PI spotlight: Hadi Meidani

Hadi Meidani is an assistant professor in the Department of Civil and Environmental Engineering (CEE) at the University of Illinois at Urbana-Champaign (UIUC). 

He leads the Uncertainty Quantification (UQ) Group at UIUC. The UQ Group focuses on addressing the issue of uncertainty in the optimal management of infrastructure systems and structures by developing advanced machine learning techniques and statistical methods. Meidani’s research has been applied on problems in structural engineering, transportation engineering, materials modeling, and energy systems. He has been published in prestigious journals in civil engineering, mechanical engineering, and computational mechanics.

Meidani is currently studying reliable crowdsourcing for participatory wind damage assessment where he uses advance coding theory methods to build a damage assessment tool that is robust to the unreliability of ordinary citizens. His other active projects include data-driven prediction of rail track geometry defects, optimal infrastructures for autonomous truck traffic, and real-time, data-driven analysis of interdependent infrastructure systems.

Meidani earned his Ph.D. in civil engineering along with a master of science in electrical engineering from the University of Southern California (USC) in 2012. He holds a bachelor of science in civil engineering from K.N. Toosi University of Technology in Iran, which he earned in 2002, and a master of science in structural engineering, which he earned at Sharif University of Technology in 2005.

Meidani was also a postdoctoral scholar in the Department of Aerospace and Mechanical Engineering at USC from 2012-2013, and a postdoctoral research associate in the Scientific Computing and Imaging Institute at the University of Utah from 2013-2014.