WOLFRAM

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.

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.

2016

Richard Scott

Mount Sinai School of Medicine

Areas: Bioimaging, Biomedical Research, Biostatistics

Richard Scott is part of a small group of engineers, pathologists and business development professionals at the pathology department at Mount Sinai working to commercialize image-based prostate cancer prediction models. The design of the analysis algorithms and the majority of the system development and testing were done using Mathematica and the Wolfram Language. One of the key technical advances of Scott’s system is its ability to accurately segment gland rings and fragments from prostate tissue across the full range of disease presentations using a Delaunay triangulation and Voronoi analysis.

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