I am an algorithmic trader turned mad scientist (though I’m working on my anger management). After spending a decade in the trenches of Wall Street, building highly optimized trading systems, designing novel portfolio algorithms, and managing some intense years of successful trading, I have moved into the world of Artificial Intelligence research and development. My interest has broadened from Computer Science, Finance, and Mathematics, into the exciting and active areas of Computational Neuroscience, Machine Learning, and Artificial General Intelligence (AGI).

I’m passionate about building the next generation of learning algorithms, with specific focus in applying Deep Reinforcement Learning and other methods toward online (incremental) modeling of complex temporal dynamics. I enjoy deep dives into data visualization, machine learning, software design, and mathematics. I’m a huge fan of the Julia programming language, and I’m not shy to predict its ascension as the future language of choice for Machine Learning and Data Science. Check out my blog for musings, ideas, and demos of my research and open source contributions.

I’m currently exploring what the next decade has in store for me. If you have a tough problem that will change the world, I want to hear about it. Send me an email, or find me on Github, Gitter, or Twitter.

Open Source Contributions


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.


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, 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).