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portfolio
publications
In vivo mapping of amyloid toxicity in Alzheimer’s disease
Published in Neurology, 2009
PET-based in vivo mapping of amyloid-beta toxicity and its regional effects on brain function in Alzheimer's disease.
Enrichment through biomarkers in clinical trials of Alzheimer’s drugs in patients with mild cognitive impairment
Published in Neurobiology of Aging, 2010
Strategy for patient enrichment using biomarkers in clinical trials for Alzheimer's disease in MCI patients.
Metabolic compensation and depression in Alzheimer’s disease
Published in Dementia and Geriatric Cognitive Disorders, 2010
PET study of metabolic compensation mechanisms and their relationship with depression in Alzheimer's disease.
4D registration of serial brain MRI images: a robust measure of changes applied to Alzheimer’s disease
Published in MICCAI Workshop on Spatio-Temporal Image Analysis for Longitudinal and Time-Series Image Data (STIA 2010), 2010
4D diffeomorphic registration framework for serial brain MRI providing robust measures of longitudinal changes in Alzheimer's disease.
Mapping the effects of Aβ1-42 levels on the longitudinal changes in healthy aging
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2011
Mapping the influence of amyloid-beta on longitudinal brain changes in healthy aging using diffeomorphic methods.
Schild’s ladder for the parallel transport of deformations in time series of images
Published in Information Processing in Medical Imaging (IPMI), 2011
Schild’s ladder scheme for parallel transport of diffeomorphic deformations along geodesics in image time series.
Effect of memantine on resting state default mode network activity in Alzheimer’s disease
Published in Drugs and Aging, 2011
fMRI study of the effect of memantine on default mode network activity in Alzheimer's disease.
Geodesics, parallel transport & one-parameter subgroups for diffeomorphic image registration
Published in 3rd MICCAI Workshop on Mathematical Foundations of Computational Anatomy (MFCA 2011), 2011
Workshop contribution on geodesics and parallel transport for diffeomorphic image registration.
Regional flux analysis of longitudinal atrophy in Alzheimer’s disease
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2012
Regional flux analysis applied to longitudinal brain atrophy in Alzheimer’s disease.
Probabilistic Flux Analysis of Cerebral Longitudinal Atrophy
Published in MICCAI Workshop on Novel Imaging Biomarkers for Alzheimer's Disease (NIBAD 2012), 2012
Probabilistic flux analysis for detecting and quantifying longitudinal cerebral atrophy patterns.
Sparse scale-space decomposition of volume changes in deformation fields
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2013
Sparse decomposition method for analyzing volume changes encoded in diffeomorphic deformation fields.
LCC-Demons: a robust and accurate symmetric diffeomorphic registration algorithm
Published in NeuroImage, 2013
LCC-Demons: symmetric diffeomorphic image registration based on the Local Correlation Coefficient similarity measure.
Geodesics, Parallel Transport & One-parameter Subgroups for Diffeomorphic Image Registration
Published in International Journal of Computer Vision, 2013
Theoretical framework for geodesics, parallel transport, and one-parameter subgroups in the context of diffeomorphic image registration.
Structural brain features of borderline personality and bipolar disorders
Published in Psychiatry Research: Neuroimaging, 2013
Comparative MRI study of structural brain differences in borderline personality disorder and bipolar disorder.
Parallel Transport with Pole Ladder: Application to Deformations of Time Series of Images
Published in Geometric Science of Information (GSI 2013), 2013
Pole Ladder scheme for parallel transport of diffeomorphic deformations, applied to time series of images.
Efficient Parallel Transport of Deformations in Time Series of Images: from Schild’s to Pole Ladder
Published in Journal of Mathematical Imaging and Vision, 2014
Efficient algorithms for parallel transport of diffeomorphic deformations along geodesics, comparing Schild's and Pole Ladder schemes.
Impact of alcohol consumption in healthy adults: A magnetic resonance imaging investigation
Published in Psychiatry Research: Neuroimaging, 2014
MRI investigation of the impact of alcohol consumption on brain structure in healthy adults.
