# Core Contributors ## Founders Variational was co-founded by [Lucas Schuermann](https://lvs.io/) and [Edward Yu](https://quant.am/). Lucas and Edward met as engineering students and researchers at Columbia University before founding their own hedge fund (Qu Capital) in 2017. In 2019, Qu Capital was acquired by Digital Currency Group, and Lucas and Edward became the VP of Engineering and VP of Quant Trading (respectively) at Genesis Trading. In 2021, after processing hundreds of billions in volume at Genesis (at the time one of the largest desks in crypto), Lucas and Edward left to start their own proprietary trading firm: Variational. After raising [$10M in funding](https://www.theblock.co/post/322653/arbitrum-crypto-protocol-variational-funding) to profitably run their trading strategies for a few years, and integrating with virtually every CEX and DEX in the space, Lucas and Edward decided to use Variational's trading profits to develop the Variational Protocol. Lucas and Edward's goal with the Variational Protocol is to return market making profits to traders with [Omni](https://docs.variational.io/omni/about-omni), and solve pain points they saw firsthand by bringing institutional OTC trading on-chain with [Pro](https://docs.variational.io/pro/about-pro). ## Development and Quant Teams The Variational development and quant teams consist of [industry veterans](https://variational.io/about) active in crypto algorithmic trading since 2017 with prior experience at Google, Meta, Goldman Sachs, GSR, and more. All members of the core technical team each have more than a decade each of experience in software engineering and/or quantiative research. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.variational.io/getting-started/core-contributors.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.