Vahid Tarokh, Rhodes Family Professor of Electrical and Computer Engineering and Professor of Mathematics and Computer Science
Vahid Tarokh’s research is in pursuing new formulations and approaches to getting the most out of datasets. Current projects are focused on representation, modeling, inference and prediction from data such as determining how different people will respond to exposure to certain viruses, predicting rare events from small amounts of data, formulation and calculation of limits of learning from observations, and prediction of a macaque monkey's future actions from its brain waves.  Contact Info:
 Recent Publications
(More Publications)
 Ding, J; Shahrampour, S; Heal, K; Tarokh, V, Analysis of Multistate Autoregressive Models,
Ieee Transactions on Signal Processing, vol. 66 no. 9
(May, 2018),
pp. 24292440 [doi]
 Magnusson, S; Enyioha, C; Li, N; Fischione, C; Tarokh, V, Convergence of Limited Communication Gradient Methods,
Ieee Transactions on Automatic Control, vol. 63 no. 5
(May, 2018),
pp. 13561371 [doi]
 Soloveychik, I; Xiang, Y; Tarokh, V, PseudoWigner Matrices,
Ieee Transactions on Information Theory, vol. 64 no. 4
(April, 2018),
pp. 31703178 [doi]
 Soloveychik, I; Xiang, Y; Tarokh, V, Symmetric PseudoRandom Matrices,
Ieee Transactions on Information Theory, vol. 64 no. 4
(April, 2018),
pp. 31793196 [doi]
 Ding, J; Zhou, J; Tarokh, V, Optimal prediction of data with unknown abrupt change points,
2017 Ieee Global Conference on Signal and Information Processing, Globalsip 2017 Proceedings, vol. 2018January
(March, 2018),
pp. 928932, ISBN 9781509059904 [doi] [abs]
