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.


Tyson Jones and Simon Benjamin

Tyson Jones, Postdoctoral Researcher, University of Oxford
Simon Benjamin, Professor of Quantum Technologies, University of Oxford

Areas: Physics, Programming, Software Development, Software Engineering

Tyson Jones is a postdoctoral researcher at the University of Oxford, studying first-generation quantum computers and their simulation via high-performance classical computing in the areas of quantum computing, high-performance computing, scientific simulation and software development. He is also a senior quantum software engineer at Quantum Motion Technologies and a consultant for the UK’s National Quantum Computing Centre.

Jones’s doctoral work included the creation of QuESTlink, an open-source WSTP-powered package for simulating quantum computers, integrating the QuEST project’s hardware-accelerated numerics with Mathematica’s powerful symbolic engine. QuESTlink combines a plethora of Wolfram facilities, novel algorithms and high-performance computing techniques behind an intuitive API, enabling research-frontier computation through only a few lines of code.

Simon Benjamin , principal investigator (PI), is a professor of quantum technologies with the Materials Department at the University of Oxford. He leads a group of 17 applied theorists who look at diverse aspects of quantum computing, including architectures, fault tolerance and algorithms that are robust against hardware imperfections. His team created QuEST, a world-leading tool for classical emulation of quantum devices.


Thomas R.H. Tibbles

Head of International Equities, Madison Investments

Areas: Data Science, Finance, Financial Analysis, Software Engineering

Tom Tibbles and his team have focused for decades on implementing a well-tested and successful investment strategy to invest portfolios of international stocks. Over the last few years, he has led the team to embrace the Wolfram technology stack to make the process explicit in software and to enhance, accelerate and improve the quality and consistency of the workflow.

Financial data can be sliced cross-sectionally, through time or simultaneously by both curating and provisioning processed data in multidimensional matrix structures—“DataCubes.” Doing so has made it highly efficient to execute the desired types of data manipulations and visualizations in Mathematica.

The project pipeline began by writing custom APIs to extract data locked in silos; legacy procedures were then translated and separated into hundreds of “CustomMetrics” to clean and increase the information content of individual data segments. After the release of Mathematica 12, the project expanded to take advantage of the entity store data framework.

Additional projects have focused, within a Wolfram Language package, on automating the integration and enhancement of data and sequencing the workflow steps across multiple internal and external data sources and applications. Lastly, user experience was vastly improved with the custom development of a GUI to access, examine further and manipulate data while dynamically displaying the visual reports.


Sandipan Bandyopadhyay

Associate Professor, IIT Madras

Areas: Computational Thinking, Education, Physics

Sandipan Bandyopadhyay is an educator and researcher in the fields of mechanisms and robotics. He specializes in theoretical and computational kinematics, in particular in the domain of spatial parallel manipulators, such as the Stewart platform.

Bandyopadhyay’s research involves highly demanding symbolic computations, for which he finds a trusted partner in Mathematica. In at least 20 of his journal publications, the symbolic capabilities of Mathematica have played a significant role. Moreover, the flexibility of Wolfram Language has allowed him to develop algorithms and modules to explore deeper into algebraic geometry and kinematics and create customized tools for analyzing problems using hyper-complex numbers, such as dual numbers and dual quaternions. He uses the dynamic visualization capabilities of Mathematica to bring virtual robots to life, enabling his students to manipulate them and develop a better understanding of complicated motions of constrained multibody systems.


Sander Huisman

Professor, Physics of Fluids, University of Twente

Areas: Data Analysis, Physics, Software Development, Software Engineering

Sander Huisman has been using Mathematica since 2003 for the processing of all his data, creating figures and visualizations and doing complicated fits and optimizations. Furthermore, he uses Mathematica’s interactive capabilities to generate illustrative examples in his fluid mechanics classes. He also uses it recreationally for the production of generated art for the yearly GENUARY event. He is also a contributor to the Wolfram Function Repository, having created over one hundred functions.


Picket Pharmaceuticals, Inc.

Accepted by: Joshua Kriger and Lauren Williams

Areas: Data Analysis, Data Analytics, Economic Research and Analysis

The foundation of Picket Pharmaceuticals, Inc.’s approach is to first acquire, then integrate, large healthcare datasets—such as shortage data, manufacturing information, unit usage, pricing, price variation and many more—that capture the universe of healthcare interactions that surround each patient’s walk from diagnosis to completion of care through their piece of the healthcare system.

