I started Walkthrough (www.walkthrough.co) to help make ethical and unconflicted financial advice accessible to everyone. I mainly wear two hats at our company:As CTO, I oversee or personally develop all technical operations (financial algorithms, AI integrations, bank data importing/standardization, end-user app, internal tools, system architecture, deployment, dev environment selection/config/maintenance). I run our engineering team, which has deployed a number of products and MVP's including a full financial advice app built on AWS/Typescript/Node/React.As Co-Founder, I've had the amazing opportunity build a business with some of my best friends in the world. I've spent a bunch of time:- Understanding the financial advice market- Building a team- Marketing and selling to consumers, businesses and investors- Developing and iterating on several products- Learning to operate a tech startup in a highly regulated space.I'm passionate about financial literacy and would love to connect with other people/initiatives in the space.

I was the training partner for the United States' 2021 Tokyo Olympic Representative in the Finn sailboat. We organized all aspects of our campaign (international competitions, coaching, equipment, finances, etc) and trained to perform at a world-class level. I'm incredibly honored to have contributed to my partner Luke's (https://www.linkedin.com/in/lukecmuller/) 6th place finish at the 2021 Finn World Championships and 13th place finish at the Tokyo 2020 Olympics.

I spent five years at Google working on the Ads Privacy and User Trust team. We developed infrastructure and policy to enforce privacy across Google Ads, protecting end users and reducing regulatory exposure of Google’s $100B+ annual ads revenue.At various times, I:- Served as technical lead for Google’s user data access privacy enforcement solution, which isolates privacy policy in a custom, lawyer-readable configuration language and handles billions of qps spread across 15+ binaries in multiple languages.- Served as project lead for privacy efforts in ML-driven user modeling and ID Linking. In this capacity I drove legal and engineering stakeholder discussions to define privacy policy and then led multi-engineer, cross-team efforts to design and implement enforcement of the resulting decisions across multiple stacks and tens of binaries.Along the way I learned way more about advertising than I ever expected to in my life (unexpectedly fascinating).

My primary research interests while at school were in numerical methods and scientific computing, so I spent a lot of time discretizing differential equations and developing solvers/optimization engines. My research most directly applied to riverbed stability and flame dynamics, although this work also has large overlap with AI/ML training algorithms and I have some experience applying it there as well.