2024
April 2024: SPICER: Self-Supervised Learning for MRI with Automatic Coil Sensitivity Estimation and Reconstruction was accepted to Magnetic Resonance in Medicine.
April 2024: Ulugbek gave an invited talk on Computational Imaging: Restoration Deep Networks as Image Priors at the workshop on Imaging Inverse Problems and Generative Models in Edinburgh, UK.
March 2024: PtychoDV: Vision Transformer-Based Deep Unrolling Network for Ptychographic Image Reconstruction was accepted to IEEE Open Journal of Signal Processing.
March 2024: Domain Expansion via Network Adaptation for Solving Inverse Problems was accepted to IEEE Transactions on Computational Imaging.
March 2024: New paper PnP Restoration with Domain Adaptation for SANS.
February 2024: DiffGEPCI: 3D MRI Synthesis from mGRE Signals using 2.5D Diffusion Model was accepted to IEEE ISBI 2024.
January 2024: A Restoration Network as an Implicit Prior was accepted to ICLR 2024.
January 2024: A Plug-and-Play Image Registration Network was accepted to ICLR 2024.
January 2024: Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models was accepted to ICLR 2024.
January 2024: Constrained Regularization by Denoising with Automatic Parameter Selection was accepted to IEEE Signal Processing Letters.
January 2024: Eddward Chandler started his semester abroad at ENS Paris.
January 2024: Ulugbek started his sabbatical visit to ENS Paris, where he will be affiliated with the Data Science Center and the Kastler–Brossel Laboratory.
2023
November 2023: Welcome to Dr. Yuanhao Wang who just joined CIG as a postdoctoral researcher. Yuanhao got his Ph.D. in Electrical and Computer Engineering under the supervision of Prof. Wolfgang Heidrich.
November 2023: Convergence of Nonconvex PnP-ADMM with MMSE Denoisers was nominated for the Best Student Paper Award at IEEE CAMSAP 2023. The paper will be presented by Chicago Park.
November 2023: New paper FLAIR: A Conditional Diffusion Framework with Applications to Face Video Restoration.
November 2023: New paper DiffGEPCI: 3D MRI Synthesis from mGRE Signals using 2.5D Diffusion Model.
November 2023: New paper DDPET-3D: Dose-aware Diffusion Model for 3D Ultra Low-dose PET Imaging.
November 2023: New paper Constrained Regularization by Denoising with Automatic Parameter Selection.
November 2023: New paper A Structured Pruning Algorithm for Model-based Deep Learning.
October 2023: Block Coordinate Plug-and-Play Methods for Blind Inverse Problems was accepted to NeurIPS 2023.
October 2023: Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems was accepted to NeurIPS 2023.
October 2023: New paper A Plug-and-Play Image Registration Network.
October 2023: New paper A Restoration Network as an Implicit Prior.
October 2023: New paper Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis.
October 2023: New paper Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models.
October 2023: New paper PtychoDV: Vision Transformer-Based Deep Unrolling Network for Ptychographic Image Reconstruction.
October 2023: New paper Domain Expansion via Network Adaptation for Solving Inverse Problems.
September 2023: Ulugbek is an invited speaker at the Conference on AI for Medicine at the Saint Louis University on 13 October 2023.
September 2023: “Convergence of Nonconvex PnP-ADMM With MMSE Denoisers” was accepted to IEEE CAMSAP 2023.
September 2023: “Overcoming Distribution Shifts in Plug-And-Play Methods With Test-Time Training” was accepted to IEEE CAMSAP 2023.
August 2023: Self-Supervised Deep Equilibrium Models for Inverse Problems with Theoretical Guarantees was accepted to IEEE Transactions on Computational Imaging.
August 2023: The recording of Ulugbek’s keynote talk at the ISCS 2023 is available on YouTube.
July 2023: DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction was accepted to ICCV 2023.
July 2023: Deep Equilibrium Learning of Explicit Regularizers for Imaging Inverse Problems was accepted to IEEE Open J. Signal Process.