Using the Wolfram technology stack, Picket has conducted interesting work with insights on the points of failure and where inefficient markets exist in the supply chain. Of note, computation techniques used include projecting large amounts of healthcare supply and medication usage data into images. These images become the data fed to repurposed visual neural net training procedures that result in AI/machine learning models that are able to accurately recognize signals that predict future drug shortages.

Working with Wolfram’s Consulting Group, Picket has also verified a derived new class of economic measures, titled the Sutherland measures, made feasible by taking into account special economic qualities and situations of supplied medicines for the generic drug markets.


Peter Taborek

Professor of Physics and Astronomy, University of California, Irvine

Areas: Computer-Aided Education, Education, Engineering, Physics

Peter Taborek’s research is in experimental condensed matter physics, and he teaches mathematical methods for the physical sciences to undergraduate and graduate students in physics, chemistry and engineering. Most of the standard textbooks for this subject were written before the era of personal computers and do not equip students with the tools of modern technical problem solving. To remedy this situation, Taborek has developed his own e-textbook, MathematicaHandbook, which is written entirely in Wolfram Notebooks.

The text covers traditional topics, such as complex analysis, linear algebra and ordinary and partial differential equations, but explains and illustrates concepts using computer algebra, graphics and numerics. This text has been used for over a decade and includes many figures, animations and live code so students can perform computations while learning course concepts. Student learning requires numerous practice problems with grading and feedback. For a large undergraduate class, this is labor-intensive, so Taborek has developed a web-based platform to deliver homework problems, which are graded using calls to Wolfram Cloud APIs.


Patrick Scheibe

Research Scientist, Max Planck Institute for Human Cognitive and Brain Sciences

Areas: Data Analytics, Programming, Software Engineering

Patrick Scheibe boasts a dynamic and illustrious career journey in academia and industry. He spent over a decade at Leipzig University, where he played a pivotal role in leading an image and data processing unit, enabling researchers to quantify medical and biological experiments easily. During his PhD studies, he took a deep dive into the intricacies of the human fovea, extensively utilizing Wolfram Language to model and quantify this crucial eye region from optical coherence tomography scans. Subsequently, Patrick’s expertise took him to the neurophysics department at the Max Planck Institute for Human Cognitive and Brain Sciences, where he continues to work on data processing for quantitative MRIs.

Patrick is a highly versatile professional with a wide range of expertise beyond academia. He has worked as a consultant using Mathematica on various projects focused on simulations, modeling and data analyses in diverse domains for companies like Daimler, Procter & Gamble and Dow Chemical. Patrick has been developing and maintaining the Wolfram Language integration for JetBrains IDEs since 2012. His exceptional skills and expertise have led him to join the IntelliJ Platform SDK team at JetBrains. In addition, Patrick has developed several syntax highlighters for Wolfram Language, one of which has been used on the official Mathematica Stack Exchange site, where he is an enthusiastic moderator and member.


Oliver Knill

Preceptor and Digital Media Specialist, Harvard University

Areas: Computational Thinking, Education, Geometry, Mathematics

Mathematica is vital to Oliver Knill’s teaching and research. In teaching, it produces professional graphics for handouts, facilitates visualizations and animations, and serves as a platform for innovative student projects. It’s also essential for vetting assignments and examples, enabling a quick search for appropriate problems for both homework and exams. Knill has employed it to design 3D printable objects, generate high-resolution animations and illustrate musical concepts like Markov chain–generated music.

In his research, Knill’s primary laboratory is Mathematica. Currently, he is delving deeper into discrete geometry, probability, spectral theory and linear algebra. He is thrilled about uncovering previously undiscovered relationships and enhancing proofs with code. This allows any curious individual to explore the underlying structure. Mathematica code is close to natural language, acting as a runnable pseudocode. While examples can elucidate a theorem, providing code that showcases it using random structures is not only thrilling but also validates the result’s efficacy.


Martijn Froeling

Assistant Professor, University Medical Center Utrecht

Areas: Image Processing, Research and Analysis, Software Development

Martijn Froeling is an assistant professor specializing in quantitative neuromuscular magnetic resonance imaging (MRI) at the University Medical Center Utrecht. His work revolves around enhancing MRI techniques to better understand muscle function and diseases.

MRI scans provide valuable data, but they need careful processing and analysis. That’s where Froeling’s QMRITools paclet comes in. The paclet is a handy toolkit for experimental design, data analysis and teaching. Since its launch in 2012, it has been used in over 50 scientific papers. Originally created to analyze muscle diffusion-weighted imaging data, QMRITools has expanded its scope. It now includes features like cardiac analysis (including tagging and T1 mapping), Dixon reconstruction, EPG modeling and fitting, J-coupling simulations and more.

