Jeremias Sulam, PhD
Office: Clark 320B
Lab: Sulam Group
PhD, Computer Science, Technion Israel Institute of Technology, Israel, 2018
Biomedical Engineering, Universidad Nacional de Entre Rios, Argentina, 2013
Jeremias’ research focuses on sparse recovery, dictionary learning and machine learning, with an interest in inverse problems in signal and image processing. In particular, he is interested in the theoretical study of deep learning, as well as its application to detection, classification and other problems in biomedical sciences.
V. Papyan, Y. Romano, J. Sulam and M. Elad, “Theoretical Foundations of Deep Learning via Sparse Representations.” IEEE Signal Processing Magazine, vol. 35, no. 4, pp. 72-89, July 2018.
J. Sulam, V. Papyan, Y. Romano, M. Elad, (2017). Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning. IEEE Transactions on Signal Processing, vol. 66, no. 15, pp. 4090-4104, Aug.1, 2018.
V. Papyan, J. Sulam, M. Elad. Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding.
J. Sulam, Y. Romano, R. Talmon. Dynamical system classification with diffusion embedding for ECG based person identification. Signal Processing. Vol. 130, January 2017, Pages 403–411.
J. Sulam, B. Ophir, M. Zibulevsky and M. Elad. Trainlets: Dictionary Learning in High Dimensions. IEEE Transactions on Signal Processing, 2016, V. 64, 12, pg: 3180 – 3193.