Rate My Professor Adrian Wills

Adrian Wills specializes in advanced computational methods for engineering applications, including nonlinear system identification, state-space models, sequential Monte Carlo methods, variational inference, Bayesian parameter estimation, jump Markov linear systems, extended target tracking, strain tomography using neutron and X-ray diffraction, stochastic optimization, model predictive control, and scanning-beam lithography. His scholarly impact is substantial, with 4,843 citations on Google Scholar and 4,067 citations across 154 publications on ResearchGate. Key publications include 'System identification of nonlinear state-space models' (with T.B. Schön and B. Ninness, 2011, 742 citations), 'Identification of hammerstein–wiener models' (with T.B. Schön, L. Ljung, and B. Ninness, 2013, 418 citations), 'Maximum likelihood identification of Wiener models' (with A. Hagenblad and L. Ljung, 2008, 256 citations), 'Barrier function based model predictive control' (with W.P. Heath, 2004, 213 citations), 'Linearly constrained Gaussian processes' (with C. Jidling, N. Wahlström, and T.B. Schön, 2017, 169 citations), and 'Sequential Monte Carlo: A Unified Review' (2023). In 2014, Wills and Professor Brett Ninness were awarded an Automatica journal prize paper award at the International Federation of Automatic Control World Congress in Cape Town, South Africa. His contributions extend to software development, such as the University of Newcastle Identification Toolbox (UNIT).