Nima Pourtolami is a highly proficient physicist with extensive modeling expertise and a knack for data analysis. Pourtolami has a track record of success in mathematical model optimization, testing, and improvement while being able to interpret and communicate data effectively. Pourtolami is a computer and data analysis savant, skilled in Mathematica, Matlab, C++, Python, Java, and Scala, machine learning, Apache Spark, SQL, parallel computing, and Linux. Emphasizing his quantitative skills, Pourtolami excels in stochastic processes and differential equations, statistics, probability theory, linear algebra, vector spaces, functional analysis, and variational methods essential in reading scientific data accurately.

Additionally, Pourtolami has dedicated expertise in finance, particularly derivatives/option pricing, fixed income, VaR, CVaR, credit risk, and CVA. Pourtolami's research portfolio is also impressive and includes model building beyond the standard model of particle physics, Higgs boson phenomenology, neutrino physics, the Casimir force, PT symmetric quantum field theory, quantum Hall effect in bilayer graphene, and the stochastic fractal properties of fluid turbulence.

Pourtolami holds a master's degree in Theoretical and Mathematical Physics from the University of Oklahoma, a master's degree in Statistical Physics from Amirkabir University of Technology - Tehran Polytechnic, and a doctorate in Theoretical High Energy Physics from Concordia University. Having held positions such as associate at National Bank Financial, quantitative researcher at National Bank of Canada, postdoctoral researcher at Concordia University, researcher, and instructor at Concordia University and the University of Oklahoma, Pourtolami brings a wealth of experience from academia and industry.