Deep Nexus builds advanced statistical models to generate probability distributions for future outcomes that are clear and actionable. Applications include sequential data in agricultural, chemical, medical, and financial markets. The finance models are combined with proprietary trading algorithms to deliver low-risk and high-reward returns.
Kevin is a technologist with over 20 years of experience in financial markets while holding Series 7 and 66 securities licenses. At Deep Nexus, he has been responsible for the development and coding of innovative deep learning models and the application of novel methods for analyzing noisy data. Kevin received his BA from Columbia University.
Deep Nexus is a multi-disciplinary collaboration among physicists, mathematicians, electrical & chemical engineers, and computer scientists. The team employs the scientific method in the development and use of emerging technologies for the quantitative analysis of time-series and sequential data.