Valentina Boeva
Associate Professor
Develops machine learning and computational genomics methods for cancer research, such as analysis of tumour copy-number changes, epigenetic regulation and single-cell transcriptomic data.
Valentina Boeva's lab at ETH Zurich works on genomics & computational biology and medical imaging & healthcare AI. 31 papers since 2023, 1 at top venues, mostly Bioinformatics and Briefings in Bioinformatics. 8 PhD students. 7 alumni.
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 3%
- PhD students
- 8
- MS students
- 0
- alumni listed
- 7
Papers by yearfrom the lab homepage, 2023–2026
- 10 papers2026 · T1 0 · collecting
- 11 papers2025 · T1 0
- 6 papers2024 · T1 0
- 4 papers2023 · T1 1
T1 venuesOtherVenues: Bioinformatics, Briefings in Bioinformatics, Nature Communications, Nucleic Acids Research
Research focuspaper titles that use each topic's words
- Genomics & computational biology5 papers
- single-cell4 papers
- Medical imaging & healthcare AI1 paper
- tumour0 papers
- regulation0 papers
Paper list
From the lab homepage.
202610 papers
- Cancer ResearchCanSig benchmarks methods for reproducible cancer cell state discovery from single-cell transcriptomic data
- Cancer ResearchCDState: an unsupervised approach to predict malignant cell heterogeneity in tumor bulk RNA-sequencing data
- BioinformaticsChiron3D: an interpretable deep learning framework for understanding the DNA code of chromatin looping
- MedFM-BenchDistillPath: An Efficient 22M Distilled Pathology Encoder Approaching Large Foundation Model Performance
- Genome ResearchEarly feature extraction drives model performance in high-resolution chromatin accessibility prediction
- NeurIPS'Link to the paper (opens in a new tab)
- RNA, , rnaRepresentation learning of single-cell RNA-seq data
- Genome ResearchRobust and efficient annotation of cell states through gene signature scoring
- BioinformaticsStriping artifact removal in VisiumHD data through nuclear counts modeling
- Nucleic Acids ResearchUniversalEPI: robust prediction of cell type-specific and differential chromatin interactions from DNA sequence and chromatin accessibility
202511 papers
- Cell Reports MedicineCell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma
- The Proceedings of Machine Learning ResearchExploring Augmentation-Driven Invariances for Graph Self-supervised Learning in Spatial Omics
- BMC CancerExploring RNA cargo in extracellular vesicles for pleural mesothelioma detection
- Genome BiologyFiltering cells with high mitochondrial content depletes viable metabolically altered malignant cell populations in cancer single-cell studies
- Proceedings of NeurIPS'Generalized Linear Mode Connectivity for Transformers
- ICML WorkshopH&Enium, Applying Foundation Models to Computational Pathology and Spatial Transcriptomics to Learn an Aligned Latent Space
- Lab on a ChipHigh-Resolution Time-Lapse Imaging of Droplet-Cell Dynamics via Optimal Transport and Contrastive Learning
- Nature CancerMIRO2-mediated mitochondrial transfer from cancer cells induces cancer-associated fibroblast differentiation
- Cancer CellNew horizons at the interface of artificial intelligence and translational cancer research
- ICML' proceedingsscSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data
- Briefings in BioinformaticsSurvBoard: standardized benchmarking for multi-omics cancer survival models
20246 papers
- Cancer Research CommunicationsA Database Tool Integrating Genomic and Pharmacologic Data from Adrenocortical Carcinoma (ACC) Cell Lines, PDX, and Patient Samples
- Journal of National Cancer InstituteDNA-methylation variability in normal mucosa: a field cancerization marker in patients with adenomatous polyps
- Proceedings of IEEE VISFeature Clock: High-Dimensional Effects in Two-Dimensional Plots
- Proceedings of The IEEE Workshop on Computer Vision for Microscopy Image Analysis (CVMI) of CVPRHistopathological Image Classification with Cell Morphology Aware Deep Neural Networks
- AccMLBioscTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-seq Data
- BioinformaticsSparsesurv: a Python package for fitting sparse survival models via knowledge distillation
20234 papers
- Clinical EpigeneticsDNA hypermethylation driven by DNMT1 and DNMT3A favors tumor immune escape contributing to the aggressiveness of adrenocortical carcinoma
- Nature Communications (T1)Reversible transitions between noradrenergic and mesenchymal tumor identities define cell plasticity in neuroblastoma
- NAR Genomics and BioinformaticsscROSHI: robust supervised hierarchical identification of single cells
- Cell Reports MethodsSystematic comparison of multi-omics survival models reveals a widespread lack of noise resistance
Where alumni went7 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.
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