From our origins in mathematical and technical computing, Wolfram technologies have emerged as a major force in many other areas of computing. Passionate individuals and organizations have played a major role in helping advance the usage of our technologies. We recognize these deserving recipients with the Wolfram Innovator Award, which is awarded at the Wolfram Technology Conferences around the world.
Adjunct Assistant Professor, Catholic University of America Areas: Authoring and Publishing, Image Processing, Machine Learning, Nuclear Engineering, Optimization, Physics, System Modeling
Nicholas Mecholsky is a research scientist and professor focusing on optimization and physical modeling. In addition to demonstrating high-level math and physics concepts to his students with the Wolfram Language, he has utilized it in research publications on subjects ranging from animal flocks to autonomous cars to thermoelectric transfer. He is currently involved in a joint project with the US Department of Energy and Vitreous State Laboratory using Wolfram Language image processing and machine learning to model, analyze and predict crystallization phenomena in nuclear tank waste. The project has significantly improved the efficiency of vitrification (transformation into glass), helping to make safer nuclear waste storage a reality.
Dr. Fazio is an assistant professor at the University of Alabama at Birmingham whose main focus is optical imaging. His research using Wolfram technologies led to several significant NIH grants, including the 2017 Xtreme Research Award from Heidelberg Engineering at the Association for Research in Vision and Ophthalmology (ARVO) meeting. This award was granted to Dr. Fazio for creating a custom clinical imaging protocol for glaucoma patients that provides an estimate of the eye-specific mechanical response to time-varying intraocular pressure. Additionally, he created an image processing algorithm that quantifies the 3D structure of the optic nerve from OCT clinical data entirely in the Wolfram Language.
Kale Wallace first started using Mathematica in university courses and has since used it in his work at Southwestern Energy and Samson Energy for data handling and image processing. At Southwestern Energy, Wallace built a well productivity prediction model analyzing millions of lines of data and using machine learning to predict well performance based on drilling and completion parameters. He has also created field-development visualizations showing wells brought online and their corresponding production and cashflow. His replication of the ARIES economics engine in Mathematica allowed probabilistic (Monte Carlo) economics methods, full-field development scenarios, break-even calculations, and go-forward recommendations to be evaluated much more quickly than could be done in ARIES.
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.
A professor in biomedical image analysis, Bart ter Haar Romeny uses Mathematica to design brain-inspired image analysis methods for computer-aided diagnosis. He is an enthusiastic teacher, and introduced Mathematica as a design tool in the curriculum for all students of his department and in most projects in his group. He advocates that Mathematica is ideal for designing innovative algorithms and for “playing with the math.” His PhD students van Almsick, Duits, Franken, (now Professor) Florack, Janssen, and Bekkers substantially contributed to the Mathematica packages on brain-inspired computing. He cochaired with Markus van Almsick the International Mathematica Symposium 2008 in Maastricht and teaches a popular national course on biologically inspired computing (book written in Mathematica), which was thrice awarded the BME Teaching Award.
Chemical engineer Ronald Kurnik develops medical devices, using Mathematica for rapid prototyping of algorithms for signal and image processing and for quantitative chemical reaction modeling. His work has led Roche to file for 15 patents, 7 of which have been issued so far.