The paclet currently offers over 450 custom functions, making it a valuable resource for researchers. Plus, there’s extensive documentation with more than 750 pages, and each toolbox comes with demonstrations. With these tools, Froeling aims to simplify quantitative MRI analysis, benefiting our understanding of muscle injury and disease.


Mark Rawlins

Executive Chairperson and Chief Engineer, Energy and Combustion Services

Areas: Mechanical Engineering, Research and Analysis, Software Engineering

Energy and Combustion Services offers global energy management analytics and autonomous measurement systems for large-scale mining and industrial manufacturing. Mark Rawlins is a professional engineer (mechanical), certified energy manager, and measurement and verification professional. He specializes in energy system modeling for efficiency and productivity, using digital twins to simulate and support new designs. His primary goal is aiding companies in transitioning to net-zero carbon emissions while maintaining efficiency. He also develops advanced metering systems that provide insights into energy and process deviations, some operating autonomously.

Wolfram Language is foundational to his R&D work, which includes a road condition monitoring system that marries vision-based road defect detection and location with vehicle dynamics and vibration signal processing using edge computation to report road and safety conditions autonomously. Separate devices can communicate and accept instructions from each other for extended inspections.


Márcio Rosa

Professor of Mathematics, IMECC-UNICAMP

Areas: Education, Mathematics, Mathematics Courseware Design

For 20 years, Márcio Rosa has been making pedagogical innovations on the principle that university students should be using software, including the Wolfram Cloud, to continue their education in higher mathematics. He believes students should be trained to use software as a tool to aid their endeavors rather than learning to replicate the software’s functions. The geometric approach is reinforced so that the student, when studying and solving problems, is able to produce images with software and interpret them. Rosa has published various articles and supervised theses based on his experience and unique approach to mathematics education.


Esma Gel

Cynthia Hardin Milligan Chair of Business and Professor of Supply Chain Management and Analytics, College of Business, University of Nebraska–Lincoln

Areas: Modeling Dynamical Systems with Mathematica, Research and Analysis

In her previous role as an associate professor in the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University, Esma Gel used Mathematica for a system dynamics model related to the spread of COVID-19.

Gel’s team, ASU METAz, helped guide the Arizona Department of Health Services by supplying predicted outcomes to various “what if?” policy questions. The team periodically released accurate projections for cases, hospitalizations and deaths in Arizona for more than 15 months, often being featured in mainstream media outlets.


J. William Helton

Professor Emeritus of Mathematics, University of California San Diego

Areas: Geometry, Mathematics, Software Engineering

J. William Helton’s group developed the package NCAlgebra for doing general-purpose noncommutative algebra in Mathematica. It began around 1990 and has been extended continually since then. From his work at the origins of noncommutative geometry and H-infinity control, Helton kept seeing such noncommutative formulas and hoping computer algebra could help. So, with Bob Miller, he started NCAlgebra and developed algorithms to find out. Around the year 2000, linear control theory shifted away from equalities to inequalities, e.g. from Riccati equations to linear matrix inequalities. This motivated Helton and a few others to begin what has developed into an elegant theory of noncommutative inequalities, to wit, a noncommutative version of real algebraic geometry. NCAlgebra seriously accelerated (and was accelerated by) this development.

A booming area full of noncommutative algebra is quantum information theory, and that is the main direction of current NCAlgebra development. Major contributions to NCAlgebra are being made by Mauricio de Oliveira and have also come from Mark Stankus and from many University of California San Diego students.


Australian Christian College

Accepted by: Jeremy Kwok, Director of Technology

Areas: Computer-Aided Education, Education

Australian Christian College (ACC) is Australia’s largest non-government distance education provider, with four schools equipped to provide a hybrid of in-house and fully remote learning. Covering K–12 education, its mission is to have all students flourish to their full potential and be a positive influence on the world. Rather than rely on traditional publishers, ACC wanted more consistent content for online and in-person assessment that showcases the ingenuity of their instructors.

ACC is now rolling out a Wolfram eLearning environment integration in their current Canvas environment. This integration will initially be used for assessments with 1,500 high-school students, which will quickly grow to 3,000 students and beyond as they implement the system for grades 7–12. With ACC’s announcement of a new STEM-focused campus in Western Sydney, this automated assessment system will be even more important in the future as enrollment continues to grow.