July 2023: DOLPH: Diffusion Models for Phase Retrieval was accepted to the Asilomar Conference on Signals, Systems, and Computers 2023.
June 2023: Ulugbek will deliver a keynote talk at the International Symposium on Computational Sensing on 12-14 June 2023 in the Grand Duchy of Luxembourg.
May 2023: New paper Block Coordinate Plug-and-Play Methods for Blind Inverse Problems.
May 2023: Respiratory motion management using a single rapid MRI scan for a 0.35 T MRI-Linac system was accepted to Medical Physics.
April 2023: Ulugbek Kamilov was promoted to Associate Professor with Tenure at Washington Univeristy.
April 2023: Ulugbek Kamilov is the recipient of the Outstanding Teaching Award from the Department of Electrical and Systems Engineering at Washington University.
March 2023: Edward Chanlder was awarded 2022 Research Excellence Award at the Department of Computer Science and Engineering at Washington University.
March 2023: Yuyang Hu was awarded 2022 Outstanding Master’s Research Award at the Department of Electrical and Systems Engineering at Washington University.
March 2023: New paper Deep Equilibrium Learning of Explicit Regularizers for Imaging Inverse Problems.
March 2023: Yu Sun was awarded 2022 Turner Dissertation Award for the best doctoral dissertation conducted at the Department of Computer Science and Engineering at Washington University.
March 2023: Three papers accepted to ICASSP 2023 taking place on 4-10 June 2023 in Rhodes Island, Greece.
February 2023: One submissions accepted to ISMRM 2023 taking place on 3-8 June 2023 in Toronto, Canada.
February 2023: Ulugbek will give an invited talk at BASP 2023.
February 2023: Ulugbek will give an invited talk at Mathematics and Image Analysis (MIA) 2023.
January 2023: Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging was published in IEEE Signal Processing Magazine.
January 2023: CIG is teaching ESE 415 Optimization this semester. All the course docs are available here.
2022
December 2022: Ulugbek will give an invited talk at EPFL on Computational Imaging: Integrating Physical and Learned Models on 19 December 2022.
December 2022: Ulugbek will give an invited talk at Institut de Mathématiques de Bordeaux on Plug-and-Play Models for Large-Scale Computational Imaging on 15 December 2022.
December 2022: Ulugbek will give an invited talk at ENS de Lyon on Plug-and-Play Models for Large-Scale Computational Imaging on 9 December 2022. The slides are available here.
December 2022: Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient Recalled Echo (qGRE) MRI metrics associated with Human Brain Neuronal Structure and Hemodynamic Properties was accepted to NMR in Biomedicine.
December 2022: Deep learning-based motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) reconstruction was accepted to Medical Physics.
December 2022: Ulugbek will give an invited talk at the Workshop on Mathematical Models for Plug-and-play Image Restoration on 7-8 December 2022 in Paris, France.
November 2022: New paper DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction.
November 2022: Three CIG members—Jiaming, Weijie, and Shirin—will travel to NeurIPS 2022 in New Orleans, LA, to present our work on online deep equilibrium learning.
November 2022: Ulugbek was elected as a member of the IEEE Bio Imaging and Signal Processing Technical Committee (BISP TC).
November 2022: New book chapter on “Optimization Algorithms for MR Reconstruction” in Chapter 3 of the book Magnetic Resonance Image Reconstruction.
November 2022: Deep Model-Based Architectures for Inverse Problems under Mismatched Priors was accepted to IEEE J. Sel. Areas Inf. Theory.
November 2022: Deep learning-based motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) reconstruction was accepted to Medical Physics.
November 2022: New paper DOLPH: Diffusion Models for Phase Retrieval.
November 2022: New paper Robustness of Deep Equilibrium Architectures to Changes in the Measurement Model.
November 2022: New paper SINCO: A Novel structural regularizer for image compression using implicit neural representations.
