I’m an engineer in the fascinating space of artificial intelligence (AI). Specifically, I’m working with a small and talented group of researchers and engineers on one of the hardest problems out there: teaching machines to understand and reason about the world the way humans do.

Previous to this, I’ve worn many hats: system architect, quant, trader, CEO, and open source leader. I’ve built teams from the ground up, managed huge portfolios, and written more lines of code than even I can imagine. Many people may know me for my Julia projects, specifically creating Plots and more generally the JuliaPlots organization and surrounding ecosystem.

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Open Source Contributions

Background

I studied mathematics and finance at the University of Rochester and NYU’s Courant Institute. My time on Wall Street included roles at several banks and hedge funds (including one which I founded), where I built the systems and strategies to run high-frequency market-making portfolios. My experience is both broad and highly specialized. I’ve hand-crafted solutions to many complex problems: real-time portfolio composition optimization, writing GPU kernels for custom evolutionary algorithms, high-speed networking and financial order book building, GUI building and visualization software, and even my own proprietary programming language for financial simulations and back-testing.

In 2013 I started to distance myself from the finance world, pursuing self-directed learning and research in the broad fields of artificial intelligence and machine learning. I also contributed my time and experience to the world of open source. As a lifelong software engineer and mathematical thinker, I’m thrilled to apply my experience to the difficult and impactful problem of building thought partners at Elemental Cognition.


Researcher

Neuroscience, machine learning, reinforcement learning, artificial general intelligence… you name it, I’m studying it. The big problems of tomorrow require intelligent integration of more data than you can imagine. With brain-inspired learning networks we can tackle the problems which are too big and complex for today’s machine learning algorithms.


Software Engineer

I have been designing and building software since I was a boy, learning BASIC in the fourth grade. I’ve always had a passion for clean, efficient code, and I love building complex visualizations for everything I do. A picture is worth a thousand words, so why not take advantage? Though I’ve used almost every programming language at some point of my life, I love developing in Julia, as I can finally bypass the curse of two languages for scientific computing.


Trader

Trader, researcher, quant, portfolio manager, and trading system designer. I have specialized in structural and statistical arbitrage in equities, ETFs, and futures. I thrive in high intensity environments. Quick thinking and calm under pressure help me find success in turbulent times (though smart modeling and software design doesn’t hurt).