Rabeeh Karimi Mahabadi

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Internship project topic:

Sparse Covariance Selection and Phase-retrieval.

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Biography

Rabeeh Karimi Mahabadi received her B.Sc. degree in Electrical Engineering (Communications) from Amirkabir University of Technology, Iran in 2012. During her undergraduate, her research was focused on machine learning, computer vision and Bayesian learning. She was an intern at LIONS, Ecole Polytechnique Federale de Lausanne in summer 2013. She is currently pursuing a Master in Computer Science at ETH, Zurch, Switzerland. Her research interests include Convex and non-convex optimization, Compressive sensing, and Statistical machine learning.

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Links
 

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PUBLICATIONS

R. Karimi Mahabadi; J. Lin; V. Cevher : A Learning-Based Framework for Quantized Compressed Sensing; IEEE Signal Processing Letters. 2019.
R. K. Mahabadi; C. Aprile; V. Cevher : Real-time DCT Learning-based Reconstruction of Neural Signals. 2018-01-01. European Signal Processing Conference (EUSIPCO), Rome, ITALY, Aug 03-07, 2018. p. 1925-1929.
R. Karimi Mahabadi; C. Aprile; V. Cevher : Real-time DCT Learning-based Reconstruction of Neural Signals. 2018. 26th European Signal Processing Conference (EUSIPCO 2018), Rome, Italy , September 3-7. 2018.
B. Gözcü; R. Karimi Mahabadi; Y.-H. Li; E. Ilıcak; T. Çukur et al. : Learning-Based Compressive MRI; IEEE Transactions On Medical Imaging. 2018. DOI : 10.1109/TMI.2018.2832540.
Y.-P. Hsieh; Y.-C. Kao; R. Karimi Mahabadi; Y. Alp; A. Kyrillidis et al. : A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization; IEEE Transactions on Signal Processing. 2018. DOI : 10.1109/TSP.2018.2870353.
A. Kyrillidis; R. Karimi Mahabadi; Q. Tran Dinh; V. Cevher : Scalable sparse covariance estimation via self-concordance. 2014. Twenty-Eighth AAAI Conference on Artificial Intelligence, Quebec, Canada, July 27-31, 2014.