O. Arda Vanli

O. Arda Vanli is a Professor in the Industrial and Manufacturing Engineering Department at the FAMU-FSU College of Engineering, jointly operated by Florida A&M University and Florida State University. His research bridges applied statistics, quality engineering, and data analytics to solve critical problems in manufacturing reliability, disaster resilience, and infrastructure safety.

Education:

• Ph.D. in Industrial Engineering and Operations Research, Pennsylvania State University (2007)
• M.S. in Mechanical Engineering, Pennsylvania State University (2000)
• B.S. in Mechanical Engineering, Middle East Technical University (1998)

Research Focus: Dr. Vanli specializes in variation reduction in manufacturing processes using statistical process control and feedback adjustment strategies. His work on uncertainty quantification addresses errors in computer models for composite manufacturing and wind energy systems, while his condition monitoring research develops sensor-based methods for damage identification using ultrasonic waves and piezoelectric sensors. Recent projects integrate spatiotemporal modeling with disaster response during hurricane-pandemics.

Publication Trends: His 2023-2025 publications reveal a strategic pivot toward interdisciplinary applications, combining transportation engineering, epidemiology, and materials science. Key themes include connected vehicle data for evacuation planning, Bayesian risk models for low-probability high-consequence events, and nanomaterial interfacial analysis under extreme conditions—demonstrating consistent methodological rigor in statistical modeling.

Scientific Recognition:

• Air Force Research Laboratory (AFRL) Summer Faculty Fellowship Program (SFFP) award (2019)
• Air Force Research Laboratory (AFRL) Summer Faculty Fellowship Program (SFFP) award (2020)
• Air Force Research Laboratory (AFRL) Summer Faculty Fellowship Program (SFFP) award (2021)

Research Leadership: Funded by NSF, NOAA, and Florida DOT, Dr. Vanli directs projects on risk assessment for infrastructure resilience and pandemic-disaster response systems. His role as former Director of Graduate Studies (2012-2016) underscores active mentorship in graduate education, with recent work emphasizing data-driven decision frameworks for public safety.

Technical Teams: He leads research groups developing statistical frameworks for sensor networks in manufacturing and infrastructure, focusing on real-time reliability prediction and adaptive maintenance protocols through collaborations with transportation and energy sectors.