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Professor Paresh Date is Professor and joint Head of the Department of Mathematics at Brunel University London, Uxbridge, within the College of Engineering, Design and Physical Sciences. An electrical engineer by background, he earned a PhD from the University of Cambridge, UK, and an MTech from the Indian Institute of Technology Mumbai. He joined Brunel University as a Lecturer in the Department of Mathematical Sciences in July 2002 and has since advanced to his current professorial position and headship, shared with Dr Shaw. Prior to this, from March 2000 to June 2002, he served as a Research Associate in the Cambridge University Engineering Department. Earlier professional experience includes roles as Engineering Executive in the Control and Automation Division at Larsen & Toubro Limited, Mumbai, India, in 1995-1996, and Associate Consultant at Citicorp Overseas Software Limited, Mumbai, in 1995. During his doctoral studies from 1996 to 2000, Date received the Cambridge Commonwealth Scholarship and the Overseas Research Student Award from the Council of Vice-Chancellors and Principals, UK.
Date's research specializations center on nonlinear state estimation, with applications in tracking and finance, alongside financial portfolio optimization and derivative pricing. His academic interests extend to algorithms for latent state estimation or filtering in nonlinear time series, particularly for forecasting and risk measurement in mathematical finance, financial modeling in microfinance, and optimization problems in power systems. He is the author of the book 'Nonlinear estimation: methods and applications with deterministic sample points,' published by Taylor & Francis in 2019. Key publications include 'A Machine Learning Approach for Micro-Credit Scoring' (Risks, 2021, with A. Ampountolas et al.), 'Pricing and hedging wind power prediction risk with binary option contracts' (Energy Economics, 2023, with J. Thakur et al.), 'Stabilization and Optimal Control for Discrete-time Markov Jump Linear System with Multiplicative Noises and Input Delays: A Complete Solution' (IEEE Transactions on Automatic Control, 2023, with C. Han et al.), 'Polynomial Chaos Kalman Filter for Target Tracking Applications' (IET Radar, Sonar and Navigation, 2022, with K. Kumar et al.), and 'Modelling and forecasting of exchange rate pairs using the Kalman filter' (Journal of Forecasting, 2024, with J. Maunthrooa). He has secured research funding, including an EPSRC overseas travel grant (EP/L019477/1, 2014), a London Mathematical Society UKFin+ grant (2021), and a recent grant for news sentiment analysis for sustainable investing (2025).