A biophysical model of shape changes due to atrophy in the brain with Alzheimer’s disease
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2014), 2014
Biophysical model of brain shape deformation driven by atrophy in Alzheimer's disease.
Discrete Ladders for Parallel Transport in Transformation Groups with an Affine Connection Structure
Published in Geometric Theory of Information Signals and Communication Technology (Springer), ed. Nielsen, 2014
Discrete ladder algorithms for parallel transport in transformation groups equipped with an affine connection structure.
Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge
Published in NeuroImage, 2015
Comparative evaluation of brain atrophy measurement algorithms in dementia from the MIRIAD challenge.
Regional flux analysis for discovering and quantifying anatomical changes: An application to the brain morphometry in Alzheimer’s disease
Published in NeuroImage, 2015
Regional flux analysis method to discover and quantify longitudinal anatomical changes in Alzheimer’s disease.
Disentangling normal aging from Alzheimer’s disease in structural magnetic resonance images
Published in Neurobiology of Aging, 2015
Statistical model to separate normal aging from Alzheimer’s disease-specific brain changes in MRI.
Efficient Gaussian process-based modelling and prediction of image time series
Published in Information Processing in Medical Imaging (IPMI 2015), 2015
Gaussian process framework for efficient modelling and prediction of longitudinal image time series.
A Riemannian framework for intrinsic comparison of closed genus-zero shapes
Published in Information Processing in Medical Imaging (IPMI 2015), 2015
Riemannian framework for intrinsic shape comparison and analysis of closed genus-zero surfaces.
Modelling Non-Stationary and Non-Separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution
Published in 1st ICML Workshop on Machine Learning Meets Medical Imaging, 2015
Gaussian process convolution model for non-stationary spatio-temporal changes in neurodegeneration.
Longitudinal Analysis of Image Time Series with Diffeomorphic Deformations: A Computational Framework Based on Stationary Velocity Fields
Published in Frontiers in Neuroscience, 2016
Computational framework for longitudinal image time series analysis using diffeomorphic deformations.
Multimodal Image Analysis in Alzheimer’s Disease via Statistical Modelling of Non-local Intensity Correlations
Published in Scientific Reports, 2016
Statistical model for multimodal neuroimaging analysis in Alzheimer's disease using non-local intensity correlations.
Longitudinal analysis of the preterm cortex using multi-modal spectral matching
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2016), 2016
Multi-modal spectral matching approach for longitudinal analysis of cortical development in preterm infants.
Accurate small deformation exponential approximant to integrate large velocity fields: Application to image registration
Published in IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2016), 2016
Efficient exponential approximation for integrating large velocity fields with application to diffeomorphic image registration.
Partial Least Squares Modelling for Imaging Genetics in Alzheimer’s Disease: Plausibility and Generalization
Published in IEEE International Symposium on Biomedical Imaging (ISBI 2016), 2016
Partial least squares approach for imaging genetics analysis in Alzheimer's disease, evaluating plausibility and generalization.
A biophysical model of brain deformation to simulate and analyze longitudinal MRIs of patients with Alzheimer’s disease
Published in NeuroImage, 2017
Biophysical model of brain deformation for simulating longitudinal MRI changes in Alzheimer’s disease.
Disease Progression Modeling and Prediction through Random Effect Gaussian Processes and Time Transformation
Published in arXiv preprint arXiv:1701.01668, 2017
Random effect Gaussian process model for disease progression, introducing patient-specific time transformations to align individual trajectories.
Selection bias in the reported performances of AD classification pipelines
Published in NeuroImage: Clinical, 2017
Analysis of selection bias in Alzheimer's disease classification pipelines and its impact on reported performance metrics.
Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer’s disease
Published in NeuroImage, 2017
Gaussian Process Progression Model (GPPM) for probabilistic disease staging and biomarker trajectory estimation in Alzheimer’s disease.
