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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.

Presented at the Wolfram Technology Conferences. Learn more

2021

Houston Methodist Research Institute

Areas: Biomedical Research, Biostatistics, Biotechnology, Mathematical Biology, Mathematical Modeling

Houston Methodist is a leading academic medical center that takes a multidisciplinary approach to changing the face of medicine. Doctors Cristini, Butner and Wang are a team of engineer scientists at the Houston Methodist Research Institute who use mathematical modeling to study biological problems, with a special focus on disease progression and treatment. They design and implement mathematical descriptions of the key biophysical phenomena within the tumor microenvironment. They are currently working to establish methods to use mathematical modeling to predict cancer-patient response to immune checkpoint inhibitor immunotherapy. Mathematica has played a key role in this process, allowing them to rapidly implement and update model versions, perform testing and optimization, and conduct extensive analysis on large sets of patient data.

Award accepted by Dr. Joseph D. Butner, faculty fellow, Mathematics in Medicine program; Dr. Vittorio Cristini, professor and director, Mathematics in Medicine program; and Dr. Zhihui Wang, research scientist and associate professor, Mathematics in Medicine program.

2021

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.

2017

Dr. Marco Thiel

Professor, Institute for Complex Systems and Mathematical Biology
Professor, Institute for Pure and Applied Mathematics

Areas: Complex Systems, Education, Mathematical Biology, Physics

Marco Thiel is a professor at the University of Aberdeen who uses Wolfram technologies in various domains, including education and research. A true evangelist, he has introduced hundreds of students and industry professionals alike to the Wolfram Language, and is an active user on Wolfram Community. For the last two years, Dr. Thiel has been using the Wolfram Language to develop algorithms and analyze sensor data of subjects in clinical dementia trials. The analysis is performed on large datasets through the external devices of subjects, and predictive tools, which determine changes in brain connectivity as dementia develops, are created. In his classes, Dr. Thiel utilizes CDF documents to create interactive lecture notes for his students. Using real-world data, students are able to connect topics they learn in other courses through simulations done in real time, instilling computational thinking into students long after they finish the course.

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