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.


Richard Carbone

Digital Forensic Analyst & Researcher, Defence R&D Canada

Areas: Data Analysis, Data Science, Research and Analysis, Software Engineering

Richard Carbone is a digital forensic analyst and researcher at Defence R&D Canada, where his work involves investigations into advanced persistent threats, state actors and insider threats. He writes and designs tools using Mathematica to solve certain digital forensic problems that have not been adequately addressed by the community or by digital forensic software vendors. (The growth in Mathematica’s image processing capabilities specifically has made it a useful tool in digital forensics.) Examples of his prototyped tools include a forensic image analysis system and a binary file analysis system, the latter of which helps the user visually identify the underlying data and structure patterns inherent in most file formats. Carbone additionally has conducted research with federal law enforcement to define Canada’s standards for forensic analysis of computer memory.


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.


Scot Martin

Gordon McKay Professor of Environmental Engineering, School of Engineering and Applied Sciences, Harvard University

Areas: Authoring and Publishing, Data Analysis, Data Science, Engineering, Environmental Engineering, Physics

Scot Martin is currently a Gordon McKay Professor of Environmental Engineering and has previously held positions as an assistant professor at the University of North Carolina at Chapel Hill and a NOAA Postdoctoral Fellow in Climate and Global Change at MIT. His research focuses on engineering solutions to the major environmental challenges presently facing the world. Scot’s laboratory works specifically on problems of air and water pollution and their effects on climate change. His current research has a focus on connections among plant emissions of volatile organic compounds, particle-phase secondary organic material and climate. Martin is currently working to complete a book on aerosol science and technology and is developing a HarvardX course on thermodynamics.


Edmund Robinson

Director of Data Analytics, Afiniti

Areas: Actuarial Sciences, Data Analysis, Data Analytics, Data Science, Industrial Mathematics, Risk Analysis, Risk Management, Software Development

Edmund Robinson is an industrial mathematician and software developer who has made many noteworthy contributions in the fields of fund and risk management as well as reinsurance. His prominent work includes the creation of interactive visualizations to provide breakdowns and comparisons of funds on the fly; generation of highly formatted performance figures with financial measures and statistics; summary infographics and PDF export; and rapid modeling, simulation and analysis of bespoke contract structures with interactive data, model and parameter selection. Edmund has also given talks focusing on workflows that combine third-party geographic information system (GIS) datasets with the contract loss distributions to produce a dynamic tool to estimate and visualize incurred but not reported (IBNR) claims related to a windstorm event and historical analysis of sunny-day flooding occurrences and forecasting with time series analysis.


Fernando Sandoya

Principal Professor, Escuela Superior Politécnica del Litoral

Areas: Business Analysis, Data Science, Education, Machine Learning, Software Development

Fernando Sandoya currently teaches at the post-graduate level and oversees research and development of new products in context of consulting business. Among his notable projects are the development and implementation of an intelligent assistant for optimal sequencing of production in the largest food manufacturer in Ecuador (PRONACA); the development and implementation of a system for optimization of the reverse logistics of used tires across Ecuador (SEGINUS); the development of descriptive and predictive analytical model for land transportation of containers to the Ports of Guayaquil (Spurrier Group); and professional training programs in business intelligence, data science, machine learning and models for Ecuadorian universities. Dr. Sandoya is currently working to develop a machine learning system for Redclic and holds development contracts with an additional dozen companies.


Omar Olmos

Instituto Technologico y de Estudios Superiores de Monterrey

Areas: Computational Physics, Data Science, Education, Machine Learning, Mathematics Courseware Design, Physics

Omar Olmos is north regional director of science and engineering for the Monterrey Institute of Technology, where he uses Mathematica for a range of education and research tasks. In addition to developing interactive examples, tutorials and other student resources, he uses Wolfram Language machine-learning analytics to predict student performance. Omar has also used Mathematica to model electromagnetic waves interacting with nanostructures, performing numeric experimentation to study new nanoscale optical effects.


Aaron Santos

Data Scientist, EMC Insurance

Areas: Authoring and Publishing, Computational Physics, Data Science, Industrial Engineering, Internet of Things, Nanotechnology, Risk Analysis

Dr. Santos is a data scientist, professor and author who uses Wolfram technology to advance data and device integration in a variety of sectors. He and his team at EMC Insurance have used the Wolfram Language and Wolfram Enterprise Private Cloud for valuable research analyzing data from IoT devices to help improve driver safety, reduce fuel consumption and identify worksite hazards. As part of a recent startup, Dr. Santos also worked on the development of a nanotechnology device for efficiently identifying the genetic makeup of food products, with future plans to integrate Wolfram Cloud technology to provide additional analytics and services to consumers.


Brian Kanze


Areas: Data Analysis, Data Science, Research and Analysis

As data scientist and concept design leader at Georgia-Pacific, Brian Kanze uses Wolfram technologies to bring innovation to Georgia-Pacific’s consumer products division. He developed a large-scale analysis and reporting tool to assist building owners and managers in forecasting product usage, reporting availability and planning work shifts according to peak usage times. Georgia-Pacific is pioneering new software-based analytic services using Wolfram Language-based technology, and Kanze’s work has identified key areas where this technology can be used to enhance performance and analysis.


ValueScape Analytics, Inc

Areas: Data Science, Engineering, Mechanical Engineering

The team at ValueScape Analytics uses the Wolfram Language and Wolfram technologies to build the cloud-based computational back end for their platform. ValueScape is an innovative data science company providing real estate analytics solutions through Valuation Navigator, an iOS application for appraisers and lending institutions. The company leverages the Wolfram Language running in the cloud to provide statistical analysis, visualization, density plots, and geographic data integration.

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