2024

Thomas Wallek

Associate Professor, Graz University of Technology

Areas: Chemical and Process Engineering, Chemical Thermodynamics, Education

Thomas Wallek’s area of expertise is chemical thermodynamics and its application in chemical and process engineering, for which he uses Wolfram as an essential standard tool for both research and teaching. In his research, he focuses on thermodynamic modeling, the estimation of physical property data, the characterization of complex mixtures and molecular simulations.

In this context, his workgroup has been developing a Gibbs-ensemble Monte Carlo simulation program completely implemented in Wolfram, which is constantly being further developed and benefits from the diverse visualization and evaluation capabilities of Wolfram Language. In the context of teaching, Wallek is committed to the Technology Enhanced Learning (TEL) Marketplace initiative of Graz University of Technology that focuses on the development and scaling of TEL innovations for teaching. In particular, Wolfram Notebooks were created as the basis of a chemical thermodynamics course that was designed in the “inverted classroom” concept and enables students to acquire the material independently through self-study. For this purpose, manipulable diagrams and animated equations were integrated into the notebooks, with which students can interact and learn independently.

2024

David G. Stork

Stanford University

Areas: Computer Graphics and Visual Arts, Computer-Aided Education, Engineering, Image Processing, Machine Learning, Materials Science, Mathematics, Visualization

David G. Stork is an adjunct professor of electrical engineering, symbolic systems and material science and engineering, as well as an adjunct lecturer in computational mathematics and engineering at Stanford University, where he considers Mathematica to be a valuable teaching tool and resource. Here, he developed and teaches Computational Symbolic Mathematics, a Mathematica-based course for using computer algebra for solving difficult non-numerical mathematical problems. Stork is a graduate in physics from the Massachusetts Institute of Technology (MIT) and the University of Maryland. He has held faculty positions at Wellesley and Swarthmore Colleges; Clark, Boston and Stanford Universities; and the Technical University of Vienna. Stork has been a long-time friend of Wolfram, using Mathematica in teaching and research. He holds 64 US patents and has published over 220 scholarly papers and nine books and proceedings volumes, including Pattern Classification, Second Edition and Pixels & Paintings: Foundations of Computer-Assisted Connoisseurship.

2024

José Guillermo Sánchez León

Instituto Universitario de Física Fundamental y Matemáticas

Areas: Applied Mathematics, Authoring and Publishing, Authoring in Mathematica, Computational Thinking, Computer Science

José Guillermo Sánchez León worked in the nuclear industry for over 30 years while simultaneously teaching as an associate professor at the Universidad de Salamanca. He is recently retired but continues as a researcher at the Instituto Universitario de Física Fundamental y Matemáticas (IUFFyM) of the Universidad de Salamanca, participating in a diverse array of research projects and publications. Furthermore, he conducts research on the history of medieval astronomy, using the extensive classic books of the Biblioteca General Histórica of the Universidad de Salamanca (BGH).

In his mind, Wolfram Language is a fundamental tool. In the summer of 1999, he was a visiting scholar at Wolfram Research and since then has collaborated on prerelease test processes. Guillermo Sánchez also gives seminars and training courses on Mathematica. He is the author of the book Mathematica Beyond Mathematics: The Wolfram Language in the Real World, where he shares examples from his experience using and teaching Wolfram Language, and even has a radio program (EUREKA).

2024

Sebastian Mizera

Princeton University

Areas: Education, Physics, Quantum Field Theory, Theoretical Physics

Sebastian Mizera is a theoretical physicist studying quantum field theory and gravitational physics. He is currently a postdoctoral researcher at Princeton University and an affiliate at the Princeton Center for Theoretical Science and the Institute for Advanced Study. His research aims to understand the nature of interactions between fundamental objects, ranging from elementary particles to black holes. He is particularly interested in how physical principles, such as causality, locality and unitarity, are encoded in the analytic structure of asymptotic observables in quantum field theory.

Wolfram Language is the bedrock of symbolic computations in the field of theoretical high-energy physics. Mizera employs it in his daily research on quantum field theory, but also in higher education. Recently, he incorporated Wolfram Language in the graduate course Physics of the Analytic S-Matrix given at the Higgs Centre School of Theoretical Physics at the University of Edinburgh. The software was used to illustrate complex concepts behind scattering theory on hands-on examples.

2024

Andrew Lütken

Technology Innovation Institute (TII)

Areas: Mathematics, Modeling Condensed Matter Systems Using Tools From String Theory, Quantum Computing, Quantum Field and String Theory

After obtaining his PhD at the University of Texas at Austin, Andrew Lütken worked at the European Organization for Nuclear Research (CERN), the Nordic Institute for Theoretical Physics (Nordita), the University of Oxford, Institut de Fisica d’Altes Energies (IFAE) at the Universitat Autònoma de Barcelona (UAB) and the University of Oslo, where he has been a professor of physics for 30 years. He is now the executive director of the Quantum Computing Lab at the Technology Innovation Institute (TII) in Abu Dhabi.

