SPECIAL SESSION CHAIR

Probabilistic Models for Mechanical Systems

Dr. Arman Melkumyan
The University of Sydney, Australia

Abstract

In many engineering applications intrinsic randomness is present in the material properties (rock, soil, concrete, …), external loads (earthquake, wind, ocean wave, …) or geometry. Accounting for randomness and spatial variability in real world scenarios requires industrial application of systematically developed robust probabilistic models. This special session looks for contributions exploring real world stochastic mechanics problems employing state-of-the-art probabilistic models (machine learning, stochastic finite elements, pattern recognition, etc.).

Biography of the Special Session Chair

Dr Arman Melkumyan got his PhD majoring in Mechanics in 2005. In his PhD thesis he studies propagation and diffraction of waves in piezoelectric materials containing cracks and inclusions. He continued investigating dynamic problems in Mechanics at the Centre for Advanced Materials Technologies at the University of Sydney as a postdoctoral fellow. Since 2008 Dr. Melkumyan works at the Australian Centre for Field Robotics at the University of Sydney as a research fellow. His current research interests include stochastic mechanics and machine learning. Arman is an author of 22 refereed publications (14 journal and 8 conference proceedings) and two patent applications. He owns and maintains the machine learning web site www.GaussianProcess.com and the stochastic mechanics web site www.StochasticMechanics.com (under development).

Submissions

Please email all submissions to a.melkumyan@acfr.usyd.edu.au by October 27, 2009. Authors MUST include their full contact information in the email.