Rabeeh Karimi Mahabadi
I work on representation learning for text. In particularly, I work on representation learning for modeling abstraction.
My end goal of research, would be to reuse the learned representation in other domains such as summarization.
I received my Bachelor in Electrical engineering (Communications and signal processing) from Amirkabir university of Technology,Iran and my master in Computer science (Computer vision and machine learning) from ETH, Zurich.
A Learning-Based Framework for Quantized Compressed Sensing, R. Karimi Mahabadi, J. Lin, V. Cevher, IEEE Signal Processing Letters, 2019.
Real-time DCT Learning-based Reconstruction of Neural Signals, R. Karimi Mahabadi, C. Aprile, V. Cevher, EUSIPCO, 2018. PDF
A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization, Y. Hsieh, Y. Kao, R.Karimi Mahabadi, A. Kyrillidis, and V. Cevher, IEEE Transactions on Signal Processing, 2018. PDF
Learning-Based Compressive MRI, B. Gözcü, R. Karimi Mahabadi, Y. Li, E. Ilıcak, T. Cukur, J. Scarlett, and V.Cevher, IEEE Transactions on Medical Imaging, 2017. PDF
Segment Based 3D Object Shape Priors, R. Karimi Mahabadi, C. Hane, M. Pollefeys, CVPR, 2015. PDF
Scalable sparse covariance estimation via self-concordance, A. Kyrillidis, R. Karimi Mahabadi, Q. Tran-Dinh, V. Cevher, AAAI, 2014. PDF
Advanced MATLAB for Electrical Engineers: Neural Networks, Image processing, Genetic Algorithms, Fuzzy logic, and Digital Communication, A. Alamdari, R. Karimi Mahabadi, A. Doosti, Z. Rajabi, Negarandeye Danesh publisher, ISBN:978-600-6190-11-2.
Simulink for Engineers, A. Alamdari, R. Karimi Mahabadi, Negarandeye Danesh publisher, ISBN:978-600-6190-04-4.
Grace Hopper travel grant by Google, 2018.
WiML (Women in Machine Learning) travel grant, 2017
EDIC PhD program fellowship by EPFL, 2017
ETH Master program Scholarship, 2015