Swati is Research Scientist at Alliance Manchester Business School, since October 2017. Her research is focused on developing interpretable AI and machine learning models to automate the decision making. She is designing a package in Python to enable industrial research partners to use AI-based tool to automate decision making in finance, healthcare, and law. AI-tool consists of Expert systems based on Belief Rule-Based, Deep neural network (Backpropagation), Evidence reasoning approach, and Non-linear constrained optimization (large scale optimization - IPOPT solver and SLSQP).
She has worked on FINTECH consulting projects with Together Financial Services: Artificial intelligence to automated mortgage lending and AstraZeneca: Machine learning model to improve financial data quality.
Swati graduated with a Masters in Financial Operational Research from the University of Edinburgh in 2011. She did her Masters dissertation with Shell Royal Dutch plc where she developed econometric models to forecast the impact of rising petrol prices in the USA to the European level and then worked as a statistician in School of Mathematics, the University of Edinburgh (2012).
Swati completed her PhD in Operational Research and Applied Statistics from Glasgow Caledonian University in 2016. After completing her Ph.D., she joined the University of Nottingham as a Research Fellow, where she did research on predictive analytics for Network Rail, UK, and SNCF (French National Railway Company).