Dr. Feeley's areas of expertise include automatic control systems, machine design, optimization, and computer modeling and simulation. He is experienced in the integration of sensors and controls with mechanical systems, and is skilled in the design of control systems and the study of their safety and performance. His background also includes research in computational science and the development of simulation models for systems biology.
During his undergraduate studies, Dr. Feeley developed a control system for a rotating TIG welding machine and evaluated sensors for obtaining feedback information on the weld bead. He participated in the tuning and preproduction testing of a digital valve controller, and designed the hardware and baseline control system for an unmanned unicycle that was constructed to test and evaluate nonlinear control algorithms.
Prior to joining Exponent, Dr. Feeley attended the University of California, Berkeley, where he conducted research on computational science and simulation. Dr. Feeley’s research focused on the validation of complex simulation models and the use of such models to make reliable scientific predictions. This work involved a combination of parameter estimation, uncertainty quantification, optimization, and statistics, and was applied to diverse areas including combustion kinetics, atmospheric chemistry, and systems biology.
Dr. Feeley also has experience using machine tools and other shop equipment. He participated in the design and fabrication of a solar car at Kansas State University that placed 5th in the 2001 American Solar Challenge. He has rebuilt motorcycle and automotive engines and transmissions and has designed and fabricated numerous mechanical devices. Additionally he has operated heavy construction equipment.
Feeley R. Fighting the curse of dimensionality: A method for uncertainty propagation and validation of complex simulation models. Ph.D. Dissertation, University of California, Berkeley, 2008.
Feeley R, Frenklach M, Onsum M, Russi T, Arkin A, Packard A. Model discrimination using Data Collaboration. J Phys Chem A 2006; 110:6803–6813.
Feeley R, Seiler P, Packard A, Frenklack M. Consistency of a reaction dataset. J Phys Chem A 2004; 108:9573–9583.
Russi T, Packard A, Feeley, R, Frenklack M. Sensitivity analysis of uncertainty in model prediction. J Phys Chem A 2008; 112:2579–2588.
Smith GP, Frenklack M, Feeley R, Packard A, Seiler P. A system analysis approach for atmospheric observations and models: the mesospheric HOx dilemma. J Geophys Res 2006; 111:D23301.1–D23301.8.
Seiler P, Frenklack M, Packard A, Feeley R. Numerical approaches for collaborative data processing. Optimization and Engineering 2006; 7:459–478.
Jarvis-Wloszek Z, Feeley R, Tan W, Sun K, Packard A. Some controls applications of sum of squares programming. Proceedings, 42nd IEEE Conf Dec and Contl 2003; 5:4676–4681.
Frenklack M, Packard A, Seiler P, Feeley R. Collaborative data processing in developing predictive models of complex reaction systems. Int J Chem Kinet 2004; 36:57–66.
Book Chapters
Frenklack M, Packard A, Feeley R. Optimization of reaction models with solution mapping. In: Comprehensive Chemical Kinetics. Elsevier, Volume 42, 2007.
Jarvis-Wloszek Z, Feeley R, Tan W, Sun K, Packard A. Control applications of sum of squares programming. In: Positive Polynomials in Control. Springer-Verlag, 2005.
Selected Presentations
Feeley R, Russi T. Small models and short proofs (the wrong way). Presented at Connections II: Fundamentals of Network Science, Pasadena, CA, August 18, 2006.