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Rhodes Family Professor of Electrical and Computer EngineeringVahid 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.
Appointments and Affiliations
- Rhodes Family Professor of Electrical and Computer Engineering
- Professor of Electrical and Computer Engineering
- Professor of Computer Science
- Professor of Mathematics
- Email Address: email@example.com
Research InterestsRepresentation, modeling, inference and prediction from data
- ECE 590: Advanced Topics in Electrical and Computer Engineering
- Xiang, Y; Ding, J; Tarokh, V, Estimation of the evolutionary spectra with application to stationarity test, Ieee Transactions on Signal Processing, vol 67 no. 5 (2019), pp. 1353-1365 [10.1109/TSP.2018.2890369] [abs].
- Ding, J; Tarokh, V; Yang, Y, Model Selection Techniques: An Overview, Ieee Signal Processing Magazine, vol 35 no. 6 (2018), pp. 16-34 [10.1109/MSP.2018.2867638] [abs].
- Xiang, Y; Ding, J; Tarokh, V, Evolutionary Spectra Based on the Multitaper Method with Application to Stationarity Test, 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), vol 2018-April (2018), pp. 3994-3998 [10.1109/ICASSP.2018.8461443] [abs].
- Banerjee, T; Whipps, G; Gurram, P; Tarokh, V, Sequential Event Detection Using Multimodal Data in Nonstationary Environments, 2018 21st International Conference on Information Fusion, Fusion 2018 (2018), pp. 1940-1947 [10.23919/ICIF.2018.8455835] [abs].
- Shahrampour, S; Noshad, M; Ding, J; Tarokh, V, Online Learning for Multimodal Data Fusion with Application to Object Recognition, Ieee Transactions on Circuits and Systems Ii: Express Briefs, vol 65 no. 9 (2018), pp. 1259-1263 [10.1109/TCSII.2017.2754141] [abs].