Wolfram Computation Meets Knowledge

Wolfram Innovator Award

Wolfram technologies have long been a major force in many areas of industry and research. Leaders in many top organizations and institutions have played a major role in using computational intelligence and pushing the boundaries of how the Wolfram technology stack is leveraged for innovation across fields and disciplines.

We recognize these deserving recipients with the Wolfram Innovator Award, which is awarded at the Wolfram Technology Conferences around the world.

2014

Dr. János Karsai

Bolyai Institute, University of Szeged

Areas: Authoring in Mathematica, Computer-Aided Education, Impulsive Systems, Modeling Dynamical Systems with Mathematica, Nonlinear Oscillations, Population Dynamics

János Karsai has been using Mathematica since 1994 in teaching and research. He teaches mathematics and Mathematica-aided modeling to math, pharmacy, biology, and engineering students in Szeged and Berlin, and has given several Mathematica trainings of different levels and topics in Hungary, Czech Republic, Serbia, and Romania. He has supervised several outstanding students in Mathematica-related research. Karsai applies Mathematica experiments in his research; works on modernizing mathematical education, especially in applied sciences; and manages several projects in these fields. He developed a package and wrote a book on impulsive systems with Mathematica in 2002 and has prepared several dynamic teaching materials in Mathematica for his courses. Karsai manages the website www.model.u-szeged.hu.

2014

John Michopoulos

Naval Research Laboratory

Areas: Control, Control Engineering, Materials Science, Modeling Dynamical Systems with Mathematica, Physics, System Modeling

John Michopoulos uses Mathematica in his professional research with composite materials and has been published in the International Journal for Multiscale Computational Engineering, Composite Structures, and the Journal of Computing and Information Science in Engineering. He applies the global optimization capabilities of Mathematica to solve inverse problems and better understand the physics of materials and composite material designs.

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