Lütken has used Wolfram extensively in particle physics, quantum field theory and the analysis of ground state strings (the construction and classification of Calabi–Yau manifolds). Together with the late Graham Ross (University of Oxford), he has shown that a new type of “modular” symmetry appears in nature (in the quantum Hall effect). He has recently built the first quantum computing lab in the Middle East and North Africa (MENA) region, including a chip foundry that has fabricated the first quantum computers in this part of the world.

2024

Pedro Fonseca

SUEZ

Areas: Computational Thinking, Engineering, Image Processing

Pedro Fonseca earned his degree in environmental engineering with a specialization in sanitary engineering from Universidade NOVA de Lisboa, Portugal. He has since built an international career focused on the detailed engineering of water treatment plants within the SUEZ Group, with professional experiences in Paris, France; Virginia, United States; and Lisbon, Portugal. Since 2012, Fonseca has managed the hydraulic discipline, contributing significantly to the research and development of new products and leading the basic and detailed hydraulic design of water treatment plants around the world.

Fonseca’s passion for education drives his engagement with Wolfram Language, which he first encountered in 2006 (Version 5.2) while pursuing a second degree in applied mathematics. Over the years, he has integrated Wolfram technologies, including Mathematica and System Modeler, into various aspects of his work and personal projects. These tools play a crucial role in his product development efforts, such as data mining, algorithm development and the creation of digital twins for design verification and optimization. Fonseca has also actively participated in multiple Wolfram Research activities, primarily in France, including boot camps, summer schools and product demonstrations.

2024

Robert Feger, Thomas Kephart, Robert Saskowski

Developers of LieART

Areas: Gravity, Particle Physics, Physics, Quantum Entanglement, Research and Analysis, Software Development, String Theory, Theoretical Physics

Robert Feger, Cocreator of LieART and Researcher, Deutscher Wetterdienst
Robert Feger is a researcher and developer at the Deutscher Wetterdienst, Germany’s national meteorological service, specializing in thunderstorm and convection detection in weather radar data. As a particle theorist, he used Wolfram extensively in his PhD studies on heavy-quark physics at the University of Siegen. During his postdoctoral fellowship by the German Academic Exchange Service at Vanderbilt University, Feger worked on grand unified theories based on special unitary groups. His research required fast and demanding calculations in group theory. Initially created as a group theory toolbox for personal use, Feger, mentored by Tom Kephart, created LieART, a Wolfram application for Lie algebras and representation theory. LieART has been appreciated by particle physicists and mathematicians for its user-friendly interface and computational power covering all classical and exceptional Lie algebras. It can also be used as a group theory teaching tool as the output and visualizations, e.g. of Dynkin diagrams and weight and root systems, are akin to textbooks—all enabled by the very same core principles of Wolfram.

Thomas Kephart, Cocreator of LieART and Professor of Physics, Vanderbilt University
Thomas Kephart is a particle theorist and has worked on formal aspects of gauge theories, particle physics models and group theory. Some topics include chiral gauge anomalies, topological defects and extensions of the standard model, including grand unification, family symmetry, discrete symmetry and string-inspired models. Wolfram has been an indispensable tool in his research for many years. The applications have ranged from particle physics model building to the classification of quantum entanglement to theoretical biophysics.

Many branches of science seem poised for great advances as machine learning, artificial intelligence and quantum computing converge. Most recently, in a study of coherent states from the solar corona, Kephart has used AI to write Wolfram Language code to analyze the signal-to-noise ratio expected in detectors. He also finds Wolfram a great help in mentoring students, as by learning to use it, they can quickly make useful contributions to research projects.

Robert Saskowski, Cocreator of LieART and Researcher, Tianjin University
Robert Saskowski is a postdoctoral researcher in the Center for Joint Quantum Studies at Tianjin University studying string theory and related topics. He specializes in higher-derivative supergravity and precision holography. His undergraduate thesis involved working on LieART, a powerful Wolfram application for doing computations with Lie algebras and their representation theory, and implementing branching rules therein.

2024

Europa Clipper Technical Resources Modeling Team

Jet Propulsion Laboratory

Areas: Aerospace, Computational Physics, Data Analysis, Data Analytics, Engineering, System Modeling, Systems Engineering

David Wagner, Andres Rivera, Emma Dodd, Narek Shougarian, David Coren and Reidar Larsen, members of the Europa Clipper project system engineering team at Jet Propulsion Laboratory (California Institute of Technology), used Wolfram Language and System Modeler as part of a large multiphysics simulation system used to validate requirements against performance of the design of the spacecraft intended to probe subsurface water on Jupiter’s moon Europa. Analysis provided by these models enabled the project to zero in on a workable design for an extremely complex mission and validate that it could achieve the mission’s aggressive requirements. The models continue to be used to validate mission plan updates into operations.

