ISE researcher awarded simulation fellowship

Published: Jul 23, 2025 3:40 PM

By Carla Nelson

The Auburn University Department of Industrial and Systems Engineering has selected Shehzaib Irfan as the recipient of the 2025 Chapman Foundation Simulation Fellowship in recognition of his research in simulation and data-driven modeling.

Irfan’s work focuses on improving fatigue life prediction of additively manufactured parts using advanced statistical and machine learning techniques.

He earned a bachelor’s degree in aerospace engineering from the National University of Sciences and Technology in Pakistan in 2011, followed by a master’s degree in 2018. He is currently pursuing a master’s in applied mathematics and a doctorate in industrial and systems engineering at Auburn.

“I was trained as an aerospace engineer during my undergraduate studies and have an appreciation for solving complex, interdisciplinary problems, especially those that can lead to tangible improvements in efficiency and safety,” Irfan said. “Industrial and systems engineering sits at the intersection of decision-making and real-world systems, and I believe it will give me the tools to make them better, smarter and more resilient.”

Irfan’s long-term goal is to develop innovative solutions to real-world problems across multiple domains.

“I hope to lead efforts that bridge simulation, decision science and systems thinking to improve the performance and sustainability of engineering systems,” he said. “I’m particularly passionate about translating research into practice, where it can drive impactful change.”

He added that receiving the Chapman Foundation Simulation Fellowship is a significant milestone in his academic journey.

“The fellowship will allow me to focus on my research and dedicate more time to advancing it,” he said. “It will also give me opportunities to attend conferences, participate in research workshops and connect with peers in the field. I am grateful to the department for placing its trust in me to contribute meaningfully to industrial and systems engineering.”

 

Media Contact: Carla Nelson, cmn0023@auburn.edu, 334-844-1404
Irfan’s work focuses on improving fatigue life prediction of additively manufactured parts using advanced statistical and machine learning techniques.

Irfan’s work focuses on improving fatigue life prediction of additively manufactured parts using advanced statistical and machine learning techniques.

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