy

“Quantum” Performance Effects: Beyond The Core

Disenchantment: Netflix Titus, its Feisty Team, and Daemons

Crisis to Calm: Story of Data Validation @ Netflix

npm and the Future of JavaScript

Learning to Love Type Systems

Desktop Applications in Electron: Pro Tips And Tricks

Building a Voice Assistant for Enterprise

What We Got Wrong: Lessons From the Birth of Microservices

Scaling Slack - The Good, the Unexpected, and the Road Ahead

Paying Technical Debt at Scale - Migrations @Stripe

Kotlin: Write Once, Run (Actually) Everywhere

Go - A Key Language in Enterprise Application Development?

Training Deep Learning Models at Scale on Kubernetes

Training Deep Learning Models at Scale on Kubernetes

Massively scaling MySQL using Vitess

The Whys and Hows of Database Streaming

Managing Values-Driven Open Source Projects
The JDK in 2018: What's Here, and What's Next

CRDTs in Production

Michelangelo - Machine Learning @Uber

Terraform Earth - Secure Infrastructure for Developers

Making AI FaaSt

Making AI FaaSt

Open Source Robotics: Hands on with Gazebo and ROS 2

Nearline Recommendations for Active Communities @LinkedIn

Jupyter Notebooks: Interactive Visualization Approaches

Fairness, Transparency, and Privacy in AI @LinkedIn

Security & Psychology: Demotivating Persistent Threats

Using Data to Measure Risk in Cyber Systems

Taking the Canary Out of the Coal Mine

Reducing Risk of Credential Compromise @Netflix

Reducing Risk of Credential Compromise @Netflix
Interviews
Incrementally Refactoring Your Habits With Psychology
What is the focus of your work today?
I build developer tools at GitHub. More broadly, I make technology more inclusive and accessible for people who have traditionally been left out.
In your spare time, you illustrate data structures and algorithms with acrylic paint. Tell me more.
When I was learning about data structures, it struck me how beautiful some of them were. I really love the idea of taking something that's generated by computer and trying to reproduce that by hand - both to get it into my head and to show my vision of how this can work to other people. I made a whole series. I was already a painter and artist learning about computer science, this inspired me to see if I could marry fine art and computer science.
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