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.

2019

Tom Burghardt

Emeritus Professor of Biochemistry, Mayo Clinic Rochester (Department of Biochemistry and Molecular Biology)

Areas: Biomedical Research, Education, Machine Learning, Molecular Biology

Tom Burghardt is a researcher at the #1 ranked Mayo Clinic, where he has spent the last three decades studying myosin and muscle tissue. In his 100+ publications, he uses Mathematica extensively for advanced statistics and modeling—tracing all the way back to a 1985 signal processing computation done in SMP, a precursor to Mathematica. Burghardt’s most recent innovation uses feed-forward neural networks developed in the Wolfram neural net framework to help create models for inheritable heart disease using a worldwide database of cardiac muscle proteins. His ultimate goal is to make these models available in the Wolfram Cloud for other researchers to explore and use.

2019

Dr. Jane Shen-Gunther

Doctor, Brooke Army Medical Center

Areas: Biomedical Research, High-Performance and Parallel Computing, Image and Signal Processing, Machine Learning, Molecular Biology

Dr. Jane Shen-Gunther is a medical doctor and researcher for the US Army, specializing in gynecologic oncology and obstetrics. She recently started using Mathematica and the Wolfram Language to advance her team’s research in HPV detection, automating the analysis of several gigabytes of image and instrument data and generating interactive visual reports for both patients and physicians. Dr. Shen-Gunther has also deployed her predictive model in the Wolfram Cloud to share access with other physicians. Her work has led to improved patient interactions, as well as better prediction of pap outcomes that impact underdeveloped countries.

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.

2015

George (Dave) Lawrence

Manager of Research Informatics, Oregon National Primate Research Center

Areas: Biomedical Research, Engineering Physics

George (Dave) Lawrence first used Mathematica in his work with the gamma ray observatory at Hughes Aircraft and today uses it as a basis for the computational integration of biomedical workflows at the Oregon National Primate Research Center. Although he starting using Mathematica for his own population modeling, Lawrence has since helped five hundred medical researchers adopt the Wolfram Language for data analytics. In addition, his ARSTools (Animal Resource System Tools) package linked diverse lab datasets and democratized data for all researchers. After his data analytics system was shown to improve the efficiency of planning new clinical trials by 50%, three other primate research centers began using Wolfram Language applications and EnterpriseCDF technology.

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