2024

Fei Du

Associate Professor of Accountancy, Gies College of Business, University of Illinois at Urbana-Champaign, and Associate Academic Director, Center for Professional Responsibility in Business and Society

Areas: Accounting Analysis, Computational Thinking, Data Analytics, Financial Analysis

Fei Du is an associate professor of accountancy at the Gies College of Business, University of Illinois Urbana-Champaign. Her research focuses on the interaction between users and designers of managerial accounting systems and has been published in top academic journals, including The Accounting Review, the Review of Accounting Studies, Contemporary Accounting Research, the Academy of Management Journal and the Journal of Management Accounting Research.

Du teaches courses in data analytics at the graduate level, emphasizing computational thinking and decision making. She leverages Wolfram Language for its powerful capabilities in accessing curated financial and socioeconomic data, which complements traditional accounting metrics. She also integrates real-world capital market events, news and case studies to enhance students’ understanding of business insights.

Du is also the author of Creative Data Analytics: Computational Recipes to Gain Insights into Businesses, published by Wolfram Media. This book features a mouse-driven interface that allows students to input data—ranging from website URLs to images and PDF files—and generate real-time computational results. Her innovative teaching approach integrates text and images from websites, CEO portraits and financial reports, blending traditional financial spreadsheet tools with advanced computational capabilities powered by Wolfram Language.

2024

Mauro Da Lio

Professor, Università degli Studi di Trento

Areas: Artificial Cognitive Systems, Intelligent Vehicles, Robotics

Mauro Da Lio is a full professor of mechanical systems at the Università degli Studi di Trento, Italy. He has been a long-time user of Mathematica since Version 6, notably using it in earlier research of modeling, simulation and optimal control of mechanical multibody systems, particularly vehicle and spacecraft dynamics. More recently, his focus shifted to modeling human sensory-motor control with applications in health, robotics and, mostly, intelligent vehicles.

He was involved in several EU framework program projects (PREVENT, Saferider, interactIVe, VERITAS, AdaptIVe, No-Tremor and SUNRISE). Professor Da Lio was the coordinator of the EU Horizon 2020 Dreams4Cars research and innovation action: a collaborative project in the robotics domain that aimed at increasing the cognition abilities of artificial driving agents using offline simulation mechanisms broadly inspired by the human dream state (the learning of forward models and offline synthesis of inverse ones).

2024

Michael Berry

Melville Wills Professor of Physics (Emeritus), University of Bristol

Areas: Divergent Series, Natural Optical Phenomena, Phase, Physical Asymptotics, Physics of Waves

Michael Berry is a theoretical physicist at the University of Bristol, where he has been for more than twice as long as he has not. His research centers on the relations between physical theories at different levels of description (classical and quantum physics, ray optics and wave optics), emphasizing the singularities at different levels. Wolfram has been his tool of choice for all the numerics and graphics in nearly two hundred research papers since 1988. In addition to these deeply mathematical, often geometric studies, he also delights in finding familiar phenomena illustrating deep concepts—the arcane in the mundane: rainbows, the sparkling of the sun on the sea, twinkling starlight, polarized light in the sky and tidal bores.

2024

Héctor Benítez Pérez

IIMAS-DGTIC Universidad Nacional Autónoma de México

Areas: Computer-Aided Education, Courseware Development, Data Science, Education, Research and Analysis

Dr. Héctor Benítez Pérez graduated with honors in electrical mechanical engineering from the Faculty of Engineering at the Universidad Nacional Autónoma de México (UNAM) and pursued his doctorate at the University of Sheffield in the Department of Automatic Control and Systems Engineering. Within UNAM, he served as the head of the Institute for Research in Applied Mathematics and Systems (IIMAS) from 2012 to 2020 and is currently the head of the General Directorate of Computing and Information and Communication Technologies (DGTIC). Additionally, he serves as a representative to various official organizations, both national and international.

Benítez Pérez has worked as a researcher in the field of control systems. He has played a pivotal role in organizing UNAM systemwide Wolfram training and communication events, providing invaluable opportunities for students, faculty and researchers to advance their work in science and technology. His contribution to academic training is highlighted by the creation of the bachelor’s degree in data science, the specialty in high-performance computing and its integration into UNAM’s Continuing Education Network (REDEC), which formalizes collaboration in continuing education activities and has led to the offering of a course at the IIMAS Academic Unit in the state of Yucatán.

In collaboration with IIMAS, the UNAM Institute of Mathematics, Centro Virtual de Computación (CViCom), the French Embassy in México, the Ministry of Foreign Affairs, Huawei México and the German Cooperation Agency, he has participated in organizing forums, workshops and meetings aimed at promoting research development in México in the field of artificial intelligence. He has supported many Wolfram training and communication events. His efforts have offered room for students, faculty and researchers space to continue research in science and technology.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.

2023

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.