Daniel C. Alexander
21 papers · 2019–2026 · 8 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (40) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Topic Evolution
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Renaissance Researcher
(5)
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Unstoppable · Bronze
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Prolific Year · Productive
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Conference Pioneer
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Century Club · Bronze
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Top co-authors
Research topics
Machine Learning
(10)
Deep Learning
(9)
Computer Vision
(7)
Artificial Intelligence
(5)
Healthcare & Medicine
(5)
Clinical
(5)
Domain-Specific
(5)
Learning Types · Machine Learning
(5)
Models
(4)
Application Areas
(3)
Architectures
(3)
Core AI
(3)
Learning Types · Deep Learning
(3)
Optimization & Theory
(3)
Core Methods
(2)
Keywords
medical imaging
(2)
large language model
(2)
computed tomography
(2)
alzheimer disease
(2)
variational inference
(2)
diffusion model
(2)
disease progression
(2)
foundation model
(2)
temporal modeling
(1)
causal discovery
(1)
multi-task learning
(1)
model calibration
(1)
optimal transport
(1)
noisy label learning
(1)
semantic segmentation
(1)
feature selection
(1)
flow matching
(1)
image retrieval
(1)
vision transformer
(1)
medical image segmentation
(1)
Papers
A Stage-Aware Mixture of Experts Framework for Neurodegenerative Disease Progression Modelling
AAAI 2026
CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis
AAAI 2026
GenTract: Generative Global Tractography
CVPR 2026
HalluGen: Synthesizing Realistic and Controllable Hallucinations for Evaluating Image Restoration
CVPR 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
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
Advancing Medical Image Segmentation with Self-Supervised Learning: A 3D Student-Teacher Approach for Cardiac and Neurological Imaging
MIDL 2025
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
Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging
ECCV 2024
Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning
ICLR 2024
Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge
MICCAI 2024
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
ICLR 2024
Unscrambling disease progression at scale: fast inference of event permutations with optimal transport
NeurIPS 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
Learning From Noisy Labels by Regularized Estimation of Annotator Confusion
CVPR 2019
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
ICCV 2019