September 2017: Computational Imaging Group is now recruiting Ph.D. students [see more].
September 2017: Prof. Kamilov joins Washington University in St. Louis as an Assistant Professor.
August 2017: Prof. Kamilov will deliver a plenary talk at the Workshop on Regularized Inverse Problem Solving and High-Dimensional Learning Methods that will be held UCLouvain, Belgium.
June 2017: Prof. Kamilov delivered an invited talk at OSA Mathematics in Imaging in San Francisco, CA, USA.
June 2017: Our accepted ICIP 2017 manuscript is now online “Online Convolutional Dictionary Learning for Multimodal Imaging.”
May 2017: New preprint “SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering.”
May 2017: Paper accepted to OSA Advanced Photonics Congress 2017: “Acceleration of FDTD-based Inverse Design Using a Neural Network Approach.”
May 2017: Two papers accepted to ICIP 2017: “Online Convolutional Dictionary Learning for Multimodal Imaging” and “Fusion of multi-angular aerial images based on epipolar geometry and matrix completion.”
April 2017: Prof. Kamilov delivered a guest lecture for the class “Computational Optical Imaging” at Boston University on nonlinear algorithms for optical imaging.
March 2017: Two papers were accepted to SPARS 2017: “Learning Convolutional Proximal Filters” (with D. Liu and H. Mansour) and “A Kaczmarz Method for Low Rank Matrix Recovery” (with H. Mansour and O. Yilmaz).
February 2017: The manuscript “Compressive Imaging with Iterative Forward Models” is the Best Student Paper Award finalist at IEEE ICASSP 2016.
January 2017: The manuscript “Motion-Adaptive Depth Superresolution” was accepted to IEEE Transactions on Image Processing.
December 2016: Three papers and a letter were accepted to IEEE ICASSP 2016:
- “Compressive Imaging with Iterative Forward Models,” with H.-Y. Liu, D. Liu, H. Mansour, and P. T. Boufounos.
- “Optical Tomography based on a Nonlinear Model that Handles Multiple Scattering,” with M. H. Shoreh, A. Goy, J. Lim, M. Unser, and D. Psaltis.
- “Learning Optimal Nonlinearities for Iterative Thresholding Algorithms,” with H. Mansour.
November 2016: The manuscript “A Parallel Proximal Algorithm for Anisotropic Total Variation Minimization” was accepted to IEEE Transactions on Image Processing.
November 2016: “Learning Bayesian Optimal FISTA with Error Backpropagation” was accepted for an invited session at International BASP Frontiers workshop 2017.
October 2016: The PhD thesis “Sparsity-Driven Statistical Inference for Inverse Problems” received a special distinction from EPFL’s award committee. The official press release is here.
October 2016: Serving as an area chair of ICASSP 2017 for computational imaging.
September 2016: The manuscript “Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization” was accepted to IEEE Transactions on Information Theory.
September 2016: Prof. Kamilov delivered two keynote talks at CoSeRa 2016: “Coherent Distributed Array Imaging under Unknown Position Perturbations” and “Online Blind Deconvolution for Sequential Through-the-Wall-Radar-Imaging.”
August 2016: Prof. Kamilov’s special session on “Large-Scale Computational Imaging with Wave Models” was accepted for ICASSP 2017. The session is organized jointly with Prof. Laura Waller and Dr. Brendt Wohlberg.
August 2016: Prof. Kamilov delivered two keynote talks at iTWIST 2016: “Learning MMSE Optimal Thresholds for FISTA” and “Minimizing Isotropic Total Variation without Subiterations.”
July 2016: Three papers were accepted to CoSeRa 2016.
July 2016: Prof. Kamilov delivered an invited talk at NYU Tandon School of Engineering on “Trainable iterative algorithms for computational sensing.”
June 2016: The manuscript “A Recursive Born Approach to Nonlinear Inverse Scattering” was accepted to IEEE Signal Processing Letters.
April 2016: The manuscript “Depth Superresolution using Motion Adaptive Regularization” was accepted to IEEE ICMEW 2016.
April 2016: Prof. Kamilov delivered an invited talk at Tufts University‘s ECE Colloquia on “Compressive Imaging with Learning Tomography.”