Alexandre Leite

Engineering Director & Mechatronics, Austral Dynamics

Areas: Control Engineering, Engineering, System Modeling

Alexandre Leite is a case of a PhD who became an entrepreneur. He currently holds a master’s and PhD in engineering and space technologies from Instituto Nacional de Pesquisas Espaciais and a degree in technology in automation from Instituto Federal Fluminense. He is experienced in the design of feasible mechatronic systems for several industry sectors and proportional–integral–derivative (PID) controllers.

He is a cofounder of Austral Dynamics, which started in 2017 as a spinoff of MWF Services. Austral developed its own hardware-in-the-loop platform called ASTURIAN. This technology allows engineers to use Functional Mock-up Unit (FMU) models generated by Wolfram System Modeler as real-time simulation mock-ups. Some applications are in agriculture machinery and commercial/heavy-duty vehicles. Currently, Austral is developing many business and technological initiatives in the field of electric powertrains for heavy vehicles.


Paul R. Garvey

Distinguished Chief Engineer/Scientist, The MITRE Corporation

Areas: Authoring and Publishing, Data Analysis, Data Analytics, Economic Research and Analysis, Modeling Dynamical Systems with Mathematica, Risk Analysis, Risk Management, System Modeling

Paul R. Garvey is a distinguished chief engineer/scientist at The MITRE Corporation, a not-for-profit organization operating federally funded research and development centers for the US government. He has decades of experience in systems operations research, network modeling, mission systems risk analyses, and the application of risk-decision analytics across a variety of problems in the federal government. His current work involves modeling the network structure of the US food supply chain, which is being done in collaboration with datasets and published studies by the University of Illinois Urbana-Champaign (UIUC) research team led by Professor Megan Konar.

Garvey has authored several textbooks, written numerous papers, holds a US patent, and continues to contribute his expertise and extensive Wolfram Language abilities to tackle big problems. One example is his work “US Food Supply Chain Security: A Network Analysis,” in conjunction with UIUC.

Utilizing Mathematica’s network modeling technologies, they identified critical US counties and links associated with the meat supply chain, which is characterized by 2,817 US counties (nodes) and 30,670 origin-to-destination links (edges) that exist between them.


The Geva Research Group, Compute-to-Learn Project

University of Michigan Ann Arbor, accepted by Ellen Mulvihill

Areas: Chemistry, Computational Thinking, Computer-Aided Education, Courseware Development, Education

The Compute-to-Learn project provides students with the opportunity to engage in creative forms of active learning. Compute-to-Learn activities stem from evidence-based, student-centered learning approaches, such as emphasis on real-world applications to promote students’ integration of new ideas, as well as authentic, collaborative environments that apprentice students as members of a scientific discipline (via practices such as explanatory writing and peer review). Students participate in tutorials and training related to Mathematica; research and propose an original Demonstration idea; workshop the idea during design and production stages; and, finally, submit the final product to external review prior to publication and dissemination on the Wolfram Demonstrations Project website. The Compute-to-Learn pedagogy is implemented within a peer-led honors studio environment. It has been offered in the University of Michigan chemistry department since 2015.


Tetsuo Ida

Professor Emeritus, University of Tsukuba

Areas: Computational Humanities, Geometry, Software Development

Tetsuo Ida is a professor emeritus in the department of computer science and faculty of engineering, informatics and systems for the University of Tsukuba.

Ida contributed greatly to expanding the use of computation in art, and is a pioneer of computational origami in particular. He and his team treat origami as a subject of art and a science and technology of shapes. They developed a software system called Eos (E-origami system) to reason about origami computationally. Eos is written in Wolfram Language and is available as a package for Mathematica.


Ricardo Martínez-Lagunes

Consultant, World Bank and Inter-American Development Bank

Areas: Civil Engineering, Data Analysis, Data Analytics, Data Science, Economic Research and Analysis, Environmental Engineering, Research and Analysis

Ricardo Martínez-Lagunes is a consultant for both the World Bank and the Inter-American Development Bank. His main professional activities currently focus on water resources policy, information systems for water resource management and environmental economic accounts and assessments.

Martínez-Lagunes is using Wolfram technologies to develop the next generation of computational water policy analytical tools to better understand and tackle challenges such as improving water utilities. In addition, he has demonstrated the ability to ingest large and disconnected datasets, compute and visualize that information more efficiently and create computationally dynamic dashboards for decision makers for policy design for investment/funding initiatives.


