The Alan Tayler Lecture 2017: Optimization in the Darkness of Uncertainty
On Monday 20th November 2017, St Catherine's College Oxford together with The Smith Institute, will welcome Kate Smith-Miles, Professor of Applied Mathematics at University of Melbourne to give the 2017 Alan Tayler Lecture entitled, 'Optimization in the Darkness of Uncertainty: when you don't know what you don't know, and what you do know isn't much!'.
St Catherine's College has a long tradition in applied and industrial mathematics, and has hosted an annual series of lectures on Mathematics and its Applications since 1986. In 1995, the series was renamed in memory of Alan Tayler, in tribute to his efforts and achievements in this field. Alan was the first Fellow in applied mathematics to be appointed at St Catherine's. His lifelong commitment was to the practical application of mathematical ideas to problems in science and industry. His vision continues to inspire many national and international collaborations on the theme of mathematics-in-industry.
Many industrial optimisation problems involve the challenging task of efficiently searching for optimal decisions from a huge set of possible combinations. The optimal solution is the one that best optimises a set of objectives or goals, such as maximising productivity while minimising costs. If we have a nice mathematical equation for how each objective depends on the decisions we make, then we can usually employ standard mathematical approaches, such as calculus, to find the optimal solution. But what do we do when we have no idea how our decisions affect the objectives, and thus no equations? What if all we have is a small set of experiments, where we have tried to measure the effect of some decisions? How do we make use of this limited information to try to find the best decisions?
This talk will present a common industrial optimisation problem, known as expensive black box optimisation, through a case study from the manufacturing sector. For problems like this, calculus can’t help, and trial and error is not an option! We will introduce some methods and tools for tackling expensive black-box optimisation. Finally, we will discuss new methodologies for assessing the strengths and weaknesses of optimisation methods, to ensure the right method is selected for the right problem.
Kate Smith-Miles holds an Australian Laureate Fellowship (2014-2019) from the Australian Research Council, and is a Professor of Applied Mathematics at The University of Melbourne. She was previously Head of the School of Mathematical Sciences at Monash University (2009-2014), Head of the School of Engineering and IT at Deakin (2006-2009), and was appointed to her first professorship in IT at Monash at the age of 35. Having held chairs in three disciplines (mathematics, engineering and IT) has given her a broad interdisciplinary focus, and she was the inaugural Director of MAXIMA (Monash Academy for Cross and Interdisciplinary Mathematical Applications) from 2014-2017.
Kate has published around 250 refereed journal and international conference papers in the areas of neural networks, optimisation, machine learning, and various applied mathematics topics. She has supervised to completion 22 PhD students, and has been awarded over AUD$12 million in competitive grants. In 2010 she was awarded the Australian Mathematical Society Medal for distinguished research, and in 2017 she was awarded the E. O. Tuck Medal for outstanding research and distinguished service in applied mathematics by the Australian and New Zealand Industrial and Applied Mathematics Society (ANZIAM). Kate is a Fellow of the Institute of Engineers Australia and a Fellow of the Australian Mathematical Society (AustMS). She is the current President of the AustMS, and a member of the Australian Research Council’s College of Experts from 2017-2019. She also regularly acts as a consultant to industry in the areas of optimisation, data mining, intelligent systems, and mathematical modelling.