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Always patient and willing to help.
Makes learning a joyful experience.
Inspires students to love their studies.
Inspires students to aim high and excel.
A true gem in the academic community.
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About Qun
Associate Professor Qun Lin serves in the Department of Mathematics and Statistics, School of Electrical Engineering, Computing and Mathematical Sciences, Faculty of Science and Engineering at Curtin University, where she is also affiliated with the Centre for Optimisation and Decision Science. She earned her PhD in Applied Mathematics from Curtin University in June 2009, along with BSc and MSc qualifications. After completing her doctorate, she worked as a postdoctoral researcher in the Micromechanics of Granular Media Research Group at the University of Melbourne throughout 2009. She returned to Curtin University as a Research Fellow in the Department of Mathematics and Statistics from 2010 to February 2012, advanced to Lecturer from 2010 to 2015, and has held the position of Senior Lecturer since 2015, with promotion to Associate Professor. Her career trajectory reflects a commitment to advancing mathematical sciences through research and teaching in optimization-related fields.
Qun Lin's research interests span optimization, optimal control, granular materials, and computational mathematics. She develops and analyzes numerical methods for solving complex optimization and optimal control problems in engineering and industrial contexts. Key publications include 'The control parameterization method for nonlinear optimal control: A survey' (Journal of Industrial and Management Optimization, 2014, co-authored with Ryan Loxton and Kok Lay Teo), 'Optimal Control of Nonlinear Switched Systems' (2013), 'Parameter estimation for nonlinear time-delay systems with noisy output measurements' (Automatica, 2016), and 'Minimizing control variation in nonlinear optimal control' (Automatica, 2013). She collaborates frequently with researchers such as Ryan Loxton and Kok Lay Teo on computational techniques for nonlinear systems. Her contributions have influenced the field through highly cited works addressing practical challenges in scheduling, process control, and granular flows. Qun Lin teaches courses in mathematics and statistics aligned with her expertise.
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