Research
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An inverse design framework for optimizing tensile strength of composite materials based on a CNN surrogate for the phase field fracture model
Gao, Yuxiang; Duddu, Ravindra; Kolouri, Soheil; Gupta, Abhinav; Prabhakar, Pavana. “An inverse design framework for optimizing tensile strength of composite materials based on a CNN surrogate for the phase field fracture model.” Composites Part A: Applied Science and Manufacturing, vol. 192, 2025, 108758, https://doi.org/10.1016/j.compositesa.2025.108758… Read MoreMar. 24, 2025
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Head Motion in Diffusion Magnetic Resonance Imaging: Quantification, Mitigation, and Structural Associations in Large, Cross-Sectional Datasets Across the Lifespan
Schilling, Kurt G.; Ramadass, Karthik; Sairanen, Viljami; Kim, Michael E.; Rheault, Francois; Newlin, Nancy; Nguyen, Tin; Barquero, Laura; D’archangel, Micah; Gao, Chenyu; Topolnjak, Ema; Khairi, Nazirah Mohd; Archer, Derek; Beason-Held, Lori L.; Resnick, Susan M.; Hohman, Timothy; Cutting, Laurie; Schneider, Julie; Barnes, Lisa L.; Bennett, David A.; Arfanakis, Konstantinos;… Read MoreMar. 24, 2025
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Learning disentangled representations to harmonize connectome network measures
Newlin, Nancy R.; Kim, Michael E.; Kanakaraj, Praitayini; Pechman, Kimberly; Shashikumar, Niranjana; Moore, Elizabeth; Archer, Derek; Hohman, Timothy; Jefferson, Angela; Moyer, Daniel; Landman, Bennett A. “Learning disentangled representations to harmonize connectome network measures.” Journal of Medical Imaging, vol. 12, no. 1, 2025, 14004, https://doi.org/10.1117/1.JMI.12.1.014004… Read MoreMar. 24, 2025
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Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3—Ex vivo imaging: Data processing, comparisons with microscopy, and tractography
Schilling, Kurt G.; Howard, Amy F. D.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Barrett, Rachel L. C.; Aggarwal, Manisha; Michielse, Stijn; Nasrallah, Fatima; Syeda, Warda; Wang, Nian; Veraart, Jelle; Roebroeck, Alard; Bagdasarian, Andrew F.; Eichner, Cornelius; Sepehrband, Farshid; Zimmermann, Jan; Soustelle, Lucas; Bowman, Christien; Tendler, Benjamin C.; Hertanu, Andreea;… Read MoreMar. 24, 2025
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Longitudinal patterns of brain aging and neurodegeneration among older adults with dual decline in memory and gait
Tian, Qu; Greig, Erin E.; Walker, Keenan A.; Duggan, Michael R.; Yang, Zhijian; Moghekar, Abhay; Landman, Bennett A.; Davatzikos, Christos; Resnick, Susan M.; Ferrucci, Luigi. “Longitudinal patterns of brain aging and neurodegeneration among older adults with dual decline in memory and gait.” Alzheimer’s & dementia : the… Read MoreMar. 24, 2025
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Partial transport for point-cloud registration
Bai, Yiku; Tran, Huy; Damelin, Steven B.; Kolouri, Soheil. “Partial transport for point-cloud registration.” Sampling Theory, Signal Processing, and Data Analysis, vol. 23, no. 1, 2025, 4, https://doi.org/10.1007/s43670-025-00097-1. Point cloud registration is a key task in areas like robotics, computer graphics,… Read MoreMar. 24, 2025
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Explainable AI for medical image analysis
Brás, Carolina; Montenegro, Helena; Cai, Leon Y.; Corbetta, Valentina; Huo, Yuankai; Silva, Wilson; Cardoso, Jaime S.; Landman, Bennett A.; IÅ¡gum, Ivana. “Explainable AI for medical image analysis.” Trustworthy Ai in Medical Imaging, 2024, pp. 347-366, https://doi.org/10.1016/B978-0-44-323761-4.00028-6. As AI-driven solutions are… Read MoreMar. 24, 2025
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BrainWash: A Poisoning Attack to Forget in Continual Learning
Abbasi, Ali; Nooralinejad, Parsa; Pirsiavash, Hamed; Kolouri, Soheil. “BrainWash: A Poisoning Attack to Forget in Continual Learning.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2024, pp. 24057-24067, https://doi.org/10.1109/CVPR52733.2024.02271. Continual learning, a field within deep learning,… Read MoreMar. 24, 2025
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Statistical Context Detection for Deep Lifelong Reinforcement Learning
Dick, J., Nath, S., Peridis, C., Benjamin, E., Kolouri, S., & Soltoggio, A. (2024). “Statistical Context Detection for Deep Lifelong Reinforcement Learning.” Proceedings of Machine Learning Research, 274, 1013-1031. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85219511357&partnerID=40&md5=44236f24c54c2e13e04ef41cc8a97b90Â Context detection involves identifying different tasks within a continuous stream of data. Read MoreMar. 24, 2025
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Equivariant vs. Invariant Layers: A Comparison of Backbone and Pooling for Point Cloud Classification
Machine learning models are increasingly being used to analyze point cloud data, which consists of unordered sets of points, such as 3D scans of objects. To effectively process this type of data, neural networks must be designed to ensure that their predictions remain the same regardless of the order… Read MoreFeb. 24, 2025