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.


Laurent Simon

Professor of Chemical Engineering and Vice Provost for Undergrad Studies, New Jersey Institute of Technology

Areas: Biomedical Research, Chemical Engineering, Computational Thinking, Pharmaceutical, Research and Analysis

Laurent Simon is a professor of chemical engineering and the vice provost for undergraduate studies at the New Jersey Institute of Technology.

Simon’s current research focuses on transdermal drug delivery, protein purification, process modeling and control; these projects involve writing Wolfram Language code that is instrumental in building population pharmacokinetic/pharmacodynamic models and designing transdermal drug-delivery systems. These same research tools, deployed with webMathematica, are now used to enhance chemical engineering curricula with applications in biological engineering.


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.


Ming Hsu

William Halford Jr. Family Associate Professor, Haas School of Business and Helen Wills Neuroscience Institute, University of California, Berkeley

Areas: Biomedical Research, Complexity Science, Economic Research and Analysis, Economics, Software Development

Ming Hsu is an economist and neuroscientist who studies how people make decisions, in terms of both the hardware (i.e. the neural systems that make decision making possible) and software (i.e. the computations that these neural systems perform). He has used Mathematica extensively since his doctoral work at Caltech, studying the formation and evolution of prices in experimental double auction markets. Subsequent work focused on developing new computational models of choice behavior in decisions under uncertainty and relating these models to behavioral and neural data. In the future, he hopes to utilize the text-analytic capabilities of Mathematica to broaden the range of cognitive functions captured in current models of decision making.


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.


James C. Wyant

Professor Emeritus of Optical Sciences and Computer Engineering, University of Arizona

Areas: Biomedical Research, Education, Physics, Software Engineering

James C. Wyant was the founding dean of the College of Optical Sciences. He was also the founder of the WYKO Corporation. His company is known for having manufactured and sold phase-shifting interferometers for testing optics that later were used for measuring the shape of the recording heads used in computer hard-disk drives. At one point, every major manufacturer of hard-disk drives globally purchased WYKO instruments to test the recording heads of their drives. He founded another company in 2002 known as 4D Technology. There, he developed single-shot phase-shifting interferometers that, unlike other interferometers, give accurate results in the presence of vibration and air turbulence, thus making them very useful in manufacturing environments.


Dr. Kenneth Bogen

Areas: Biomedical Research, Chemical Engineering, Environmental Engineering, Molecular Biology, Risk Analysis

Kenneth T. Bogen, DrPH, DABT, is a nationally recognized, board-certified consulting toxicologist and former University of California environmental scientist who has done extensive work in environmental health risk assessment, with over one hundred published (including award-winning) scientific journal publications in the field. Since 1988, he has developed RiskQ, a comprehensive package for efficient, symbolic, documented statistical and data analysis in the Wolfram Language. Dr. Bogen has used RiskQ and Mathematica in a broad range of research and applied assessment topics including zinc-ion diffusion and cytotoxicity in the nasal cavity, nickel biokinetic modeling, multi-route exposure assessment, biologically based and mode-of-action-informed cancer risk modeling, physiologically based organophosphate pharmacokinetic/pharmacodynamic modeling, and applications of environmental, occupational and consumer product-related toxicology and epidemiology.


Tomás de Camino-Beck

LEAD University

Areas: 3D Printing, Biomedical Research, Complex Systems, Computer Graphics and Visual Arts, Image and Signal Processing, Internet of Things, Software Development

Tomás de Camino-Beck is a professor, researcher, entrepreneur and music producer who has contributed to the fields of mathematical biology, satellite imaging, cellular automata and epidemiological modeling, among others. He has used Mathematica for teaching a range of mathematical subjects and hands-on maker activities like 3D printing and microcontroller programming, as well as for projects in generative design and music video creation. Most recently, he has helped develop several educational videos and a Wolfram Language–powered website for demonstrating agent-based COVID-19 models in conjunction with the Costa Rican news agency El Financiero.


Virgilio Gomez Jr.

Quality Aspirators

Areas: Biomedical Research, Image Processing, Mechanical Engineering

Virgilio Gomez Jr. is a mechanical engineer who frequently uses Mathematica for research and development. As a graduate student, he used Mathematica to implement closed-form solutions for three-dimensional vibrations of elastic bodies. In his time as a research development mechanical engineer at Quality Aspirators, he has used Wolfram Language image processing in several projects, most recently for quantifying the aerosol spray generated during a certain dental procedure. This work aided in the design and testing of Safety Suction, a device for removing blood- and bacteria-carrying particles from the air to create a more hygienic environment, helping reduce the spread of COVID-19.


Greg Hurst

United Therapeutics Corporation

Areas: 3D Printing, Biomedical Research, Computer Science, Materials Science, Software Development

Greg Hurst is a mathematician and software developer who has used Wolfram technology heavily throughout his educational and professional career. He recently used the Wolfram Language to create novel algorithms for designing an artificial human lung that can be 3D printed using biocompatible materials such as collagen. Greg is constantly evangelizing Wolfram technology to his colleagues at United Therapeutics Corporation and elsewhere.


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.


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.


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.


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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