Most of what I do is not easily compressed into a sound bite. Some people get confused because on the surface I’m involved in all sorts of things. However, if you look beneath the surface, everything I do follows the same pattern: I question, imagine, learn, and create things. It’s usually in that order and is what I consider to be ultimate intellectual freedom. This is what drives me and informs everything I do. In some ways it is a dichotomy of primitive and modern as the drive stems from the thrill of the hunt. Yet there are no arrows nor guns, and the game is not animal. Instead it is the idea that must be captured from out of the wild unknown and transformed into something tangible. At times this journey requires exploring places where others have dared not trespass. It’s like pushing the edges of the world and finding a new land.

Whether it’s designing and leading an organization to build a financial exchange for derivatives, creating statistical and machine learning models to predict people’s spending habits, or filtering noise from covariance matrices to optimize investment portfolios, the overarching motivation is the pursuit of the idea. At times this is in stark contrast to the world of startups, where it is about monetization. It can be closer to the misunderstood and tormented world of Van Gogh than the immediately impactful world of Godin, and this is okay. There is a place for ideas that not only take time to develop but also time to understand. After all Rome wasn’t built in a day, and neither was the sequencing of the human genome, nor quantum mechanics.

Brian founded Zato Novo as a vehicle to pursue artificial intelligence and machine learning R&D. Zato Novo’s flagship product is Pez.AI, which is a platform that melds conversational AI with data analysis. His first foray in AI was shortly after university, where he wrote a genetic algorithm to parse content and sentences from HTML pages. Afterward, he implemented his own self organizing map (aka Kohonen network). He founded his first company, Cenozoa, to commercialize the technology as a fuzzy search/recommendation engine. After winding down Cenozoa, Brian joined the world of finance, where he developed tools for quantitative research at Bridgewater Associates, Merrill Lynch, and GAMA. Brian has also built an exchange for interest rate swaps, created models to classify clauses within contracts, forecast individual consumer spending. Brian has released numerous open source packages, including a library for optimizing portfolios using random matrix theory and shrinkage estimation. He is currently finishing his book, Modeling Data With Functional Programming In R, to be published in 2016 by Chapman & Hall/CRC Press. Brian is also an Adjunct Professor at the CUNY MS program for Data Analytics, where he teaches mathematics and machine learning.