Gunnar Rätsch
Full Professor
Leads the Biomedical Informatics group, developing machine learning methods for clinical time series, electronic health records and cancer genomics.
Gunnar Rätsch's lab at ETH Zurich works on medical imaging & healthcare AI, genomics & computational biology and medical image analysis. 55 papers since 2023, 14 at top venues, mostly Bioinformatics and NeurIPS. 8 PhD students. 40 alumni.
At a glance
- papers, 2023–2026
- 14/ year
- at T1 venues
- 25%
- PhD students
- 8
- MS students
- 0
- alumni listed
- 40
Papers by yearfrom the lab homepage, 2023–2026
- 5 papers2026 · T1 1 · collecting
- 13 papers2025 · T1 2
- 16 papers2024 · T1 2
- 21 papers2023 · T1 9
T1 venuesOtherVenues: Bioinformatics, NeurIPS, ICML, Nature Communications, ICLR
Research focuspaper titles that use each topic's words
- Medical image analysis6 papers
- Medical imaging & healthcare AI4 papers
- Genomics & computational biology3 papers
- electronic health1 paper
- biomedical informatics0 papers
Paper list
From the lab homepage.
20265 papers
- Nature Communications (T1)A tumor profiling resource for ovarian cancer: insights into chemotherapy-driven heterogeneity and personalized treatment strategy (opens in a new tab)
- BioinformaticsAn end-to-end computational framework for “Record- seq” transcriptional recording data (opens in a new tab)
- BioinformaticsStriping artifact removal in VisiumHD data through nuclear counts modeling (opens in a new tab)
- ICLR LMRLTowards Cross-Sample Alignment for Multi-Modal Representation Learning in Spatial Transcriptomics (opens in a new tab)
- ICML Multi-modal Foundation Models and Large Language Models for Life SciencesTranscriptomics-Conditioned Virtual Tissue Synthesis via Diffusion Transformers (opens in a new tab)
202513 papers
- Molecular PharmaceuticsA Semimechanistic Ocular Pharmacokinetic Model for ADVM-022 Gene Therapy Describing the Dose-Exposure Relationship in Monkeys and the Scaling to Human (opens in a new tab)
- WABI24A*PA2: Up to 19× Faster Exact Global Alignment (opens in a new tab)
- PMLRData-Driven Discovery of Feature Groups in Clinical Time Series (opens in a new tab)
- NeurIPS ImageomicsDeepSpot2Cell: Predicting Virtual Single-Cell Spatial Transcriptomics from H&E images using Spot-Level Supervision (opens in a new tab)
- Nature (T1)Efficient and accurate search in petabase-scale sequence repositories (opens in a new tab)
- The IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)Generalizable Single-Source Cross-Modality Medical Image Segmentation via Invariant Causal Mechanisms (opens in a new tab)
- Nature Machine Intelligence (T1)Histopathology-based protein multiplex generation using deep learning (opens in a new tab)
- BioinformaticsImmunoPepper: extracting personalized peptides from complex splicing graphs (opens in a new tab)
- The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)MIXPINN: Mixed-Material Simulations by Physics-Informed Neural Network (opens in a new tab)
- ICML FM4LSMolecularly informed analysis of histopathology images using natural language (opens in a new tab)
- NeurIPS AI4D3Perturbation-aware representation learning for in vivo genetic screens (opens in a new tab)
- Medical Image Computing and Computer Assisted Intervention (MICCAI)Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology (opens in a new tab)
202416 papers
- BioinformaticsAn empirical study on KDIGO-defined acute kidney injury prediction in the intensive care unit (opens in a new tab)
- Circulation: Cardiovascular Quality and OutcomesDefining a Minimal Benchmark for Cardiovascular Risk Prediction Calculators in New England Electronic Health Record–Derived Cohort (opens in a new tab)
- ICLR (T1)Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding (opens in a new tab)
- CHILDynamic Survival Analysis for Early Event Prediction (opens in a new tab)
- BioinformaticsExact global alignment using A* with chaining seed heuristic and match pruning (opens in a new tab)
- Proceedings of Machine Learning ResearchFAMEWS: a Fairness Auditing tool for Medical Early-Warning Systems (opens in a new tab)
- Journal of Bone and Mineral ResearchFracture risk prediction in postmenopausal women with traditional and machine learning models in a nationwide, prospective cohort study in Switzerland with validation in the UK Biobank (opens in a new tab)
- BioinformaticsLabel-guided seed-chain-extend alignment on annotated De Bruijn graphs (opens in a new tab)
- ISCA (T1)MegIS: High-Performance, Energy-Efficient, and Low-Cost Metagenomic Analysis with In-Storage Processing (opens in a new tab)
- TS4H ICLR WorkshopMulti-Modal Contrastive Learning for Online Clinical Time-Series Applications (opens in a new tab)
- Nature MedicinePrediction of recurrence risk in endometrial cancer with multimodal deep learning (opens in a new tab)
- PMLRSystematic Evaluation of Self-Supervised Learning Approaches for Wearable-Based Fatigue Recognition (opens in a new tab)
202321 papers
- Genome ResearchAligning distant sequences to graphs using long seed sketches (opens in a new tab)
- Nature Communications (T1)Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer (opens in a new tab)
- NeurIPS (T1)Effective Bayesian Heteroscedastic Regression with Deep Neural Networks (opens in a new tab)
- Medical Image Analysis (T1)Generative appearance replay for continual unsupervised domain adaptation (opens in a new tab)
- ML4HKnowledge Graph Representations to enhance Intensive Care Time-Series Predictions (opens in a new tab)
- NeurIPS (T1)Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures (opens in a new tab)
- NeurIPS WorkshopLanguage Model Training Paradigms for Clinical Feature Embeddings (opens in a new tab)
- AABILaplace-Approximated Neural Additive Models: Improving Interpretability with Bayesian Inference (opens in a new tab)
- NeurIPS WorkshopLearning Genomic Sequence Representations using Graph Neural Networks over De Bruijn Graphs (opens in a new tab)
- NeurIPS (T1)Learning Layer-wise Equivariances Automatically using Gradients (opens in a new tab)
- Cell Host and MicrobeMicrobial medics diagnose and treat gut inflammation (opens in a new tab)
- PMLRMulti-modal Graph Learning over UMLS Knowledge Graphs (opens in a new tab)
Where alumni went40 listed
Apply to ETH ZurichRolling
Not announced yet
Computer Science Doctorate (D-INFK)
- Round
- Rolling (no deadline)
- Opens
- —
- GRE
- See program page
- English
- Proficiency in written and spoken English
- Fee
- See program page
Confirmed on the program page.
Similar labsnearest by research summary
- CNTsinghua
Xuegong Zhang
- Genomics & computational biology
- CNPeking
Hanpin Wang
- Proteins, drugs & materials
- USUCLA
Sriram Sankararaman
- Genomics & computational biology
- GBUCL
Maneesh Sahani
- Probabilistic & causal inference
- CAToronto
Chris McIntosh
- Medical imaging & healthcare AI
- CHETH Zurich
Benjamin Grewe
- Computational neuroscience & cognition
Your notes
Save this lab to keep notes.
Data
Checked against the lab homepage.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.