News - SLIM

Recent Updates!

2025
05/15/25: The paper titled "Object Detection with Deep Learning for Rare Event Search in the GADGET II TPC" worked on by SLIM member Tyler Wheeler has been accepted for publication in Nuclear Inst. and Methods in Physics Research, A. (arXiv)
05/09/25: The paper "Learning Robust Features for Scatter Removal and Reconstruction in Dynamic ICF X-Ray Tomography" by Siddhant Gautam, M. Klasky, B.T. Nadiga, T. Wilcox, G. Salazar & S. Ravishankar (a collaboration with LANL) has been accepted for publication in Optics Express! (arXiv)

05/05/25: Join us in congratulating our grads!

Evan Bell: Johns Hopkins ECE grad school
Annie Wozniak: Analyst at DSV (Detroit area)
Minh Nguyen: Caltech Applied & Computational Math PhD
Avrajit Ghosh: Postdoc with Peter Bartlett at Berkeley
Shijun Liang: Postdoc at UMich & MSU

05/01/25: Our paper "SITCOM: Step-wise Triple-Consistent Diffusion Sampling for Inverse Problems", co-authored with Ismail R. Alkhouri, Shijun Liang, Cheng-Han Huang, Jimmy Dai, Qing Qu, Saiprasad Ravishankar, Rongrong Wang, has been accepted to ICML 2025! (arXiv)
03/11/25: Please join us in congratulating Avrajit Ghosh for being the CMSE nominee for the 2024-25 Fitch H. Beach Award for Outstanding Doctoral Research, and Siddhant Gautam for the Outstanding Graduate Student Award for 2024-25! Congratulations!
03/02/25: SLIM group PhD student Avrajit Ghosh has been nominated for the Fitch H. Beach Award from the CMSE department. The award recognizes the most outstanding graduate researchers within the College of Engineering. Congrats!
01/22/25: "Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability" has been accepted to the ICLR 2025 Conference. Worked on by Avrajit Ghosh, Soo Min Kwon, Rongrong Wang, Saiprasad Ravishankar, and Qing Qu. (OpenReview)
01/21/25: SLIM group postdoc Dr. Ismail Alkhouri has been selected to receive the CPAL Rising Star Award. Congratulations!
01/14/25: "Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction" has been accepted to IEEE Transactions on Computational Imaging. Worked on by Shijun Liang. (arXiv)
2024
12/20/24: "Sequential Diffusion-Guided Deep Image Prior For Medical Image Reconstruction" has been accepted to ICASSP25. Worked on my Ismail Alkhouri, Shijun Liang, and Dr. Ravishankar. (arXiv)
09/25/24: "Image Reconstruction Via Autoencoding Sequential Deep Image Prior" has been accepted at NeurIPS 2024 as a poster! Worked on by Ismail Alkhouri, Shijun Liang, and Evan Bell.
08/22/24: The paper "Learning Robust Features for Scatter Removal and Reconstruction in Dynamic ICF X-Ray Tomography" has been submitted to arXiv. Worked on by Siddhant Gautam and Dr. Ravishankar. (arXiv)
07/23/24: The paper, "Time projection chamber for GADGET II," has been accepted in Physical Review C (PRC). Worked on my Tyler Wheeler and Dr. Ravishankar. (PRC)
06/17/24: Dr. Ravishankar, Angqi Li, Pratham Pradhan as well as SLIM collaborators co-hosted the first talk of the Data-driven Understanding of Meditation and Consciousness (DUNES) Webinar Series. Presented by Dr. Lazar.
05/15/24: Dr. Ravishankar received the NSF Award for Research Experiences for Undergraduates (REU) for supporting 4 undergraduate researchers, along with Dr. Wang. This will be part of the CISE Medium Award for research on "Taming Deep Unsupervised Representation Learning in Imaging: Theory and Algorithms".
05/07/24: Abstract on "Understanding Longitudinal Effects of Mantra Meditation and Breath-focused Meditation using EEG" submitted to Neuroscience 2024.
05/01/24: Paper titled "Optimal Eye Surgeon: Finding image priors through sparse generators at initialization" accepted at the International Conference on Machine Learning (ICML) 2024. Worked on by Avrajit Ghosh, Kenneth Sun, Dr. Qu, Dr. Ravishankar, and Dr. Wang. (ICML)
05/01/24: Abstract titled "Pruning Unrolled Networks (PUN) at Initialization for MRI Reconstruction Improves Generalization" submitted to session on Machine Learning Methods for Inverse Problems in Biomedical Imaging at the Asilomar Conference on Signals, Systems, and Computers, 2024 (Invited).
03/23/24: Paper on "Adaptive Local Neighborhood-based Neural Networks for MR Image Reconstruction from Undersampled Data" accepted to IEEE Transactions on Computational Imaging. Worked on by Shijun Liang, Anish Lahiri, and Saiprasad Ravishankar. (arXiv)
03/18/24: Tyler Wheeler concludes his Ph.D. thesis defense and is reintroduced to the group as a postdoc. Congratulations!

