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.


Dr. Carol Johnstone

Senior Scientist, Particle Accelerator Corporation

Areas: Applied Mathematics, Biomedical Research, Computational Physics, Computer Science, Data Science, Mathematical Biology, Optimization, Physics

Dr. Johnstone is an internationally recognized senior accelerator physicist at Fermilab and Particle Accelerator Corporation. Her work was initially created to solve a simple set of approximate, thin lens optics equations simultaneously with geometric orbit equations. These constraint equations provided physical and field parameters that insured stable machine performance in novel accelerators for high energy physics research, such as the muon collider or Neutrino Factory. Her work evolved into a powerful new methodology for advanced accelerator design and optimization, which has since been applied to innovations in accelerators for radioisotope production, cancer therapy, security and cargo scanning, radiopharmaceuticals and green energy production. Dr. Johnstone’s efforts have resulted in the creation of a now-patented design for a non-scaling fixed-field gradient accelerator. Her work has also helped lead to the now-under-construction National Center for Particle Beam Therapy and Research in Texas, which will be the most advanced cancer therapy center in the US.


Nicholas Mecholsky

Research Scientist, Vitreous State Laboratory
Adjunct Assistant Professor, Catholic University of America

Areas: Authoring and Publishing, Image Processing, Machine Learning, Nuclear Engineering, Optimization, Physics, System Modeling

Nicholas Mecholsky is a research scientist and professor focusing on optimization and physical modeling. In addition to demonstrating high-level math and physics concepts to his students with the Wolfram Language, he has utilized it in research publications on subjects ranging from animal flocks to autonomous cars to thermoelectric transfer. He is currently involved in a joint project with the US Department of Energy and Vitreous State Laboratory using Wolfram Language image processing and machine learning to model, analyze and predict crystallization phenomena in nuclear tank waste. The project has significantly improved the efficiency of vitrification (transformation into glass), helping to make safer nuclear waste storage a reality.

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