Vahid Tarokh

Rhodes Family Professor of Electrical and Computer Engineering

Vahid Tarokh’s research is in pursuing new formulations and approaches to getting the most out of datasets.

Appointments and Affiliations

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

Contact Information

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

Research Interests

Foundations of AI,  Foundations of Signal Processing, Learning Representations, Transfer Learning,  Meta-Learning, Physics Infused Learning, Extreme Value Theory, Dependence Modeling, Hypothesis Testing, Sequential Analysis.

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 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

  • Lin, J., M. Hasan, P. Acar, J. Blanchet, and V. Tarokh. “Neural network accelerated process design of polycrystalline microstructures.” Materials Today Communications 36 (August 1, 2023). https://doi.org/10.1016/j.mtcomm.2023.106884.
  • Soloveychik, I., and V. Tarokh. “Region selection in Markov random fields: Gaussian case.” Journal of Multivariate Analysis 196 (July 1, 2023). https://doi.org/10.1016/j.jmva.2023.105178.
  • Peng, Rixi, Juncheng Dong, Jordan Malof, Willie J. Padilla, and Vahid Tarokh. “Deep Generalized Green's Functions,” June 5, 2023.
  • Hasan, Ali, Yu Chen, Yuting Ng, Mohamed Abdelghani, Anderson Schneider, and Vahid Tarokh. “Inference and Sampling of Point Processes from Diffusion Excursions,” June 1, 2023.
  • Le, Cat P., Juncheng Dong, Ahmed Aloui, and Vahid Tarokh. “Few-Shot Continual Learning for Conditional Generative Adversarial Networks,” May 18, 2023.