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

Robert Rasmussen and Kirk Reinholtz

Senior Engineers, Jet Propulsion Laboratory

Areas: Aerospace, Control Engineering, High-Performance and Parallel Computing, Probability Theory, Risk Analysis, Software Development, Systems Engineering

Robert Rasmussen and Kirk Reinholtz are systems engineers who have used the Wolfram Language to develop a set of methodologies for building complex control system applications. Their integrated mission operation systems utilize the Wolfram Language to provide live updates to local data stores, keeping information consistent throughout processes. Both have used Mathematica extensively for large probability and engineering computations—including hundred-day distributed computations and the processing of gigabyte-scale datasets. They evangelize Mathematica and the Wolfram Language to others in the aerospace field, encouraging them to use Wolfram Notebooks for exploration and the expression of ideas.

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.

2013

Prof. Dr. Frank Brand

Berlin School of Economics and Law, Germany

Areas: Finance, High-Performance and Parallel Computing, Industrial Engineering Economics, Mathematics

Physicist Frank Brand teaches courses in business mathematics, statistics, econometrics, and optimization using Mathematica. He has used Mathematica for many years, starting with his PhD thesis, “Optimization of Complex Optical Systems with Evolution Strategies.” Frank’s achievements using Mathematica in his research include the automatic construction of quality functions related to optimization problems. He also used Wolfram technology to write books—very recently he published a book on the analysis of complex systems, based on applications of graph theory.

2013

Stefan Braun

Managing Director of SmartCAE

Areas: Aerospace, Biotechnology, Chemical Engineering, Control, Data Mining and Analysis, Engineering, Finance, Financial Risk, High-Performance and Parallel Computing, Image Processing, Industrial Engineering, Interface Design, Materials Science, Mathematica Consulting, Mechanical Engineering, Pharmaceutical, Physics, Risk Analysis, Signal Processing, Structural Engineering

Stefan Braun is recognized for using Mathematica in industrial applications. He has used Mathematica and the SmartCAEFab in more that 150+ industrial projects in different application areas. SmartCAE’s software solutions allow practical users to simulate complex applications problems, with a lot of parameters, without being a simulation or Mathematica expert.

2012

Richard Anderson

Computer Scientist

Areas: High-Performance and Parallel Computing, Mathematics

Richard Anderson is recognized for his pioneering use of gridMathematica to explore network properties using percolation and random graph theories. He has developed gridMathematica applications that use a probabilistic approach along with large-scale multiprocessor computing techniques to explore the underlying structure of complex networks. This work led to the development of new methodologies to identify nodes that are critical to network cohesion and connectivity.

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