A vertex clustering model for disease progression: application to cortical thickness images
Published in Information Processing in Medical Imaging (IPMI 2017), 2017
Vertex clustering model for spatiotemporal disease progression applied to cortical thickness in Alzheimer's disease.
Secure multivariate large-scale multi-centric analysis through on-line learning: an imaging genetics case study
Published in 12th International Symposium on Medical Information Processing and Analysis (SIPAIM 2017), 2017
Privacy-preserving multivariate online learning for large-scale multi-centric imaging genetics analysis.
A magnetic resonance multi-atlas for the neonatal rabbit brain
Published in NeuroImage, 2018
Construction of a multi-atlas for MRI-based brain analysis in neonatal rabbits.
Genetic study of multimodal imaging Alzheimer’s disease progression score implicates novel loci
Published in Brain, 2018
GWAS of a multimodal imaging-based Alzheimer’s disease progression score identifies novel genetic loci.
Susceptibility of brain atrophy to TRIB3 in Alzheimer’s disease, evidence from functional prioritization in imaging genetics
Published in Proceedings of the National Academy of Sciences, 2018
Imaging genetics analysis identifying TRIB3 as a susceptibility gene for brain atrophy in Alzheimer’s disease.
Model-based refinement of nonlinear registrations in 3D histology reconstruction
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2018), 2018
Model-based approach for refining nonlinear registrations in 3D histology reconstruction from serial sections.
Constraining the Dynamics of Deep Probabilistic Models
Published in International Conference on Machine Learning (ICML 2018), 2018
Framework for constraining the dynamics of deep probabilistic models, with application to disease progression modeling via gradient matching.
Alzheimer’s Disease Modelling and Staging through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes
Published in arXiv preprint arXiv:1808.06367, 2018
Independent Gaussian process model for staging and characterizing spatio-temporal brain changes in Alzheimer’s disease.
Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data
Published in International Conference on Machine Learning (ICML 2019), 2018
Multi-Channel Variational Autoencoder (MCVAE) for joint latent representation learning from heterogeneous multimodal data using variational dropout for sparse encoding.
Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data
Published in IEEE International Symposium on Biomedical Imaging (ISBI 2019), Venice, 2018
One of the first applications of federated learning to medical imaging: meta-analysis of subcortical brain structures across distributed datasets.
Disease Knowledge Transfer across Neurodegenerative Diseases
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019
Transfer learning approach for sharing disease knowledge across different neurodegenerative conditions.
Differences in topological progression profile among neurodegenerative diseases from imaging data
Published in eLife, 2019
Data-driven comparison of topological disease progression patterns across neurodegenerative diseases.
A model of brain morphological changes related to aging and Alzheimer’s disease from cross-sectional assessments
Published in NeuroImage, 2019
Statistical model disentangling aging and Alzheimer’s disease effects on brain morphology from cross-sectional data.
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders
Published in NeuroImage, 2019
DIVE: a spatiotemporal model estimating regional ordering and timing of brain pathology progression.
Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort
Published in NeuroImage, 2019
Spatiotemporal shape analysis for detecting pre-symptomatic brain changes in genetic frontotemporal dementia.
Modeling and inference of spatio-temporal protein dynamics across brain networks
Published in Information Processing in Medical Imaging (IPMI 2019), 2019
Spatio-temporal model for inferring protein propagation dynamics across brain networks in neurodegeneration.
Enhancing OCT signal by fusion of GANs: improving statistical power of glaucoma clinical trials
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2019), 2019
GAN-based OCT signal enhancement to improve statistical power in glaucoma clinical trials.
Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions
Published in Functional Imaging and Modeling of the Heart (FIMH 2019), 2019
Large-scale personalisation of a cardiovascular biophysical model for studying heart-brain interactions.
Multivariate Learning in Distributed Biomedical Databases: Meta-analysis of Large-scale Brain Imaging Data
Published in IEEE International Symposium on Biomedical Imaging (ISBI 2019), Venice, 2019
Federated multivariate learning for meta-analysis of large-scale subcortical brain imaging data across distributed databases.
