Sergey Voronin has a background in applied and computational mathematics and scientific computing in academic and industry settings. He completed Engineering school, went on to defend his Ph.D. in 2012 in Applied and Computational Mathematics, worked in academia in postdoctoral and instructor capacity beween 2012 and 2017 and then worked for an R&D small business between 2017 and 2022, where he actively participated in the SBIR program, followed recently by an R&D role at a tech company. He has experience with data analysis, optimization methods, data compression, imaging applications, machine learning, and high performance computing. (resume).

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