Research Fellow; Associate, Oxford India Centre for Sustainable Development; Parkinson's UK Early Career Fellow
Siddharth completed his DPhil, focused on developing statistical methods for time series forecasting, at Somerville College.
His research interests include Biomedical Signal & Image Processing, Statistical Modelling, Forecasting, and Chaos Synchronization. His work is primarily concerned with two application areas: Healthcare, and Energy.
Currently, Siddharth is investigating remote technologies for the diagnosis and monitoring of Parkinson’s disease. He develops statistical algorithms using data for voice, gait, posture, reaction times, dexterity, and tremor, collected using smartphones in a home and community setting. These algorithms are aimed at identifying patterns in the data, which can be used to discriminate people with Parkinson’s disease from healthy controls and accurately monitor the severity symptoms of the disease over time.
Siddharth is also working on a NHS funded project aimed at predicting the A&E arrivals, admissions and discharges across hospitals in the West Midlands. The algorithms developed as part of this project will be used operationally by the NHS to optimize staffing decisions, which would help reduce patient waiting times.
“Detecting and Monitoring the Symptoms of Parkinson’s Disease using Smartphones: A Pilot Study”, Parkinsonism and Related Disorders, 21, 650–653.
S. Arora, V. Venkataraman, A. Zhan, S. Donohue, K.M. Biglan, E.R. Dorsey, M.A. Little (2015)
“Forecasting Electricity Smart Meter Data Using Conditional Kernel Density Estimation”, Omega, forthcoming.
S. Arora and J.W. Taylor (2014)
“Cortical and Clonal Contribution of Tbr2 Expressing Progenitors in the Developing Mouse Brain”, Cerebral Cortex, forthcoming.
N.A. Vasistha, F. García-Moreno, S. Arora, A.F.P. Cheung, S.J. Arnold, E.J. Robertson and Z. Molnár (2014)
Synchronization of Coupled Map Lattice using Delayed Variable Feedback”, Journal of Applied Nonlinear Dynamics, 3, 245-253.
S. Arora and M.S. Santhanam (2014)
“Short-term Forecasting of Anomalous Load using Rule-based Triple Seasonal Methods”, IEEE Transactions on Power Systems, 28, 3235-3242.
S. Arora and J.W. Taylor (2013)
“Nonlinear and Nonparametric Modelling Approaches for Probabilistic Forecasting of the US Gross National Product”, Studies in Nonlinear Dynamics and Econometrics, 17, 395-420.
S. Arora, M.A. Little and P.E. McSharry (2013)