2023
12/15/23: Paper on "Patient-adaptive and Learned MRI Data Undersampling Using Neighborhood Clustering" accepted to IEEE ICASSP 2024. Worked on by Siddhant Gautam. (arXiv)
12/13/23: Paper on "Diffusion-based Adversarial Purification for Robust Deep MRI Reconstruction" accepted to IEEE ICASSP 2024. Worked on by Ismail Alkhouri and Shijun Liang. (arXiv)
11/30/23: Siddhant has been invited for an oral presentation entitled "Scatter Removal in Dynamic X-Ray Tomography using Robust Features," at the Machine Learning for Scientific Imaging Conference, at Electronic Imaging 2024 from January 21-25 in Burlingame, CA USA.
11/20/23: Lanlang Feng joins SLIM for one year as a visiting Ph.D. student from the University of Electronic Science and Technology of China (UESTC)!
11/06/23: Dr. Ravishankar has been elected to the IEEE MLSP Technical Committee 2024. Congratulations!
10/28/23: Paper on "Patient-adaptive and Learned MRI Data Undersampling Using Neighborhood Clustering" accepted for presentation at Med-Neurips 2023. Worked on by Siddhant Gautam, Angqi Li, and Dr. Ravishankar.
09/04/23: Evan Bell, Madeline Mitchell, Annie Wozniak, and Kenneth Sun are beginning an NSF REU with the SLIM Group and Dr. Rongrong Wang (CMSE).
08/17/23: Proposal on "Machine Learning for Time Projection Chambers at FRIB" funded by the Department of Energy. Dr Wrede (FRIB) and Dr. Ravishankar will lead this project at MSU.
07/26/23: Dr. Ravishankar will be organizing a special session on "Robust Reconstruction Methods in Computational Imaging" at IEEE ICASSP 2024.
07/18/23: Dr. Ravishankar presented work on "Unifying Supervised and Unsupervised Methods for Low-dose CT Reconstruction: a General Framework" at the Fully3D Conference, 2023. Collaborated with Zhishen Huang and UM-SJTU Joint Institute.
07/17/23: Paper on "Multi-layer Clustering-based Residual Sparsifying Transform for Low-dose CT Image Reconstruction" accepted for publication in Medical Physics. (arXiv)
07/10/23: Ismail Alkhouri joins SLIM as a postdoctoral research associate and a visiting scholar at UMich, Ann Arbor!
07/09/23: Dr. Ravishankar virtually presented the tutorial on "Machine Learning for Image and Multimedia Reconstruction: From Sparse Modeling to Deep Neural Networks" at IEEE International Conference on Multimedia and Expo (ICME) 2023.
06/18/23: Dr. Ravishankar will be organizing a special session on "Learning and Optimization for Computational Imaging" at IEEE CAMSAP 2023.
06/14/23: Abstract on "Measuring the effectiveness of mantra-based meditation using EEG data analysis" — worked on by Angqi Li, Pratham Pradhan, and Annie Wozniak — accepted for presentation at the Society of Neuroscience 2023.
06/12/23: Paper on "Learning Sparsity-Promoting Regularizers using Bilevel Optimization" accepted for publication in the SIAM Journal on Imaging Sciences. Worked on by Avrajit Ghosh, Mike McCann, and Madeline Mitchell.
05/15/23: PhD student Gabriel and undergraduate Evan Bell will do a summer internship at Los Alamos National Laboratory.
04/19/23: Dr. Ravishankar led two-part tutorial at the IEEE International Symposium on Biomedical Imaging (ISBI) on "Recent Advances in Machine Learning for Image Reconstruction: From Sparse Modeling to Deep Networks". PhD students Avrajit Ghosh, Gabriel Maliakal, and Shijun Liang, along with NTU collaborator Dr. Bihan Wen and his team, also contributed and spoke at the tutorial.
04/12/23: Dr. Ravishankar received the NSF Award for Research Experiences for Undergraduates (REU) for supporting four undergraduate researchers, along with Dr. Rongrong Wang. This will be part of the CISE Medium Award for research on "Taming Deep Unsupervised Representation Learning in Imaging: Theory and Algorithms".
03/31/23: Work on "Unifying Supervised and Unsupervised Methods for Low-dose CT Reconstruction: a General Framework" accepted at the Fully3D Conference, 2023.
02/17/23: Papers on "Robust Self-Guided Deep Image Prior" and "SMUG: Towards Robust MRI Reconstruction by Smoothed Unrolling" accepted for presentation at IEEE ICASSP, 2023.
02/15/23: Brainwave Science is supporting our research on "Using EEG Imaging and Data Analysis to Understand the Effects of Meditation and Its Benefits for Health".
01/23/23: Paper on "Deep Reinforcement Learning based Unrolling Network for MRI Reconstruction" accepted for presentation at the IEEE International Symposium on Biomedical Imaging (ISBI), 2023.
01/03/23: Dr. Ravishankar spoke at the Third Workshop on Seeking Low-Dimensionality in Deep Neural Networks (SLowDNN) in Abu Dhabi, UAE. Avrajit Ghosh, Gabriel Maliakal, and Evan Bell also presented their research.