Voxel-based assessments of treatment effects on longitudinal brain changes in the Multidomain Alzheimer Preventive Trial cohort
Published in Neurobiology of Aging, 2020
Voxel-based analysis of longitudinal brain changes in response to multidomain preventive interventions.
Monotonic Gaussian Process for spatio-temporal disease progression modeling in brain imaging data
Published in NeuroImage, 2020
A monotonic Gaussian process model for spatiotemporal disease progression in neuroimaging.
Joint data imputation and mechanistic modelling for simulating heart-brain interactions in incomplete datasets
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2020), 2020
Combined data imputation and biophysical modelling to simulate heart-brain interactions in datasets with missing data.
Fed-BioMed: A general open-source frontend framework for federated learning in healthcare
Published in 1st MICCAI Workshop on Distributed and Collaborative Learning (DCL 2020), 2020
Introduction of Fed-BioMed, an open-source framework for federated learning in healthcare applications.
Estimation of imaging biomarker’s progression in post-infarct patients using cross-sectional data
Published in Statistical Atlases and Computational Models of the Heart (STACOM 2020), 2020
Cross-sectional estimation of imaging biomarker progression in post-myocardial infarction patients.
Beyond Riemannian geometry: The affine connection setting for transformation groups
Published in Riemannian Geometric Statistics in Medical Image Analysis (Elsevier), eds. Pennec, Sommer, Fletcher, 2020
Theoretical framework extending Riemannian geometry to affine connection settings for transformation groups in medical image analysis.
Free-rider Attacks on Model Aggregation in Federated Learning
Published in International Conference on Artificial Intelligence and Statistics (AISTATS 2021), 2020
Analysis of free-rider attacks in federated learning where malicious clients exploit aggregation without contributing.
Revealing the Timeline of Structural MRI Changes in Premanifest to Manifest Huntington Disease
Published in Neurology Genetics, 2021
Spatiotemporal modeling of structural MRI changes across the Huntington disease timeline.
Simulating the outcome of amyloid treatments in Alzheimer’s disease from imaging and clinical data
Published in Brain Communications, 2021
A computational model to simulate and predict the outcome of amyloid-targeting treatments in Alzheimer’s disease.
Biophysics-based statistical learning: Application to heart and brain interactions
Published in Medical Image Analysis, 2021
Integration of biophysical modeling and statistical learning for heart-brain interaction analysis.
Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain
Published in NeuroImage, 2021
A Gaussian process progression model for learning protein propagation dynamics in neurodegeneration.
Improving statistical power of glaucoma clinical trials using an ensemble of cyclical generative adversarial networks
Published in Medical Image Analysis, 2021
GAN-based data augmentation to improve statistical power in glaucoma clinical trials.
OCT Signal Enhancement with Deep Learning
Published in Ophthalmology Glaucoma, 2021
Deep learning approach for enhancing optical coherence tomography signal quality.
Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction
Published in Medical Image Analysis, 2021
A robust method for joint registration of histological stains and MRI for 3D reconstruction.
Vessel-CAPTCHA: An efficient learning framework for vessel annotation and segmentation
Published in Medical Image Analysis, 2021
An efficient active learning framework for vessel annotation and segmentation in medical images.
Phase-independent latent representation for cardiac shape analysis
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2021), 2021
Phase-independent latent representation for cardiac shape analysis across the cardiac cycle.
A probabilistic framework for modeling the variability across federated datasets
Published in Information Processing in Medical Imaging (IPMI 2021), 2021
Probabilistic framework for modeling inter-site variability across federated biomedical datasets.
Multivariate data analysis suggests the link between brain microstructure and cognitive impairment in multiple sclerosis
Published in IEEE International Symposium on Biomedical Imaging (ISBI 2021), 2021
Multivariate analysis of brain microstructure and cognitive impairment in multiple sclerosis.
