Vahid Tarokh

Tarokh

Rhodes Family Distinguished Professor of Electrical and Computer Engineering

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.

Appointments and Affiliations

  • Rhodes Family Distinguished Professor of Electrical and Computer Engineering
  • Professor of Electrical and Computer Engineering
  • Professor of Mathematics

Contact Information

  • Office Location: 130 Hudson Hall, Durham, NC 27708
  • Office Phone: (919) 660-7594
  • Email Address: vahid.tarokh@duke.edu
  • Websites:

Research Interests

Representation, modeling, inference and prediction from data

Awards, Honors, and Distinctions

  • Member. National Academy of Engineering. 2019

Courses Taught

  • COMPSCI 590: Advanced Topics in Computer Science
  • COMPSCI 675D: Introduction to Deep Learning
  • ECE 280L9: Signals and Systems - Lab
  • ECE 280L: Introduction to Signals and Systems
  • ECE 392: Projects in Electrical and Computer Engineering
  • ECE 493: Projects in Electrical and Computer Engineering
  • ECE 494: Projects in Electrical and Computer Engineering
  • ECE 590: Advanced Topics in Electrical and Computer Engineering
  • ECE 685D: Introduction to Deep Learning
  • ECE 891: Internship
  • ECE 899: Special Readings in Electrical Engineering
  • MATH 493: Research Independent Study

Representative Publications

  • Momenifar, M; Diao, E; Tarokh, V; Bragg, AD, A Physics-Informed Vector Quantized Autoencoder for Data Compression of
    Turbulent Flow
    (2022) [abs].
  • Hasan, A; Pereira, JM; Farsiu, S; Tarokh, V, Identifying Latent Stochastic Differential Equations, Ieee Transactions on Signal Processing, vol 70 (2022), pp. 89-104 [10.1109/TSP.2021.3131723] [abs].
  • Huo, Q; Shi, Y; Liu, C; Tarokh, V; Ferrari, S, Online Action Change Detection for Automatic Vision-based Ground Control of Aircraft, Aiaa Science and Technology Forum and Exposition, Aiaa Scitech Forum 2022 (2022) [10.2514/6.2022-2031] [abs].
  • Momenifar, M; Diao, E; Tarokh, V; Bragg, AD, Dimension reduced turbulent flow data from deep vector quantisers, Journal of Turbulence, vol 23 no. 4-5 (2022), pp. 232-264 [10.1080/14685248.2022.2060508] [abs].
  • Le, CP; Soltani, M; Dong, J; Tarokh, V, Fisher Task Distance and its Application in Neural Architecture Search, Ieee Access, vol 10 (2022), pp. 47235-47249 [10.1109/ACCESS.2022.3171741] [abs].