Automating Decision-making


Bio: "Richard is Business Engagement Lead of Alliance Manchester Business School and Senior Lecturer (Associate Prof) in Data Science at The University of Manchester. Prior to Manchester, he worked at the Biochemical Engineering Department, University College London. He studied Business Engineering at the Karlsruhe Institute of Technology and the Royal Melbourne Institute of Technology and completed a PhD in Computer Science at The University of Manchester. Richard's research interests are in the field of data science and in particular in the development and application of optimization and machine learning techniques to real-world problems arising in areas such as healthcare, manufacturing, economics, sports, music, and forensics. Much of research has been funded by UK funding bodies (e.g. ESRC, EPSRC, Innovate UK) and industrial partners. Richard is a Member of the Editorial Board of several international journals, Vice-Chair of the IEEE CIS Bioinformatics and Bioengineering Technical Committee, Co-Founder of the IEEE CIS Task Force on Optimization Methods in Bioinformatics and Bioengineering, and contributes regularly to conference organisation and special issues as guest editors."

Computational optimization is prevalent in numerous application domains in industry; government and academia; and concerned with the design and application of computational search; modelling and simulation techniques to select a best element; with regard to some criterion; from some set of available alternatives. In practice; a computational optimization problem can have various additional challenges; such as multiple conflicting criteria to be optimized simultaneously; resourcing constraints; dynamic and uncertain problem components; and time-consuming and/or expensive experiments. In this clinic; I will draw on my research expertise and the literature in Optimization and Machine Learning; and close collaboration with external stakeholders; to provide advice on how to use state-of-the-art research methods to help you frame; define and solve your computational optimization problem efficiently. I will also provide advice on suitable funding and engagement routes for collaborative work with academic and other stakeholders. To get the most out of this session; please come prepared with a short pitch of the problem you want to tackle and the aspect of the problem that you would like to get advice on.