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Published in International Conference on Machine Learning (ICML 2021), 2021
Clustered sampling strategy for client selection in federated learning, reducing variance and improving representativity.
Decoding Genetic Markers of Multiple Phenotypic Layers Through Biologically Constrained Genome-To-Phenome Bayesian Sparse Regression
Published in Frontiers in Molecular Medicine, 2022
Bayesian sparse regression model associating genetic data to multiple phenotypic features through biologically inspired constraints.
SimulAD: a dynamical model for personalized simulation and disease staging in Alzheimer’s disease
Published in Neurobiology of Aging, 2022
A dynamical model enabling personalized simulation and staging of Alzheimer’s disease progression.
Predicting Visual Fields From Optical Coherence Tomography via an Ensemble of Deep Representation Learners
Published in American Journal of Ophthalmology, 2022
Deep learning ensemble to predict visual fields from OCT data in glaucoma.
Predicting myocardial infarction through retinal scans and minimal personal information
Published in Nature Machine Intelligence, 2022
Deep learning approach predicting myocardial infarction risk from retinal fundus photographs and minimal clinical data.
Privacy Preserving Image Registration (Conference Version)
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022), 2022
Privacy-preserving image registration method for federated medical imaging, presented at MICCAI 2022.
What PLS can still do for Imaging Genetics in Alzheimer’s disease
Published in IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2022), 2022
Analysis of partial least squares methods for imaging genetics studies in Alzheimer's disease.
Long-term remodelling and arrhythmogenicity after myocardial infarction using a novel image-based estimator: the Scar Maturation Score
Published in Europace, 2022
Novel image-based Scar Maturation Score for assessing long-term cardiac remodelling and arrhythmia risk after myocardial infarction.
Prediction of thrombosis in atrial fibrillation with compact atrial shape representation
Published in Europace, 2022
Compact atrial shape representation for predicting thrombosis risk in atrial fibrillation.
A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations
Published in Journal of Machine Learning for Biomedical Imaging (MELBA), 2022
Differentially private probabilistic model for federated analysis of heterogeneous multi-view biomedical datasets.
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
Published in Journal of Machine Learning Research, 2022
Unified convergence theory for federated optimization accommodating asynchronous and heterogeneous client updates.
A General Theory for Client Sampling in Federated Learning
Published in International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI (FL-IJCAI 2022), 2022
Theoretical framework unifying client sampling strategies in federated learning with convergence guarantees.
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
Published in Neural Information Processing Systems (NeurIPS 2022), Datasets and Benchmarks Track, 2022
FLamby: a benchmark suite of realistic cross-silo federated learning datasets from healthcare domains.
Integration of Multimodal Data
Published in Machine Learning for Brain Disorders (Springer), 2023
Book chapter on methods for multimodal data integration in brain disorder research.
MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling
Published in NeuroImage, 2023
A multi-channel recurrent variational autoencoder for multimodal disease progression modeling in Alzheimer’s disease.
Imaging Genetics
Published in Medical Image Analysis (Elsevier, 2nd ed.), eds. Frangi, Prince, Sonka, 2023
Book chapter on imaging genetics methods, covering multivariate approaches for linking genetic variation to brain imaging phenotypes.
Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models
Published in arXiv preprint arXiv:2304.08054, 2023
Federated missing data imputation using deep generative models, extending MIWAE to the federated setting.
On Tail Decay Rate Estimation of Loss Function Distributions
Published in Journal of Machine Learning Research, 2023
Theoretical study of tail decay rate estimation for loss function distributions in deep learning.
Enhanced Distribution Modelling via Augmented Architectures For Neural ODE Flows
Published in NeurIPS 2023 Workshop on Deep Learning and Differential Equations (DLDE-III), 2023
Augmented neural ODE architectures for improved density estimation in normalizing flows.
Faster Training of Diffusion Models and Improved Density Estimation via Parallel Score Matching
Published in NeurIPS 2023 Workshop on Diffusion Models, 2023
Parallel score matching method for faster training of diffusion models with improved density estimation.
Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation
Published in PharML Workshop at AAAI 2023, 2023
Benchmark study evaluating cost-effectiveness of federated and collaborative learning for prostate segmentation.
Tackling the dimensions in imaging genetics with CLUB-PLS
Published in arXiv preprint arXiv:2309.07352, 2023
CLUB-PLS: a dimensionality reduction approach for high-dimensional imaging genetics analysis.
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
Published in International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2024
SIFU: a sequential federated unlearning method with provable guarantees for efficient client data removal.
A data-driven model of disability progression in progressive multiple sclerosis
Published in Brain Communications, 2024
Data-driven modeling of disability progression trajectories in progressive multiple sclerosis.
Volumetric Study of the Hippocampus in Early-onset Schizophrenia: Correlations with Age of Onset
Published in Current Medical Imaging, 2024
MRI volumetric analysis of the hippocampus in early-onset schizophrenia.
Preictal dysfunctions of inhibitory interneurons paradoxically lead to their rebound hyperactivity
Published in Proceedings of the National Academy of Sciences, 2024
Study of inhibitory interneuron dynamics preceding epileptic seizures.
Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis
Published in Multiple Sclerosis Journal, 2024
Review and application of AI methods for MRI data analysis in multiple sclerosis.
Privacy preserving image registration
Published in Medical Image Analysis, 2024
A method for privacy-preserving medical image registration in federated settings.
Federated Multi-centric Image Segmentation with Uneven Label Distribution
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2024), 2024
Federated learning framework for multi-centric medical image segmentation addressing uneven label distributions across sites.
Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Stragglers
Published in 19th International Conference on Availability, Reliability and Security (ARES 2024), 2024
Scalable federated learning protocol robust to straggler clients through adaptive dropping strategies.
A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures
Published in Computational Statistics, 2024
Bayesian clustering and model selection approach for longitudinal data mixtures with exact finite-sample guarantees.
Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications
Published in 5th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DCL 2024), 2024
Secure aggregation protocol enhancing privacy guarantees in federated learning for healthcare.
A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications
Published in arXiv preprint arXiv:2412.06494, 2024
Empirical analysis of the cost-effectiveness of federated and collaborative AI in real-world medical imaging settings.
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
Published in Federated Learning Systems, 2nd ed. (Springer, Studies in Computational Intelligence, vol. 832), 2025
Fed-BioMed: an open-source federated learning framework designed for real-world healthcare and biomedical applications.
Disease Progression Modeling and Stratification for detecting sub-trajectories in the natural history of pathologies: Application to Alzheimer’s disease trajectory modeling
Published in Imaging Neuroscience, 2025
A disease progression modeling approach for detecting sub-trajectories, applied to Alzheimer’s disease.
When to Forget? Complexity Trade-offs in Machine Unlearning
Published in International Conference on Machine Learning (ICML 2025), 2025
Analysis of computational complexity trade-offs in machine unlearning algorithms.
Scalable Modeling of Nonlinear Network Dynamics in Neurodegenerative Disease
Published in arXiv preprint arXiv:2508.10343, 2025
Scalable framework for modeling nonlinear propagation dynamics across brain networks in neurodegeneration.
A Technical Policy Blueprint for Trustworthy Decentralized AI
Published in arXiv preprint arXiv:2512.11878, 2025
Policy blueprint outlining technical requirements for trustworthy decentralized AI systems.
Fed-ComBat: A Generalized Federated Framework for Batch Effect Harmonization in Collaborative Studies
Published in arXiv (preprint), 2026
A federated framework for batch effect harmonization across collaborative imaging studies.
Variance-Reduced (ε,δ)-Unlearning using Forget Set Gradients
Published in arXiv preprint arXiv:2602.14938, 2026
Variance-reduced machine unlearning algorithm using forget-set gradients with (ε,δ)-privacy guarantees.
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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