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.

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.

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.

2021

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.

2021

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.

2021

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.

2021

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.

2021

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.

2020

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.

2018

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.

2016

Brian Kanze

Georgia-Pacific

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.

2015

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.