November 2022: Eddie Chandler and Junhao Hu are recipients of the Dean’s Select PhD Fellowship from the Washington University McKelvey School of Engineering. Congratulations!
October 2022: New paper CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping.
October 2022: New paper Self-Supervised Deep Equilibrium Models for Inverse Problems with Theoretical Guarantees.
October 2022: New paper SPICE: Self-Supervised Learning for MRI with Automatic Coil Sensitivity Estimation.
September 2022: Online Deep Equilibrium Learning for Regularization by Denoising was accepted to NeurIPS 2022.
September 2022: CIG is part of a team receiving an award from Wellcome Leap to support the study of fetal growth restriction during gestational development.
August 2022: New paper Deep Model-Based Architectures for Inverse Problems under Mismatched Priors.
August 2022: Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging was accepted to IEEE Signal Processing Magazine.
August 2022: Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fields was accepted to Nature Machine Intelligence.
August 2022: The slides of the CIG talk at Google Computational Imaging Workshop are here.
July 2022: Congratulations to Dr. Xiaojian Xu for defending her PhD thesis. Xiaojian will be moving to University of Michigan as a postdoctoral researcher.
July 2022: Learning Cross-Video Neural Representations for High-Quality Frame Interpolation was accepted to ECCV 2022 in Tel-Aviv, Israel.
July 2022: The project page for Deformation Compensated Learning (DeCoLearn) is now online.
July 2022: The recording of Ulugbek’s talk at the CVPR UG2+ Workshop is available on YouTube.
June 2022: Two papers accepted to IEEE ICIP 2022 in Bordeaux, France. The papers are available here.
June 2022: Drew McAllister of Parkway School District was featured in The Source. Drew is working with CIG this summer to design a program for high-school kids to engage with machine learning.
June 2022: New paper Online Deep Equilibrium Learning for Regularization by Denoising.
May 2022: Congratulations to Dr. Yu Sun for defending her PhD thesis. Yu will be moving to Caltech as a postdoctoral researcher.
May 2022: Two abstracts accepted to 2022 Annual Meeting of American Association of Physicists in Medicine (AAPM) as Best-in-Physics award oral presentations.
April 2022: Ulugbek is an invited speaker at the UG2+ workshop of CVPR 2022 on 20 June 2022.
April 2022: Yu is an invited speaker at the CCD workshop of CVPR 2022 on 20 June 2022.
April 2022: New paper Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging.
March 2022: Deformation-Compensated Learning for Image Reconstruction without Ground Truth was accepted to IEEE Transactions on Medical Imaging.
March 2022: New paper Learning Cross-Video Neural Representations for High-Quality Frame Interpolation.
March 2022: Invited Talk for Ulugbek at the Department of Electrical and Computer Engineering (ECE) at Boston University.
March 2022: Invited Talk for Ulugbek at the Systems, Information, Learning and Optimization (SILO) Seminar at University of Wisconsin–Madison.
March 2022: Invited talk for Ulugbek at EECE Seminar of Energy, Environmental & Chemical Engineering at WashU.
March 2022: Learning-based motion artifact removal networks for quantitative R2* mapping was accepted to Magnetic Resonance in Medicine. The code and preprint are also available online.
February 2022: MR-Assisted PET Respiratory Motion Correction Using Deep-Learning Based Short-Scan Motion Fields was accepted to Magnetic Resonance in Medicine.
February 2022: CoIL is now available in the Neural Fields in Visual Computing database.
February 2022: The code for Coordinate-based Internal Learning (CoIL) is publicly available on GitHub.
February 2022: New paper Monotonically Convergent Regularization by Denoising.
February 2022: New paper Bregman Plug-and-Play Priors.
January 2022: Yu Sun is invited to give a talk on “Integrating Physical Models and Learning Priors for Computational Imaging” at Stanford Computational Imaging Lab (SCI).
