Daniel C. Alexander
19 papers · 2019–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (7) π Cross-Pollinator (14)
π
Interdisciplinary Bridge
π§
Keyword Pioneer
π
Conference Polyglot
(7)
π
Conference Pioneer
β‘
Prolific Year
(5)
π₯
Unstoppable
(5)
π
Century Club
(13)
Conferences
MIDL (6)
ICLR (4)
MICCAI (3)
AAAI (2)
CVPR (1)
ECCV (1)
ICCV (1)
NIPS (1)
Top co-authors
Keywords
variational inference
(2)
foundation model
(2)
disease progression
(2)
medical imaging
(2)
computed tomography
(2)
image retrieval
(1)
image translation
(1)
vision transformer
(1)
self-supervised learning
(1)
noisy label learning
(1)
temporal modeling
(1)
optimal transport
(1)
medical image segmentation
(1)
model interpretability
(1)
alzheimer disease
(1)
model calibration
(1)
diffusion model
(1)
neural ordinary differential equation
(1)
multi-task learning
(1)
contrastive learning
(1)
Papers
CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis
AAAI 2026
Scalable Detection of Undiagnosed ILD in Population Screening: A Multi-Cohort Study using 3D Foundation Models
MIDL 2026
What Fine-Tuning Changes: A Radiomic Lens on Prostate Foundation Model Representations
MIDL 2026
A Stage-Aware Mixture of Experts Framework for Neurodegenerative Disease Progression Modelling
AAAI 2026
Analysis of Image-and-Text Uncertainty Propagation in Multimodal Large Language Models with Cardiac MR-Based Applications
MICCAI 2025
Balancing Act: Diversity and Consistency in Large Language Model Ensembles
ICLR 2025
Tackling Hallucination from Conditional Models for Medical Image Reconstruction with DynamicDPS
MICCAI 2025
Advancing Medical Image Segmentation with Self-Supervised Learning: A 3D Student-Teacher Approach for Cardiac and Neurological Imaging
MIDL 2025
4D-VQ-GAN: A World Model for Synthesizing Medical Scans at Any Time Point for Personalized Disease Progression Modeling of Idiopathic Pulmonary Fibrosis
MIDL 2025
Unscrambling disease progression at scale: fast inference of event permutations with optimal transport
NIPS 2024
Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning
ICLR 2024
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
ICLR 2024
Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging
ECCV 2024
Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge
MICCAI 2024
DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification
MIDL 2023
Learning Morphological Feature Perturbations for Calibrated Semi-Supervised Segmentation
MIDL 2022
Learning to Downsample for Segmentation of Ultra-High Resolution Images
ICLR 2022
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
ICCV 2019
Learning From Noisy Labels by Regularized Estimation of Annotator Confusion
CVPR 2019