2022
11/17/22: Dr. Ravishankar gave an invited talk on "Advancing Machine Learning for Imaging: Regularization and Robustness" in the Communications and Signal Processing (CSP) Seminar Series at the University of Michigan.
11/11/22: Dr. Ravishankar, Siddhant Gautam, Angqi Li, Minh Nguyen, and Pratham Pradhan organize the 2nd CMSE Data Science Student Conference (DISC) 2022 in the Michigan State University campus.
10/07/22: Paper on "Sparse-view Cone Beam CT Reconstruction using Data-consistent Supervised and Adversarial Learning from Scarce Training Data" has been accepted to the IEEE Transactions on Computational Imaging (arXiv). Worked on by Anish Lahiri.
10/05/22: Paper on "Learning Nonlocal Sparse and Low-Rank Models for Image Compressive Sensing" accepted to the IEEE Signal Processing Magazine Special Issue on Physics-Driven Machine Learning for Computational Imaging. (arXiv)
09/30/22: Dr. Ravishankar gave a talk at the Annual Allerton Conference on Communication, Control, and Computing on "Robust Deep Image Prior for MRI Reconstruction with Partial Guidance".
09/20/22: Dr. Ravishankar will be organizing a special session on "Unsupervised Deep Learning of Image Priors for Inverse Problems" at ICASSP 2023.
09/15/22: Dr. Ravishankar received an NIH R21 Award (from NIBIB) for doing research on "Machine Learning-Based Adaptation of Data Sampling and Reconstruction for Efficient Dynamic MRI".
09/02/22: Undergraduates Minh Nguyen and Pratham Pradhan join SLIM as Professorial Assistants (PA).
08/30/22: Dr. Ravishankar is invited to present in Mini Symposium on "Recent Advances in Inverse Problems for Computational Imaging’’ at the 2023 SIAM Conference on Computational Science and Engineering. Talk Title: Improving the Robustness of Deep Unrolling-based MRI Reconstruction by Learned Randomized Smoothing.
06/20/22: Dr. Ravishankar's co-authored paper on "RePnP: Plug-and-Play with Deep Reinforcement Learning Prior for Robust Image Restoration" accepted to IEEE ICIP 2022. Worked on by Bihan Wen and team at NTU, Singapore.
06/14/22: Dr. Ravishankar gave an invited talk on "Robust Deep Image Prior with Partial Guidance" in the Allerton Conference's session on Imaging and Data Science.
06/01/22: Paper on "Adaptive Local Neighborhood-based Neural Networks for MR Image Reconstruction from Undersampled Data" posted online (arXiv). Worked on by Anish Lahiri and Shijun Liang.
05/26/22: Dr. Ravishankar recieved an NSF Award from the CISE Directorate for a Medium Project on "Taming Deep Unsupervised Representation Learning in Imaging: Theory and Algorithms". This will be work between MSU and UMich (Prof. Qing Qu).
05/17/22: PhD student Siddhant Gautam will do a summer internship at Dolby Laboratories. PhD student student Gabriel Maliakal will do a summer internship at Los Alamos National Lab.
03/25/22: Dr. Ravishankar gave an invited talk on "Learning Regularizers for Image Reconstruction" virtually at Bilkent University, Turkey.
03/23/22: Work on "Single-pass Object-adaptive Data Undersampling and Reconstruction for MRI" has been accepted to the IEEE Transactions on Computational Imaging (arXiv). Worked on by Zhishen Huang.
03/18/22: Abstract on "Comparing one-step and two-step scatter correction and density reconstruction in X-ray CT" accepted at the CT Meeting, 2022. Work on by Alexander Sietsema (MSU Undergrad) and Los Alamos National Laboratory collaborators. (arXiv)
03/15/22: Paper on "Physics-Driven Learning of Wasserstein GAN for Density Reconstruction in Dynamic Tomography" accepted for publication in Applied Optics. Work on by Dr. Zhishen Huang (Postdoc) and Los Alamos National Laboratory collaborators. (arXiv)
02/28/22: Recent works (this and this) with PhD student Tyler Wheeler and Nuclear Astrophysics team at MSU.
02/05/22: Abstract on "Optimized Parallel Combination of Deep Networks and Sparsity Regularization for MR Image Reconstruction (OPCoNS) " accepted at ISMRM 2022. Worked on by Avrajit Ghosh, Shijun Liang, and Anish Lahiri (UM postdoc).
01/21/22: Our paper on "Bilevel learning of l1 regularizers with closed-form gradients (BLORC)" has been accepted at ICASSP 2022. Worked on by Avrajit Ghosh and Dr. Michael McCann (LANL). (arXiv)
01/09/22: White paper on "Learning Nonlocal Sparse and Low-Rank Models for Image Compressive Sensing" accepted in the Special Issue on Physics-Driven Machine Learning for Computational Imaging in the IEEE Signal Processing Magazine.
01/07/22: Paper titled "LONDN-MRI: Adaptive Local Neighborhood-based Networks for MR Image Reconstruction from Undersampled Data" has been accepted to ISBI 2022. Worked on by Shijun Liang, Ashwin Sreevatsa (Undergraduate summer intern in SLIM in 2021), and Anish Lahiri (UM postdoc).

