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UW Crest with engineering background
January 9, 2023

PhD student brings statistical skills to helmet liner research

Written By: Tom Ziemer

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Abhijeet Bhardwaj is drawn to interesting problems where he can apply his statistical skills to unearth solutions.

So when a friend and fellow PhD student in the University of Wisconsin-Madison College of Engineering told Bhardwaj about a project devising an improved foam material for helmets, his interest was piqued.

Abhijeet Bhardwaj
Abhijeet Bhardwaj

Bhardwaj, a PhD student in industrial engineering, wound up conducting statistical analyses to support experimental work by researchers in the lab of Ramathasan Thevamaran, an assistant professor of engineering physics. The group published a paper in the journal Extreme Mechanics Letters detailing a lightweight, ultra-shock-absorbing material that could vastly improve helmets designed to protect people from strong blows.

“I have always felt that the underlying mathematics and statistics remains constant,” says Bhardwaj. “If you have a knowledge of that, you can go help people with their problems, be it from any domain.”

Bhardwaj, a member of E-Business Chair Professor Raj Veeramani’s research lab, was taking his final course toward adding a master’s degree in statistics to his CV (a common path in Veeramani’s group), which entailed a required collaborative project with other UW-Madison researchers.

Abhishek Gupta, a PhD student in Thevamaran’s lab and friend of Bhardwaj’s, had previously told him about their group’s challenge of trying to optimize design parameters for their carbon nanotube foam. After contacting Thevamaran and taking a month or so to review previous publications and familiarize himself with the context of the project, Bhardwaj began analyzing the group’s experimental data.

His work provided a statistical backing for the researchers’ testing of design parameters—thickness, inner diameter and gap between nanotubes—to achieve the best energy absorption.

In his PhD research, Bhardwaj is extracting useful textual data from manufacturing machine failure logs to derive prognostic analyses and guide maintenance decisions. It’s a drastically different application from the helmet liner research, which showcases the adaptability of industrial engineering methods across sectors.

“Industrial engineers face many problems, and industrial engineering is not specific to one kind of industry, not necessarily just manufacturing,” says Bhardwaj, who plans to pursue a research-oriented career after completing his PhD in May 2023. “It could be any industry with multiple problems.”