William A. Sethares

Professor, Electrical and Computer Engineering, University of Wisconsin–Madison

Areas: Computational Humanities, Computational Thinking, Computer-Aided Education, Courseware Development, Engineering, Image and Signal Processing, Image Processing, Signal Processing

Bill Sethares is a researcher and professor of electrical and computer engineering at the College of Engineering at the University of Wisconsin–Madison, focusing on signal processing with applications in acoustics, image processing, communications and optimization.

At the University of Wisconsin–Madison, Sethares attracts students from majors beyond engineering with his computationally rich image processing course material and project-based learning (all Wolfram Language–based, of course!). Sethares is a founding member of the LEOcode project and brings computation to art historians in the form of applications used to find patterns in watermarks and canvases. These can help to identify and date historical papers and paintings.


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.


Daniel Sze

Research Fellow, Georgia Pacific Innovation Center

Areas: Engineering, Modeling Dynamical Systems with Mathematica, System Modeling, Systems Engineering

Daniel Sze is a research fellow at the Georgia Pacific Innovation Center, working with dynamic system modeling to realize a new way to conduct research, tests and exploration in a much more cost-effective and timely way.

Sze’s work focuses on quickly building interactive design tools and dynamic system modeling of some of Georgia Pacific’s largest papermaking systems. Dan is currently supporting an initiative to model large papermaking machines using Wolfram System Modeler, producing a GUI to easily change parameters related to friction, torque, speed and other variables to better understand the way large papermaking machines function under those circumstances.



Telconet, accepted by Igor Krochin, Director

Areas: Business Analysis, Data Analysis, Data Analytics, Data Science, Economic Research and Analysis

Igor Krochin is the managing director of Telconet, the largest telecom company in Ecuador. They own some of the first certified cloud and data centers in Latin America, along with the first fiber-optic cable factory in the region.

Tomislav Topic and Krochin lead Telconet in implementing Wolfram Language solutions in a wide variety of areas, including events log correlations, route analysis and optimization, big data analysis and failure correlation, resulting in better planning and scalability. Telconet continues to build infrastructure and deploy services, including internet connectivity, that help students and educators in the region become empowered with Wolfram technologies, such as the Spanish version of Wolfram|Alpha, by accessing powerful and sophisticated computation from anywhere.


Dr. Girish Arabale

Founding Director, Scigram Technologies Foundation

Areas: Computational Thinking, Education, Software Development

Dr. Arabale is the founding director of Scigram Technologies Foundation, a not-for-profit education organization seeking to introduce a tinkering culture into the schools to foster creativity, excitement and innovation in science learning. At Scigram, Dr. Arabale teaches underprivileged children how to program using the Raspberry Pi. He also frequently speaks to children at the K–12 level to teach coding techniques using the Wolfram Language. Currently, Dr. Arabale is developing a computational learning platform and is working on a project known as “Computable City” that aims to make every aspect of the city’s ecosystem computable.


Bruno Autin

President, Les Trois Platanes

Areas: Authoring and Publishing, Computational Physics, Physics, Software Development

Bruno Autin started his professional life in the Laboratoire de Recherches Générales de la Compagnie Française Thomson Houston, where he studied the amplification of acoustic microwaves in cadmium sulfide. He strove to replace classical traveling wave tubes by tiny crystals, the scaling factor being the ratio between sound and light velocities. In 1967, he began working at the European Center for Nuclear Research (CERN), where his research turned quickly towards subnuclear physics with the development of very-high-energy accelerators. Bruno started with the first proton collider, the Intersection Storage Rings (ISR), and became introduced to the design and operation of the magnetic systems of accelerators and colliders. The basic theory had been established by Ernest Courant, but matching the architecture of colliders to particle detectors was largely a process of trial and error depending on numerical computations. Finding this to be unsatisfactory, he started testing symbolic languages. The first achievement was the shape of the CERN antiproton source calculated with Veltman’s Schoonschip. The saga of the antiprotons continued both at CERN and at Fermilab. Then, during a sabbatical year at Lawrence Berkeley National Laboratory, where he worked on the design of the Advanced Synchrotron Light Source, he tested the first release of Mathematica, which was packed with the NeXT computer. Having symbolics, numerics, graphics and the notebook interface convinced him to build two packages: Geometrica for geometry and BeamOptics for the investigation of optical systems adapted to projects such as beam emittance optimization for the Large Hadron Collider (LHC), muon colliders, neutrino factories and medical synchrotrons. Now retired from CERN, he follows the progress of particle physics and writes particle accelerator documentation for Wolfram Research.

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