2022

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.

2022

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.

2022

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.

2022

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.

2022

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.

2022

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.

2022

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.

2022

Telconet

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.