January 2022: The Computational Cameras and Displays (CCD) workshop was accepted as a full-day workshop at CVPR 2022. This workshop is co-organized by Emma Alexander (Northwestern), Tali Dekel (Weizmann Institute and Google), He Sun (Caltech), and Ulugbek Kamilov (WashU).
January 2022: Estimation of the mechanical properties of a transversely isotropic material from shear wave fields via artificial neural networks was accepted to Journal of the Mechanical Behavior of Biomedical Materials.
2021
December 2021: New paper Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fields.
December 2021: Ulugbek gives a seminar at the Computational Imaging Seminar Series of Purdue University on Wednesday, 1 December 2021.
October 2021: CoIL: Coordinate-based Internal Learning for Tomographic Imaging was accepted to IEEE Transactions on Computational Imaging.
October 2021: Yuyang Hu and Flora Sun are recipients of the Dean’s Select PhD Fellowship from the Washington University McKelvey School of Engineering. Congratulations with this achievement!
September 2021: Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition was accepted to NeurIPS 2021.
September 2021: New paper Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient Recalled Echo (qGRE) MRI metrics associated with Human Brain Neuronal Structure and Hemodynamic Properties.
September 2021: New paper Learning-based Motion Artifact Removal Networks (LEARN) for Quantitative R2* Mapping.
September 2021: Ulugbek is teaching ESE513/CSE534A Large-Scale Optimization for Data Science. There are 74 students taking the class.
September 2021: CIG research was featured in the WashU news: New deep learning method boosts MRI results without requiring new data.
August 2021: “SS-JIRCS: Self-Supervised Joint Image Reconstruction and Coil Sensitivity Calibration in Parallel MRI without Ground Truth” was accepted to the ICCV 2021 workshop on Learning for Computational Imaging.
August 2021: Joint Reconstruction and Calibration Using Regularization by Denoising with Application to Computed Tomography was accepted to the ICCV 2021 workshop on Learning for Computational Imaging.
August 2021: CIG is awarded a grant for the project Enabling Noninvasive Lipid Profiling with Intermodal Deep Learning as part of Scialog: Advancing BioImaging program. Read the press release here.
July 2021: New paper MoDIR: Motion-Compensated Training for Deep Image Reconstruction without Ground Truth.
July 2021: Ulugbek will give a talk at the AI Seminar Series of SLAC National Accelerator Laboratory on Friday, 2 July 2021.
June 2021: Scalable Plug-and-Play ADMM with Convergence Guarantees was accepted to IEEE Transactions on Computational Imaging.
June 2021: New paper Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition.
June 2021: CIG will be presenting three papers at IEEE International Conference on Image Processing (ICIP) this year.
June 2021: Ulugbek will give a talk at the Mathematics, Physics & Machine Learning seminar series on Friday, 11 June 2021. Form more info read here.
May 2021: SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees was accepted to IEEE Transactions on Computational Imaging.
April 2021: Phase2Phase: Respiratory Motion-Resolved Reconstruction of Free-Breathing MRI Using Deep Learning Without a Ground Truth for Improved Liver Imaging was accepted to Investigative Radiology.
March 2021: Congratulations to Jiaming who will join Los Alamos National Laboratory as a summer research inter! He will work with Brendt Wohlberg and other computational imaging researchers to develop randomized learning-based algorithms for scientific imaging.
March 2021: Congratulations to Xiaojian who will join Facebook Reality Labs as a summer research inter! She will get to develop novel technologies in the areas of computational imaging and display.
March 2021: The source code for Regularization by Artifact Removal (RARE) is now available for download.
March 2021: Congratulations to Yu who will join NVIDIA Research this summer as an inter! He will get to collaborate with the leading experts, such as Orazio Gallo, in the areas of computational imaging, computer vision, and deep learning.
February 2021: Ulugbek was selected as one of 55 Fellows for Advancing Bioimaging Scialog initiative sponsored by RCSA the Chan Zuckerberg Initiative.