2021
12/08/21: Dr. Ravishankar gave an invited talk in the "From Cells to Galaxies – Exploring the Synergies between Radio Astronomy and Medical Imaging" Virtual Speaker Series on "Machine Learning for Medical Image Reconstruction".
11/02/21: Dr. Ravishankar presented a talk on "Descattering and Density Reconstruction in Polyenergetic X-Ray Tomography with Locally Learned Models" at the Asilomar Conference on Signals, Systems, and Computers, 2021.
10/29/21: Dr. Ravishankar gave an invited talk at the third Deep Reconstruction Workshop during November 14-15, 2021. Talk title: Improving Deep Learning for MR Image Reconstruction by Exploiting Structured Patient-Adaptive Representations.
10/04/21: Extended abstract on "Adaptive Local Neighborhood-based Networks for MR Image Reconstruction from Undersampled Data" accepted to the 2nd Learning for Computational Imaging Workshop at ICCV 2021. Presented as oral by Shijun Liang.
08/16/21: Paper on "Local Models for Scatter Estimation and Descattering in Polyenergetic X-Ray Tomography" accepted for publication in Optics Express. Worked on by Mike McCann.
08/16/21: Graduate students Cassandra Lem and Gabriel Maliakal joined SLIM group.
07/27/21: Dr. Ravishankar gave an invited talk at the AAPM Meeting 2021 on "Machine Learning for Low-dose Computed Tomography Reconstruction".
06/28/21: Paper on "Unified Supervised-Unsupervised (SUPER) Learning for X-ray CT Image Reconstruction" accepted for publication in the IEEE Transactions on Medical Imaging. (arXiv)
06/24/21: Paper on "Blind Primed Supervised (BLIPS) Learning for MR Image Reconstruction" accepted to the IEEE Transactions on Medical Imaging. (arXiv)
05/20/21: Paper on "LABMAT: Learned Feature-domain Block Matching for Image Restoration" accepted at ICIP 2021. Worked on by Shijun Liang (PhD student), Berk Iskender (SLIM intern during Summer 2020), and Bihan Wen (NTU, Singapore).
05/20/21: Paper on "Multi-layer Residual Sparsifying Transform (MARS) Model for Low-dose CT Image Reconstruction" accepted for publication in Medical Physics (arXiv). Collaborated with UM-SJTU Joint Institute.
04/28/21: Our papers on "Limited-view Cone Beam CT reconstruction using 3D Patch-based Supervised and Adversarial Learning" and "Descattering and Reconstruction in Multimaterial Polyenergetic X-Ray Tomography Using Local Scatter Models" have been accepted for oral presentation at the OSA Imaging and Applied Optics Congress, 2021.
04/05/21: Postdoc Dr. Michael McCann will be joining Los Alamos National Laboratory as a Research Scientist in May. Congratulations to Mike!
