WOLFRAM

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.

Presented at the Wolfram Technology Conferences. Learn more

2019

Mihai Vidrighin

R&D Lead, PsiQuantum

Areas: Electrical Engineering, Image Processing, Physics, System Modeling

Mihai Vidrighin is a researcher in photonics who has used Mathematica extensively throughout his career. During his PhD thesis, he used Mathematica to run simulations and data analytics involving quantum thermodynamics, and he continues to recommend the system to colleagues. He currently leads a team developing a photonics component for generating single photon pairs with new accuracy and scale. In this project, he has used the Wolfram Language to build an extremely comprehensive model for nonlinear and quantum optics to describe photon-pair generation and quantum optics circuits. Vidrighin has also written several Wolfram Language packages for quantum optics simulation and electron microscope image processing.

2019

Dr. Jane Shen-Gunther

Doctor, Brooke Army Medical Center

Areas: Biomedical Research, High-Performance and Parallel Computing, Image and Signal Processing, Machine Learning, Molecular Biology

Dr. Jane Shen-Gunther is a medical doctor and researcher for the US Army, specializing in gynecologic oncology and obstetrics. She recently started using Mathematica and the Wolfram Language to advance her team’s research in HPV detection, automating the analysis of several gigabytes of image and instrument data and generating interactive visual reports for both patients and physicians. Dr. Shen-Gunther has also deployed her predictive model in the Wolfram Cloud to share access with other physicians. Her work has led to improved patient interactions, as well as better prediction of pap outcomes that impact underdeveloped countries.

2019

Robert Rasmussen and Kirk Reinholtz

Senior Engineers, Jet Propulsion Laboratory

Areas: Aerospace, Control Engineering, High-Performance and Parallel Computing, Probability Theory, Risk Analysis, Software Development, Systems Engineering

Robert Rasmussen and Kirk Reinholtz are systems engineers who have used the Wolfram Language to develop a set of methodologies for building complex control system applications. Their integrated mission operation systems utilize the Wolfram Language to provide live updates to local data stores, keeping information consistent throughout processes. Both have used Mathematica extensively for large probability and engineering computations—including hundred-day distributed computations and the processing of gigabyte-scale datasets. They evangelize Mathematica and the Wolfram Language to others in the aerospace field, encouraging them to use Wolfram Notebooks for exploration and the expression of ideas.

2019

Flip Phillips

Professor of Motion Picture Science, Rochester Institute of Technology

Areas: Computational Humanities, Computational Thinking, Computer Graphics and Visual Arts, Education, Machine Learning

Flip Phillips is a professor, researcher and former Pixar animation scientist who uses Wolfram technology to integrate real-world computation into his psychology and neuroscience curriculum. Through his course, students get unique hands-on experience with computational thinking and machine learning, completing cross-disciplinary projects ranging from predicting voter behavior to identifying fruit from sensor readings. Phillips makes use of Wolfram connected devices for gathering data and frequently publishes his work in the Wolfram Cloud. He has used Mathematica extensively for his research on perception, psychological aesthetics and cortical plasticity. He has also written several packages for extending the Wolfram Language’s rendering capabilities.

2019

Casey B. Mulligan

Professor of Economics, Becker Friedman Institute, University of Chicago

Areas: Computational Humanities, Economic Research and Analysis, Economics, Software Development

Casey Mulligan is a renowned economist who has served as chief economist for the White House Council of Economic Advisors, a visiting professor at several universities and a research associate for the National Bureau of Economic Research. He frequently uses the Wolfram Language in his economic research and has published numerous papers that utilize Mathematica computations and visualizations. Mulligan has additionally developed a Wolfram Language package that provides unique functionality for automated economic reasoning using both quantitative and qualitative assumptions.

2019

Dr. Joo-Haeng Lee

Senior Research Scientist, Electronics and Telecommunications Research Institute

Areas: Computer Graphics and Visual Arts, Computer Science, Machine Learning

Dr. Joo-Haeng Lee is a researcher specializing in human-machine interaction, robotics and computational art. He has used Mathematica to develop several unique geometric algorithms for camera calibration and Bézier curves/surfaces. Most recently, he utilized the Wolfram Language to develop PixelSwap, an algorithm for pixel-based color transition that can be used for both aesthetic images and synthetic learning sets for deep learning. Dr. Lee regularly uses Mathematica visualization for technical illustrations and his artworks for exhibitions.

2019

Chris Hanusa

Associate Professor of Mathematics, PhD, CUNY Queens College

Areas: 3D Printing, Computer Graphics and Visual Arts, Mathematics, Mathematics Courseware Design

Chris Hanusa is a professor at Queens College in Queens, New York, teaching classes on calculus, mathematical modeling, graph theory and more. He makes extensive use of Mathematica to help his students with complex calculations and for visualizing difficult concepts. In his Math with Mathematica course, Hanusa works with students on several Mathematica-based projects, including 3D modeling and printing. He gives regular talks on teaching with Mathematica, emphasizing the importance of the Wolfram Language’s 3D printing capabilities.

2019

Todd Feitelson

Math Teacher, Millbrook School

Areas: 3D Printing, Computer Graphics and Visual Arts, Mathematics, Mathematics Courseware Design

Todd Feitelson teaches mathematics at Millbrook School in Millbrook, New York, and has been using Mathematica to build a new hands-on curriculum for his high-school students. His unique projects and problem sets bring math to life, using the Wolfram Language’s 3D modeling and printing capabilities to design and print polyhedrons, chessboards, rockets and more. Feitelson has presented his results at several conferences, showcasing Mathematica’s usefulness for creating these interactive problem sets.

2019

Tom Burghardt

Emeritus Professor of Biochemistry, Mayo Clinic Rochester (Department of Biochemistry and Molecular Biology)

Areas: Biomedical Research, Education, Machine Learning, Molecular Biology

Tom Burghardt is a researcher at the #1 ranked Mayo Clinic, where he has spent the last three decades studying myosin and muscle tissue. In his 100+ publications, he uses Mathematica extensively for advanced statistics and modeling—tracing all the way back to a 1985 signal processing computation done in SMP, a precursor to Mathematica. Burghardt’s most recent innovation uses feed-forward neural networks developed in the Wolfram neural net framework to help create models for inheritable heart disease using a worldwide database of cardiac muscle proteins. His ultimate goal is to make these models available in the Wolfram Cloud for other researchers to explore and use.

2019

Dr. Yehuda Ben-Shimol

Senior Lecturer, Ben-Gurion University of the Negev (Communications Systems Engineering Department)

Areas: Education, Engineering, System Modeling, Systems Engineering

Yehuda Ben-Shimol has taught courses in graph theory, queueing theory, information theory and more using Wolfram technologies. Using Mathematica and Wolfram SystemModeler, he developed a series of “virtual labs” that allow hands-on exploration of complex engineering models. Through his published work and ongoing community engagement, Ben-Shimol has exposed thousands of students and faculty members to the benefits of using Wolfram technology in coursework and research.

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