February 2021: Ulugbek gave a talk at the ECE Colloquium of the University of California Riverside on “Computational Imaging: Reconciling Physical and Learned Model”. For more info go here.
February 2021: We are happy co-recipients of “Beckman Foundation Funding for Advanced Microscopy Technology” as part of a broader WUSTL effort. The grant will provide $1.2M for the acquisition of a lightsheet microscope and the development of data science algorithms for it.
February 2021: New paper CoIL: Coordinate-based Internal Learning for Imaging Inverse Problems. See a short video summary here.
February 2021: Ulugbek gave a talk at the Signal and Information Processing (SIP) Seminar Series of the Rutgers University on “Computational Imaging: Reconciling Physical and Learned Model”.
February 2021: “Stochastic Deep Unfolding for Imaging Inverse Problems” was accepted to IEEE ICASSP 2021. An extended version of this work is available here.
February 2021: Ulugbek gives a talk at Stanford University on Computational Imaging: Reconciling Physical and Learned Models.
February 2021: New paper SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees.
January 2021: Ulugbek receives the NSF CAREER Award.
January 2021: Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors was accepted to ICLR 2021 as a spotlight.
January 2021: Deep Image Reconstruction using Unregistered Measurements without Groundtruth was accepted to IEEE ISBI 2021.
2020
December 2020: Ulugbek was appointed as an Associate Editor of Biological Imaging, a new journal published by the Cambridge University Press.
November 2020: New paper Joint Reconstruction and Calibration using Regularization by Denoising.
October 2020: Ulugbek will talk at Quantitative Phase Imaging VII conference at SPIE Photonics West 2021 that will take place on 6-11 March 2021. We will talk about Scalable Image Reconstruction in Optical Tomography using Deep Priors.
October 2020: Ulugbek will talk at 2021 SIAM Conference on Computational Science and Engineering that will take place on 1-4 March 2021. We will present RARE: Image Reconstruction using Deep Priors Learned without Ground Truth in a session “Beyond the Classical Variational Regularization in Imaging: When Bayesian and Learning Methods Come to Rescue”.
October 2020: “Single-shot 3D holographic particle localization using deep priors trained on simulated data” was accepted to Computational Imaging Conference at IS&T Electronic Imaging 2021.
October 2020: New paper Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors.
October 2020: New paper Deep Image Reconstruction using Unregistered Measurements without Groundtruth.
September 2020: Two papers will be presented at the 54th Asilomar Conference 2020.
September 2020: We are organizing a special session on AI-driven imaging instruments in Computational Imaging XIX conference.
June 2020: Provable Convergence of Plug-and-Play Priors with MMSE denoisers was accepted to IEEE Signal Processing Letters.
June 2020: Ulugbek was elevated to the grade of IEEE Senior Member.
June 2020: New paper Scalable Plug-and-Play ADMM with Convergence Guarantees.
June 2020: SIMBA: Scalable Inversion in Optical Tomography using Deep Denoising Priors was accepted to IEEE Journal of Selected Topics in Signal Processing.
June 2020: Ulugbek will deliver a virtual keynote on Regularization by Artifact Removal at the Computational Cameras and Displays workshop of CVPR 2020.
June 2020: We are organizing a special issue on “Computational Microscopy” in Elsevier Optics Communications. Guest editors for the issue are H. B. de Aguiar (ENS, France), U. S. Kamilov (WashU, USA), and L. Tian (BU, USA).
May 2020: RARE: Image Reconstruction using Deep Priors Learned without Groundtruth was accepted to IEEE Journal of Selected Topics in Signal Processing.
May 2020: The journal version of Block Coordinate Regularization by Denoising was accepted to IEEE Transactions on Computational Imaging.
May 2020: New paper Provable Convergence of Plug-and-Play Priors with MMSE denoisers.
May 2020: Deep learning using a biophysical model for Robust and Accelerated Reconstruction (RoAR) of quantitative and artifact-free R2* images was accepted to Magnetic Resonance in Medicine.
