RAMDO Leadership

Kyung K. Choi


Dr. Kyung K. Choi earned a B.S. in physics in 1970 at Yonsei University in Korea; and an M.S. in Mechanical Engineering in 1977 and Ph.D. in Applied Mathematics in 1980 both at the University of Iowa (UI). He is the Roy J. Carver Professor of Mechanical Engineering in the UI Department of Mechanical and Industrial Engineering. His research areas are reliability analysis, reliability-based design optimization, design sensitivity analysis, and mathematical theory of optimization and its applications.

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Dr. Choi’s dedicated efforts in research and service have garnered peer recognition resulting in several notable awards, including UI Faculty Scholar Award in 1987; Iowa Regents Award for Faculty Excellence in 2003; UI College of Engineering Faculty Excellence Award for Research in 2003; ASME Design Automation Award in 2006; UI Graduate College Outstanding Faculty Mentor Award in 2012; two ASME Best Paper Awards (2001 & 2003); and two ISSMO Best Paper Awards (2003 & 2007). He has co-authored 348 papers, including 147 journal papers in leading engineering journals. He has co-authored several graduate engineering texts (Design Sensitivity Analysis of Structural System, 1986; Methods of Engineering Mathematics, 1993; Design Sensitivity Analysis of Linear and Nonlinear Structural Systems – Two Volume, 2004).

At Iowa, Dr. Choi is a founding member of the Iowa Board of Regents-approved Center for Computer Aided Design (CCAD), where he has served as Associate Director (1990-93), Deputy Director (1993-95), and Director (1995-2003). He is an associate editor of five national and international journals. He is a Fellow of American Society of Mechanical Engineers (ASME), Fellow of Society of Automotive Engineering (SAE), Associate Fellow of American Institute of Aeronautics and Astronautics (AIAA), and President Elect of the International Society for Structural and Multidisciplinary Optimization (ISSMO, 2007-2011).

Nicholas Gaul


Dr. Nicholas Gaul received his Ph.D. in Mechanical Engineering from The University of Iowa in 2014. During his time there, he developed reliability analysis and surrogate modeling methods and completed his thesis titled, “Modified Bayesian Kriging for Noisy Response Problems and Bayesian Confidence-Based Reliability-Based Design Optimization.”

Dr. Gaul has extensive experience using high performance computing (HPC) systems, is a member of ASME (The American Society of Mechanical Engineers) and AIAA (The American Institute of Aeronautics and Astronautics), and has co-authored 10 journal/conference papers (Click here to view CV).

RAMDO History


Developed the Performance Measure Approach (PMA) in 1999. The paper received 582 citations in journal and conference papers.


Developed the Hybrid Mean Value Method (HMV) for RBDO in 2001. It received the 2001 ASME Black and Decker Best Paper Award at Pittsburg, PA. The paper received 426 citations in journal and conference papers.


Developed methods for efficient identification of feasible probabilistic constraints and fast reliability analysis using the condition of design closeness using HMV.  The paper received the ISSMO-Springer Prize 2003.


Developed the Enriched Performance Measure Approach (PMA+) for the RBDO process in 2004.  The paper received 191 citations in journal and conference papers.


Developed the Dimension Reduction Method (DRM) based RBDO for highly nonlinear systems.  The paper received the ISSMO-Springer Prize 2007.


Developed input modeling methods for correlated input variables using copula for RBDO.    The paper was a runner-up for the ISSMO-Springer Prize 2007.


The RBDO method was successfully demonstrated to provide an optimum design with approximately 20% reduction in weight, more than 10 times improved fatigue lives and 2-sigma reliable design of a U.S. Army Stryker A-arm in 2007.


Developed the Dynamic Kriging (DKG) method for surrogate models in sampling-based RBDO in 2010.


Demonstrated Iowa developed RBDO (I-RBDO) software at a workshop at the U.S. Army TARDEC in April 2011 with all attendees having successful hands-on experiences to solve example problems.


Developed an efficient variable screening method to mitigate the curse-of-dimensionality in surrogate models for RBDO in 2013.


With the success of I-RBDO, the team established a small start-up company, RAMDO Solutions, LLC, in fall 2013 to develop the commercial software Reliability Analysis & Multidisciplinary Design Optimization (RAMDO).


Developed the Confidence-Based RBDO (C-RBDO) method and Virtual Support Vector Machine (V-SVM) method for limited input data for input uncertainty modeling in 2014.


RAMDO Solutions successfully obtained an Army SBIR Phase I funding in May 2014 and Army SBIR Phase II funding in June 2015.

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