Instructor • Research Associate

Room number: ECOT 235

Farhad Pourkamali-Anaraki is a Research Associate in the Department of Applied Mathematics at the University of Colorado at Boulder. He received his Ph.D. in 2017 in Electrical Engineering from the University of Colorado at Boulder. He won the 2017 Gold Research Award and 2016 Gold Teaching Award in recognition of outstanding contribution to the Department of Electrical, Computer, and Energy Engineering, University of Colorado at Boulder.

Research Interests: 

  1. Algorithmic and theoretical aspects of modern large-scale data analysis 
  2. Statistical signal processing and machine learning 
  3. Information extraction from large high-dimensional data 
  4. Randomized numerical linear algebra 

Selected Publications:

  1.  F. Pourkamali-Anaraki and S. Becker, “Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means,” IEEE Transactions on Information Theory, vol. 63, no. 5, pages 2954-2974, 2017.

  2.  F. Pourkamali-Anaraki, “Estimation of the Sample Covariance Matrix from Compressive Measurements,” IET Signal Processing, vol. 10, no. 9, pages 1089-1095, 2016.

  3.  F. Pourkamali-Anaraki, S. Becker, and S. Hughes, “Efficient Dictionary Learning via Very Sparse Random Projections,” Sampling Theory and Applications (SampTA), pages 478-482, 2015.

  4.  F. Pourkamali-Anaraki and S. Hughes, “Memory and Computation Efficient PCA via Very Sparse Random Projections,” Proceedings of the 31st International Conference on Machine Learning (ICML), pages 1341-1349, 2014.