Pictured from left: Rajendram Rajnarayanan, Ph.D., assistant dean of research and publications at NYIT-Arkansas; Pablo Lorenzo-Eiroa, associate professor of architecture; Dongsei Kim, M.Des., assistant professor of architecture; Ranja Roy, Ph.D., associate professor and chair of Math; Rozina Vavetsi, Ph.D., associate professor and chair of Digital Art and Design; Deborah Cohn, Ph.D., professor of marketing; Yusui Chen, assistant professor of physics; and Roger Yu, Ph.D., professor and interim chair of Physics.
Professor of Marketing Deborah Cohn, Ph.D., tried various qualitative tools to analyze research for her study on the use of social media in the workplace. “Ultimately, the best method has always been for me to read through the interviews myself and pull out what I need to pull out,” she says.
Cohn’s manual method of data analysis may be a thing of the past. In October 2019, along with several other New York Institute of Technology faculty members, Cohn attended the annual Wolfram Technology Conference in Illinois, gaining exposure to myriad uses of the computational software Wolfram Language.
Wolfram Language leverages computational machine learning with a vast depth of algorithms and meticulously curated data sets, allowing researchers to program information at a significantly higher level than has been conventional. In January 2019, the university acquired a site license for Wolfram Mathematica and Alpha Pro, making the software available to all faculty, staff, and students. Mathematica is commonly used for technical computing while Alpha Pro is more information based.
Cohn was astounded to see how Wolfram Language could be used to analyze Twitter—both what was being said across the platform on a specific topic and how individual Twitter feeds increased awareness and connected with wider audiences.
“It was mind-boggling what they were able to pull from Twitter and how they were able to analyze the data,” says Cohn. “Twitter has its own analytics tools, but the data sets are much smaller. Using Wolfram Language, you can combine those and have a huge dataset to analyze. I was excited to see that I might be able to write a code to pull out the insights from my data that I haven’t been able to do with other tools.”
She returned from the conference with an understanding of how Wolfram can be used in the field of marketing, with her own intent to learn the basics to code Wolfram Language and a plan to encourage her undergraduate students to master the program.
That was just what New York Tech President Hank Foley, Ph.D., was hoping for. “The goal is to foster computational thinking in all our majors, just as we do in engineering and computer science,” says Foley, who is author of Introduction to Chemical Engineering Analysis Using Mathematica (Wolfram Books, 2002). He believes computational thinking tools can help research, discovery, and creation beyond math and science and has made its emphasis an institutional goal.
“Many problems do not lend themselves to neat mathematical solutions,” he says. “Due to complexity, the solution needs to be algorithmic. Wolfram Language is rather easy to learn, so with a modicum of effort, a student in finance, economics, or social sciences—in addition to those in mathematics, physics, or chemistry—can learn to build models of increasing sophistication. Even students and scholars in literature and other humanities can use the Wolfram language to do a deep analysis of writing and large sets of data.”
Faculty from disciplines across campus took advantage of the opportunity to attend the Wolfram Conference.
“With many New York Tech departments represented at our annual Wolfram Technology Conference in 2019 (from architecture, to digital art and design, to math, and physics) I expect New York Tech graduates will now inject new computational ideas into their respective fields post-graduation, and more effectively contribute to new multidisciplinary fields by using Wolfram Language as the bridge between those fields,” said Stephen Wolfram, founder and chief executive officer of Wolfram Research.
Pablo Lorenzo-Eiroa, M.Arch., associate professor of architecture who uses both Mathematica and Alpha Pro in both spatial and materials design, became the first architect to present at a Wolfram Conference, with his presentation “e-Chaise Chair and Site Specific 3-D Printer.”
“Our e-chaise lounge chair’s design is based on certain periodical mathematical equations that we have been researching since we started using Mathematica back in 2004,” he says, explaining that mathematical equations provide a different type of means to design geometry than architecture software as their algorithms are often not open to editing.
Mathematica and Alpha Pro were used in the design of the e-chaise lounge chair, as well as a polymer-based filament and robotic cable-driven 3-D printer to fabricate the chair. “The polymer is designed to react at a certain temperature of the body when a person uses the chair, and thus acquire a slightly different form,” Lorenzo-Eiroa says.
Cheryl Gao, Ph.D., assistant professor of finance, used Wolfram Language for calculation in her quantitative finance research.
“Computational thinking is extremely important for quantitative finance, which has revolutionized trading strategies and the dynamics of financial markets,” she says. “For me, the conference was beneficial in terms of conducting quantitative research and teaching financial technology, as it incorporated the most contemporary issues in both areas.”
At the other end of the spectrum, Rozina Vavetsi, M.Sc., associate professor and chair of Digital Art and Design, had no exposure to Wolfram Language prior to attending the conference. She was sold.
“It was eye-opening,” she says. “Computational thinking is a must in the education of tomorrow’s generation. It’s a necessity when it comes to web design, game design, data visualization, graphic design, and interactive installations.”
Roger Yu, Ph.D., professor and interim chair of Physics, says the interdisciplinary make-up of the New York Tech faculty attending the conference was a reflection of the vast applications of Wolfram Language. “It can be used in any field; the speakers were artists, engineers, mathematicians, journalists, chemists, you name it,” he says.
Yu first used Mathematica in his own physics research after its launch in 1989. Now, he is helping the university integrate computational thinking across campus.
“It’s a way of formulating and approaching a problem by using computers to execute a solution,” he says. “With ever-increasing amounts of information available in our society, it’s increasingly important.”
Yu coordinated a faculty working group on Wolfram Language, created training workshops, and is in the process of developing Wolfram Language modules that will be integrated into required first-year mathematics and physics courses. The modules are being tested in select classes this spring and will be fully integrated in fall 2020. The goal is to expose all first-year students to the concept of computational thinking.
“Computational thinking is the next wave, and we want to instill the skill and habit in students to be able to harness the vast amounts of data available to solve problems,” he says. “It’s exciting.”
By Renée Gearhart Levy