April 2020: Ulugbek gave a virtual guest lecture at the ECE department of Rice University. The recording of the talk is available here.
April 2020: Three CIG students have accepted PhD offers this year. Weijie Gan, Zihui (Ray) Wu, and Max Torop will be starting at WashU, Caltech, and Northeastern, respectively this Fall. Congratulations and good luck to all three!
February 2020: New paper Boosting the Performance of Plug-and-Play Priors via Denoiser Scaling.
February 2020: A New Recurrent Plug-and-Play Prior Based on the Multiple Self-Similarity Network was accepted to IEEE Signal Processing Letters.
February 2020: Ulugbek spoke at the ECE Colloquium Series at University of Minnesota. The title of the talk was “Computational Imaging: Reconciling Models and Learning.”
February 2020: Our work “Image reconstruction for MRI using deep CNN priors trained without ground truth” was accepted to ISBI 2020 Workshop on Deep Learning for Biomedical Image Reconstruction taking place on 3-7 April 2020 in Iowa City, IA, USA.
January 2020: Ulugbek delivers an invited talk at IPAM Workshop on Deep Learning and Medical Applications. The video recording of the talk is available here.
January 2020: Two submissions accepted to ISMRM 2020 taking place on 18-23 April 2020 in Sydney, Australia.
2019
December 2019: New paper Deep learning using a biophysical model for Robust and Accelerated Reconstruction (RoAR) of quantitative and artifact-free R2* images.
December 2019: New paper RARE: Image Reconstruction using Deep Priors Learned without Ground Truth.
December 2019: New paper SIMBA: Scalable Inversion in Optical Tomography using Deep Denoising Priors.
November 2019: Ulugbek joins the editorial board of IEEE Transactions on Computational Imaging as an Associate Editor. IEEE TCI is the leading journal in the computational imaging area.
November 2019: Ulugbek delivers an invited talk on Computational Imaging: Reconciling Models and Learning at the Learning for Computational Imaging workshop of ICCV 2019 in Seoul, South Korea.
October 2019: Ulugbek delivers an invited talk on Computational Imaging: Reconciling Models and Learning at the Center for Molecular Spectroscopy and Dynamics of Korea University in Seoul, South Korea.
October 2019: Proximal Newton Methods for x-ray imaging with non-smooth regularization was accepted to the Computational Imaging Conference at IS&T Electronic Imaging 2020.
September 2019: Infusing Learned Priors into Model-Based Multispectral Imaging was accepted to IEEE CAMSAP 2019.
September 2019: Block Coordinate Regularization by Denoising was accepted to NeurIPS 2019.
September 2019: Online Regularization by Denoising with Applications to Phase Retrieval will be presented at ICCV 2019 workshop on Learning for Computational Imaging.
September 2019: Plug-and-Play Priors for Reconstruction-based Placental Image Registration was accepted to MICCAI 2019 workshop on Perinatal, Preterm and Paediatric Image analysis (PIPPI).
August 2019: Ulugbek will be speaking at the Los Alamos National Laboratory (LANL) on 15 Aug 2019 in Los Alamos, NM, USA.
August 2019: Ulugbek will be giving a seminar on “Reconciling Model-Based and Data-Adaptive Imaging” at AI Summer Institute of the Oak Ridge National Laboratory (ORNL) on 6 Aug 2019 in Oak Ridge, TN, USA.
July 2019: New paper A New Recurrent Plug-and-Play Prior Based on the Multiple Self-Similarity Network.
June 2019: Ulugbek will be speaking at Learning for Computational Imaging (LCI) Workshop at ICCV 2019, taking place on 2 Nov 2019 in Seoul, Korea.
June 2019: Ulugbek will be speaking at IPAM Deep Learning and Medical Applications workshop taking place on 27-31 Jan 2020 in Los Angeles, CA, USA.