04/05/21: Dr. Ravishankar gave a virtual invited talk in the LANSCE Futures Spring 2021 Workshop Series, Workshop on Dynamic Radiography, held at Los Alamos National Laboratory. Talk title: Limited-View Cone Beam CT Reconstructions using 3D Patch Based Supervised and Unsupervised Adversarial Learning.
03/31/21: Two abstracts on "Two-layer Clustering-based Sparsifying Transform Learning for Low-dose CT Reconstruction" and "Learning Overcomplete or Undercomplete Models in Clustering-based Low-dose CT Reconstruction" accepted for oral presentations at the International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 2021. Jointly worked on by Xikai Yang, Ling Chen, and Yong Long at the UM-SJTU Joint Institute.
03/14/21: Dr Ravishankar, Dr. Zhishen Huang (Postdoc), and Dr. Gregory Ongie (Marquette University) will be organizing a special session on "Model-based deep learning for inverse problems in imaging" at the Asilomar Conference on Signals, Systems, and Computers, 2021.
02/24/21: Abstract on "Blind Primed Supervised (BLIPS) Learning for MR Image Reconstruction" accepted for presentation in an Oral Scientific session at ISMRM 2021. Work between Dr. Ravishankar and Anish Lahiri, Guanhua Wang, and Jeff Fessler at UM.
01/29/21: Two co-authored papers on "Self-Convolution: A Highly-Efficient Operator for Non-Local Image Restoration" and "Learning Sparsifying Transforms for Image Reconstruction in Electrical Impedence Tomography" accepted for presentation at IEEE ICASSP 2021. Works between Dr. Ravishankar and Dr. Bihan Wen and team at NTU, Singapore.

2020
11/19/20: Prof. Ravishankar gave a research talk at Purdue University.
11/09/20: The ARS Foundation will fund our group for developing methods for fast magnetic resonance imaging (MRI).
08/25/20: Prof. Ravishankar gave a Talk in the SPACE webinar series titled "From Transform Learning to Deep Learning and Beyond for Imaging". See YouTube version here.
08/17/20: Postdoc Dr. Zhishen Huang joined the group with a PhD from the Department of Applied Mathematics at the University of Colorado, Boulder.
07/07/20: Postdoc Dr. Michael McCann presented talk on "Learning Regularizers for Image Reconstruction" at the SIAM Conference on Imaging Science (IS20). Abstract here.
06/09/20: Paper on "Supervised Learning of Sparsity-Promoting Regularizers for Denoising" by Dr. McCann and Prof. Ravishankar posted to arXiv.
05/19/20: Prof. Ravishankar is co-organizing the SPACE Webinar Series.
05/16/20: The group received funding from a LANL/DOE award for "Methods for Inverse Problems: Models, Algorithms, Machine Learning, and Theory".
05/16/20: Anish Lahiri (EECS, UM) and Berk Iskender (ECE, UIUC) joined as summer interns.