Head of Algorithmic Trading Group, GlimmAnalytics

Dr. Kaufman received his PhD in Applied Mathematics and Statistics from Stony Brook University, New York, in 2014. He has served as a High Performance Computing (HPC) Systems Administrator, Postdoctoral Research Scientist, and as an Adjunct Professor at Stony Brook, and is currently a Visiting Scientist. 

Dr. Kaufman has 12 years’ experience developing small and large-scale computing applications, including 3 years developing applications for financial analysis. He has also published in the field of turbulent fluid flow of immiscible fluids.

At GlimmAnalytics, Dr. Kaufman is developing models for efficient and accurate computation of market risk and automated trading strategies. This includes the design of econometric analysis tools, automated stock trading algorithms and risk management analysis tools for stock portfolios, and the design and implementation of algorithmic trading frameworks.