June 2019: Three summer REU students joined CIG, Julia Dai (from WashU), Ishika Jain (from Cornell), T.A. Nguyen (from George Mason University). Welcome!
June 2019: Ulugbek is co-organizing a special session Recent Progress in Computational Microscopy at Electronic Imaging 2020. The session will take place on 27-28 Jan 2020 in Burlingame, CA USA.
May 2019: Holographic particle localization under multiple scattering was accepted to SPIE Advanced Photonics.
May 2019: New paper Block Coordinate Regularization by Denoising.
May 2019: Congratulations to Xiaojian who will join MERL this summer as an intern. She will work with the leading experts in computational sensing and imaging, such as Hassan Mansour and Petros Boufounos.
April 2019: Ulugbek served as an area chair for “Computational Imaging” at IEEE ICASSP 2019.
March 2019: The video recording of Ulugbek’s talk at the ICERM Workshop on Computational Imaging is available online.
March 2019: Ulugbek is co-organizing an IMA Special Workshop on Computational Imaging. The workshop will take place on 14-18 Oct 2019 in Minneapolis, MN USA.
February 2019: Three publications accepted to ICASSP 2019 in Brighton, UK.
January 2019: An Online Plug-and-Play Algorithm for Regularized Image Reconstruction was accepted to IEEE Transactions on Computational Imaging.
January 2019: This semester Ulugbek will be teaching Optimization. Xiaojian will be the lead assistant instructor.
2018
December 2018: The video recording of Ulugbek’s plenary at iTWIST 2018 is available online.
November 2018: Ulugbek was re-elected as a member of the IEEE Technical Committee on Computational Imaging for 2019-2021.
November 2018: Plenary by Ulugbek on Signal Processing for Nonlinear Diffractive Imaging and a talk by Yu on Stability of Scattering Decoder for Nonlinear Diffractive Imaging, both at iTWIST 2018.
November 2018: Doctoral course at iTWIST 2018 on Computational Imaging with Convex and Non-Convex Optimization.
November 2018: Our manuscript Plug-In Stochastic Gradient Method was accepted to BASP 2019.
November 2018: New paper Regularized Fourier Ptychography using an Online Plug-and-Play Algorithm.
October 2018: New paper Image Restoration using Total Variation Regularized Deep Image Prior.
October 2018: Jiaming Liu is a recipient of the Dean’s Select PhD Fellowship from the Washington University, School of Engineering & Applied Science. Congratulations for this achievement!
October 2018: Ulugbek is serving as a program chair for OSA Mathematics in Imaging 2019 (24-27 Jun 2019 in Munich, Germany). Consider submitting to the conference. For more info see the conference flyer here.
September 2018: Ulugbek and Adam Scholefield are organizing a special session on “Recent Advances in Signal Processing for Large-Scale Computational Imaging” at IEEE ICASSP 2019.
September 2018: Our manuscript Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging was accepted to IEEE Transactions on Computational Imaging.
September 2018: New paper An Online Plug-and-Play Algorithm for Regularized Image Reconstruction.
August 2018: Our manuscript Stability of Scattering Decoder For Nonlinear Diffractive Imaging was accepted to iTWIST 2018.
August 2018: New paper Single-shot holographic 3D particle-localization under multiple scattering.
July 2018: New paper signProx: One-Bit Proximal Algorithm for Nonconvex Stochastic Optimization.
July 2018: Building a better microscope describes our NSF-sponsored project on high-resolution microscopy.
July 2018: New paper Stability of Scattering Decoder For Nonlinear Diffractive Imaging.
July 2018: The list of research projects at CIG available to the current WashU students is here.
June 2018: The source code for Efficient and accurate inversion of multiple scattering with deep learning is now available for download.
June 2018: Our project on data-adaptive imaging was awarded WUSTL Collaboration Initiation Grant.
May 2018: Our manuscript Efficient and accurate inversion of multiple scattering with deep learning was accepted to OSA Optics Express.
May 2018: New arXiv manuscript Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging.
