First-year engineering student places first in ‘Places and Spaces: Mapping Science’

Three other engineering students are winners

Two student projects—one using an interactive webpage that explores the complexity of sorting algorithms, and the other a study of human movement over space and time —were the top winners in a Vanderbilt student data visualization competition held April 13 in conjunction with the campus exhibition Places and Spaces: Mapping Science.

The student competition was the final in a series of activities held this semester during the exhibition, which remains open in Vanderbilt’s Sarratt Student Center, Rand Hall, the Wond’ry, and the Central Library through April 23.

Blake Quigley

The Best Data Visualization by an Undergraduate Student award went to Blake Quigley, a first-year student who is majoring in computer science in the School of Engineering, for exploring the complexity and nuances of sorting various algorithms with his interactive webpage.

Other undergraduate student winners were Trent Sexton, civil engineering senior, second place; Ashley Rivera, civil engineering junior; and Leyao Yu and Lin Fei, both math and psychology double majors in the College of Arts and Science, tied for third place.

Quigley used the example of sorting five numbers in increasing order. “Ostensibly, this is a problem so trivial that no one would even bother to write it out,” he said. “Yet, beneath these billions of neurons that we call human intellect and intuition, would it be so easy to write out exact instructions capable of sorting any list? A human programmer must think with this level of scrupulous introspection to translate the brain’s abstract thoughts into machine code. A sorting algorithm is just one specific set of instructions that computer scientists have invented to consistently sort a list of numbers.”

The generated graphs on Quigley’s webpage show the size of a task on the x-axis and the time it takes to complete the task on the y-axis. “My website, along with a backbone of C++ and R computer programming languages, lets users choose from four sorting algorithms, six different data distributions, four different viewing modes and three different ‘order of complexity’ best-fit lines to understand the real-world, industry efficiency of different sorting algorithms in different situations.”

Examples Quigley gave of the need to sort big data could be an attorney with a corporate email account that has millions of emails that must be arranged chronologically, or a telescope that automatically sorts data by the likelihood of containing an Earth-like planet. “In these situations, the need to sort large arrays, or lists, becomes paramount,” Quigley said.

Ben Shapiro, a doctoral student in Teaching and Learning at Peabody College, received first place for Best Data Visualization by a Graduate or Professional Student for an entry related to his dissertation, “Interaction Geography.” One component of his project demonstrates how a 6-year-old boy runs back and forth across a museum gallery space in a frantic effort to lead his sister’s fiancé on a “pedagogical tour” of other exhibits there.

A second part of Shapiro’s project illustrates new types of technologies and collaborations with community partners to map people’s movement and conversation over space and time in relation to the design of physical spaces. “These maps can be used to organize complex forms of research data to address challenges like observing 12 children playing simultaneously in up to six different areas of the preschool classroom or playground,” said Shapiro, who is a member of Vanderbilt’s Space, Learning and Mobility Lab.

Other graduate and professional student winners were Ben Skinner, Department of Leadership, Policy and Organizations, Peabody College, second place; Qian Weiqiang, Department of Psychological Sciences, Peabody College; and Kate Brady, a graduate student in computer science, School of Engineering; tied for third place.

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