Julia Vogt
Associate Professor
Leads the Medical Data Science group, developing interpretable and multimodal machine learning methods for clinical data and medical imaging.
Julia Vogt's lab at ETH Zurich works on medical imaging & healthcare AI, trustworthy & safe ML and vision-language & multimodal. 107 papers since 2023, 16 at top venues, mostly TMLR and ICLR. 4 PhD students. 4 alumni, most often to Apple.
At a glance
- papers, 2023–2026
- 28/ year
- at T1 venues
- 15%
- PhD students
- 4
- MS students
- 0
- alumni listed
- 4
Papers by yearfrom the lab homepage, 2023–2026
- 16 papers2026 · T1 4 · collecting
- 24 papers2025 · T1 2
- 25 papers2024 · T1 3
- 42 papers2023 · T1 7
T1 venuesOtherVenues: TMLR, ICLR, CHI, NeurIPS, EMNLP
Research focuspaper titles that use each topic's words
- Vision-language & multimodal11 papers
- Trustworthy & safe ML3 papers
- Medical imaging & healthcare AI2 papers
- medical2 papers
- medical data1 paper
Paper list
From the lab homepage.
202616 papers
- IEEE Journal of Biomedical and Health InformaticsAntithetic Sampling Enhanced Probabilistic Diffusion for Denoising Cardiac Time Series (opens in a new tab)
- SoftwareXEGM analyzer: A modular software platform for visualization and analysis of cardiac electrograms (opens in a new tab)
- MIDLEnhancing Radiology Report Generation and Visual Grounding using Reinforcement Learning (opens in a new tab)
- MIDLGeometry-Aware Cardiac MRI Representation Learning with Equivariant Neural Fields (opens in a new tab)
- Circulation: Arrhythmia and ElectrophysiologyImpact of Catheter Configuration on the Mapping of Atrial Fibrillation (opens in a new tab)
- IEEE Journal of Translational Engineering in Health and MedicineMultimodal Patient-Specific Identification of Atrial Flutter Circuits From ECG Time Series Using Explainable Machine Learning (opens in a new tab)
- International Conference on Learning Representations (ICLR) Workshop on Trustworthy AIPost-hoc Stochastic Concept Bottleneck Models (opens in a new tab)
- Expert Systems with ApplicationsReducing Diverse Sources of Noise in Ventricular Electrical Signals Using Variational Autoencoders (opens in a new tab)
- International Conference on Learning Representations (ICLR) Workshop on Agents in the WildReference-Guided Machine Unlearning (opens in a new tab)
- Oral at ICLR Workshop TTURethinking Machine Unlearning: Models Designed to Forget via Key Deletion (opens in a new tab)
- CHI (T1)Steering Generative Models for Accessibility: EasyRead Image Generation (opens in a new tab)
- TMLR (T1)Structure is Supervision: Multiview Masked Autoencoders for Radiology (opens in a new tab)
202524 papers
- Pediatric ResearchAutomated detection of neonatal pulmonary hypertension in echocardiograms with a deep learning model (opens in a new tab)
- International Conference on Learning Representations (ICLR) Workshop AI4CHLBeyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes (opens in a new tab)
- Circulation: Arrhythmia and ElectrophysiologyComparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning (opens in a new tab)
- Frontiers in Cardiovascular MedicineECG-XPLAIM: eXPlainable Locally-adaptive Artificial Intelligence Model for arrhythmia detection from large-scale electrocardiogram data (opens in a new tab)
- Heart RhythmEndo-Epicardial Electrical Disarray in Arrhythmogenic Cardiomyopathy with Ventricular Arrhythmias (opens in a new tab)
- Circulation: Arrhythmia and ElectrophysiologyEngineering of Generative Artificial Intelligence and Natural Language Processing Models to Accurately Identify Arrhythmia Recurrence (opens in a new tab)
- —From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection (opens in a new tab)
- BiomedicinesHearts, Data, and Artificial Intelligence Wizardry: From Imitation to Innovation in Cardiovascular Care (opens in a new tab)
