Dr. Sinnu Susan Thomas
Post Doctoral Research Associate
Designing MacPherson Suspension Architectures using Bayesian Optimization
In this work, the authors develop a Bayesian optimization strategy for determining parameters of a MacPherson suspension system that optimizes desired performance characteristics of an automobile. In contrast to the industry standard of hand designed parameters, we aim to achieve partial automation of the design process by employing a multibody dynamics simulation model and allowing the Bayesian optimization to iteratively explore the design space without human intervention.
Sinnu Susan Thomas received her PhD degree in Electrical Engineering from Indian Institute of Technology Kanpur, India. She was teaching in India for the last nine years. Currently she is working with Department of Electrical Engineering KU Leuven Belgium with Prof. Matthew Blaschko on optimization techniques and applications of machine learning techniques.