May 2018: Ulugbek will chair the session “Sparsity Based Priors” at OSA Imaging and Applied Optics Congress 2018 in Orlando, FL, USA.
May 2017: Our manuscript Learning-based Image Reconstruction via Parallel Proximal Algorithm was accepted to IEEE Signal Processing Letters.
May 2018: The patent application System and Method for Through-the-Wall-Radar-Imaging using Total-Variation Denoising was granted by USPTO.
April 2018: Ulugbek is a recipient of the IEEE Signal Processing Society’s 2017 Best Paper Award (with V. K. Goyal and S. Rangan). The award was delivered during IEEE ICASSP 2018 in Calgary, Canada.
April 2018: Sergio Goodwin, Jhoan Hernandez, and Jason Liao will join CIG as summer undergraduate researchers. Sergio and Jhoan join via the Washington University Summer Engineering Fellowship (WUSEF) program.
April 2018: Ulugbek chaired the session “Computational Imaging II” at IEEE ICASSP 2018 in Calgary, Canada.
March 2018: Two publications accepted to OSA Imaging Congress 2018.
March 2018: New paper Efficient and accurate inversion of multiple scattering with deep learning.
March 2018: The patent application Method and System for Through-the-Wall Radar Imaging was granted by USPTO.
March 2018: One publication accepted to IGARSS 2018.
March 2018: Ulugbek talks at the Interdisciplinary Distinguished Seminar Series of NC State University, Raleigh, NC, USA.
February 2018: Xiaojian Xu joins CIG as a PhD student. Welcome!
January 2018: Three publications accepted to ICASSP 2018.
January 2018: New paper Learning-based Image Reconstruction via Parallel Proximal Algorithm.
January 2018: Wenmei Bo joins CIG as a MSc student starting from January 2018. Welcome!
January 2018: Terry Pan joins CIG as a MSc student starting from January 2018. Welcome!
2017
December 2017: Shiqi Xu joins CIG as a MSc student starting from January 2018. Welcome!
December 2017: CIG gratefully acknowledges the support of NVIDIA Corporation with the donation of the Titan Xp GPU for research.
November 2017: Yu Sun joins CIG as a PhD student starting from January 2018. Welcome!
October 2017: Our manuscript SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering was accepted to IEEE Transactions on Computational Imaging.
October 2017: Our manuscript A Plug-and-Play Priors Approach for Solving Nonlinear Imaging Inverse Problems was accepted to IEEE Signal Processing Letters.
October 2017: Ulugbek serves as a program committee member for OSA Mathematics in Imaging conference.
October 2017: Ulugbek joined the Journal of Electronic Imaging (JEI) as an Associate Editor.
September 2017: Computational Imaging Group is now recruiting Ph.D. students.
September 2017: Ulugbek joins Washington University in St. Louis as an Assistant Professor.
August 2017: Ulugbek delivers a plenary talk at the Workshop on Regularized Inverse Problem Solving and High-Dimensional Learning Methods in UC Louvain, Belgium.
June 2017: Ulugbek delivers 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 paper “SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering.”
May 2017: Publication accepted to OSA Advanced Photonics Congress 2017: “Acceleration of FDTD-based Inverse Design Using a Neural Network Approach.”
May 2017: Two publications 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: Ulugbek delivers a guest lecture for the class “Computational Optical Imaging” at Boston University on nonlinear algorithms for optical imaging.
March 2017: Two publications 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.
2016
December 2016: Three publications 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: Ulugbek delivers 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: Ulugbek’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: Ulugbek delivers two keynote talks at iTWIST 2016: “Learning MMSE Optimal Thresholds for FISTA” and “Minimizing Isotropic Total Variation without Subiterations.”
July 2016: Three publications were accepted to CoSeRa 2016.
July 2016: Ulugbek delivers 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: Ulugbek delivers an invited talk at Tufts University‘s ECE Colloquia on “Compressive Imaging with Learning Tomography.”