- International Conference on Machine Learning (ICML) Workshop on PRALInterpretable Reward Modeling with Active Concept Bottlenecks (opens in a new tab)
- International Conference of Machine Learning (ICML) Workshop on FM4LSLeveraging the Structure of Medical Data for Improved Representation Learning (opens in a new tab)
- Frontiers in ImmunologyMathematical models and computational approaches in CAR-T therapeutics (opens in a new tab)
- International Conference on Learning Representations (ICLR) Workshop: XAI4ScienceMeasuring Leakage In Concept-Based Methods: An Information Theoretic Approach (opens in a new tab)
202425 papers
- ICLR - Workshop on Time Series for HealthcareA denoising VAE for intracardiac time series in ischemic cardiomyopathy (opens in a new tab)
- TMLR (T1)A Probabilistic Model behind Self-Supervised Learning (opens in a new tab)
- Findings Machine Learning for Health (ML4H) Symposium colocated with NeurIPSAutomatic Classification of General Movements in Newborns (opens in a new tab)
- FAccTBenchmarking the fairness of image upsampling methods (opens in a new tab)
- EMBCCan Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy (opens in a new tab)
- The Fifteenth International Conference on Learning Representations, ICLRCross-Entropy Is All You Need To Invert the Data Generating Process (opens in a new tab)
- ICLR: The Twelfth International Conference on Learning RepresentationsDeep generative clustering with multimodal diffusion variational autoencoders (opens in a new tab)
- IJCV (T1)Deep Learning Based Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms (opens in a new tab)
- NeurIPS WorkshopDIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features (opens in a new tab)
- Lancet eBiomedicineDynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillator (opens in a new tab)
- EMBCEEG Tensorization Enhances CNN-Based Outcome Classification in Comatose Patients Following a Cardiac Arrest (opens in a new tab)
- ACM Celebration of Women in Computing: womENcourageEstimating Patent Ductus Arteriosus from Pulse Wave Transition Time in Newborn Infants (opens in a new tab)
202342 papers
- ICML Workshop(Un)reasonable Allure of Ante-hoc Interpretability for High-stakes Domains: Transparency Is Necessary but Insufficient for Comprehensibility (opens in a new tab)
- CinC3D CNN as an Approach to Predict the Cerebral Performance of Comatose Patients (opens in a new tab)
- Conference on Causal Learning and Reasoning (Datasets Track), CLeaR3DIdentBox: A Toolbox for Identifiability Benchmarking (opens in a new tab)
- EMBCAssessment of the Interelectrode Distance Effect over the Omnipole with High Multielectrode Arrays (opens in a new tab)
- XAI in Action: Past, Present, and Future Applications, NeurIPSBeyond Concept Bottleneck Models: How to Make Black Boxes Intervenable? (opens in a new tab)
- Frontiers in PediatricsBlood glucose forecasting from temporal and static information in children with T1D (opens in a new tab)
- ICMIBreathing New Life into COPD Assessment: Multisensory Home-monitoring for Predicting Severity (opens in a new tab)
- ICML WorkshopDeep Generative Clustering with Multimodal Variational Autoencoders (opens in a new tab)
- CinCDefining the Predictive Ceiling of Electrogram Features Alone for Predicting Outcomes From Atrial Fibrillation Ablation (opens in a new tab)
- NeurIPS (T1)Differentiable Random Partition Models (opens in a new tab)
- Physical and Engineering Sciences in MedicineEvaluation and assessment of clique arrangements for the estimation of omnipolar electrograms in high density electrode arrays: an experimental animal model study (opens in a new tab)
- NeurIPS (T1)ExpLIMEable: An exploratory framework for LIME (opens in a new tab)
Where alumni went4 listed, 100% to industry
Industry 4Academia 0
Most often to
- Apple
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