Researchers
| Name | Position | Topic | Project | Collab. | Funding | Year (start) |
|---|---|---|---|---|---|---|
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Head | 2017 | ||||
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PhD | ML paradigms, selection bias prediction of candidate targets for anticancer therapy |
ONCOTARGETS | INSY/TU Delft | 2020 | |
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PhD | representation learning mechanisms of proton-induced DNA damage response |
PROTON-DDR | LUMC, Erasmus MC (Tijsterman, Kanaar, Reinders) | HollandPTC | 2020 |
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PhD | multimodal ML for molecular atlases spatial omics deconvolution |
BIOMIC | Vanderbilt U. (Spraggins) | NIH/NIDDK HuBMAP | 2022 |
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Postdoc | multimodal ML for molecular atlases multiomics integration |
BIOMIC | Vanderbilt U. (Spraggins) | NIH/NEI HuBMAP | 2022 |
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PhD | multimodal ML for molecular atlases | BIOMIC | Vanderbilt U. (Spraggins) | NIH/NIDDK KPMP + NIH/NIA | 2023 |
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PhD | individualized models of disease diversity | iCELL | Erasmus MC (van Meurs), Erasmus U. (Redekop) | Convergence Flagship | 2023 |
Thesis Students
| Name | Programme | Topic | Year (start) |
|---|---|---|---|
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MSc Computer Science / Data Science and AI Tech | ? | 2025 |
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MSc Computer Science | ? | 2025 |
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MSc Computer Science | Selection bias mitigation | 2025 |
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MSc Computer Science | Integrated transcriptional and mutational signature learning for cancer patient survival prediction | 2022 |
Research Students (Non-Thesis)
| Name | Programme | Topic | Year (start) |
|---|---|---|---|
|
|
Computer Science (TU Delft) | 2025 |
Former Lab Researchers
| Name | Position | Topic | Project | Collab. | Funding | Year |
|---|---|---|---|---|---|---|
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Postdoc | [computational] modelling of single-cell response to proton therapy | PROTON-SC | Erasmus MC (Chien) | Convergence Impulse | 2020-2022 |
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Postdoc | [experimental] modelling of single-cell response to proton therapy | PROTON-SC | Erasmus MC (Chien) | Convergence Impulse | 2020-2022 |
Alumni (MSc thesis students)
| Name | Programme | Topic | Year | Career |
|---|---|---|---|---|
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MSc Data Science and Engineering (Pol. Torino) [thesis] | Representation learning of cancer genomes | 2023-2024 | Whitehall Reply |
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MSc Computer Science [thesis] | Semi-supervised NMF for learning of mutational signatures and prediction of DNA repair deficiencies | 2023-2024 | Mollie |
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MSc Computer Science [thesis] | Representations of DNA sequence context and mutational spectra for prediction of repair deficiencies | 2022-2023 | Enza Zaden |
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MSc Computer Science [thesis] | Exploring intronic RNA-seq read counts for phenotype prediction | 2022-2023 | MrWork |
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MSc Computer Science [thesis] | Mitigating selection bias in synthetic lethality prediction using metric learning | 2022-2023 | DSW Zorgverzekeraar |
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MSc Computer Science [thesis] | Attention-based deep learning for DNA repair outcome prediction | 2021-2022 | Codo (own company) |
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MSc Computer Science (cum laude) + Nanobiology [preprint] | Integrated learning of mutational signatures and prediction of DNA repair deficiency | 2021-2022 | PhD (our lab, TU Delft) |
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MSc Nanobiology | Explaining CRISPR/Cas9 DNA damage repair outcome prediction models | 2021-2022 | PhD (QMUL, UK) |
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MSc Computer Science [thesis] | mutational signatures of CRISPR repair outcomes | 2020-2021 | Associate Tech/AI (PwC) |
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MSc Computer Science [thesis] | interpretable or explainable time-to-event prediction | 2020-2021 | AI Engineer (Vodafone/Ziggo) |
|
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MSc Computer Science (cum laude) [journal paper] | prediction of synthetic lethality in cancer: integration, generalisation, bias | 2019-2020 | PhD (our lab, TU Delft) |
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MSc Computer Science [thesis] | prediction of DNA repair pathways from DNA scars | 2019-2020 | Data Engineer (LUMC) |
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MSc Computer Science (cum laude) [thesis] | multitask learning of gene essentiality in cancer cell lines | 2018-2019 | PhD (Erasmus MC) |
Alumni (BSc thesis students, shorter MSc internships)
| Name | Programme | Topic | Year | Career |
|---|---|---|---|---|
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BSc Computer Science (cum laude) | Attention-based models for prediction of CRISPR repair outcomes | 2023-2024 | MSc Comp. Bio. and Bioinformatics (ETH Zurich) |
|
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BSc Computer Science (cum laude) | Selection bias mitigation: importance weighting adaptation to a global underlying domain | 2022-2023 | MSc Computer Science (TUD) |
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BSc Computer Science (cum laude) | Selection bias mitigation: deep domain adaptation without a specific target domain | 2022-2023 | |
|
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BSc Computer Science | Selection bias mitigation: semi-supervised learning techniques | 2022-2023 | MSc Computer Science (TUD) |
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BSc Computer Science | Selection bias mitigation: subspace mapping to unlabeled population samples | 2022-2023 | |
|
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BSc Computer Science | Selection bias mitigation: minimax estimation methods | 2022-2023 | |
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MSc intern Nanobiology | inference of regulation from variation in single-cell gene expression | 2018-2019 | Bioinformatician (OSbiome) |
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BSc Nanobiology | computational reconstruction of cell lineages based on CRISPR recorders | 2019-2021 | MSc Nanobiology (TU Delft) |
|
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BSc Nanobiology | single-cell gene expression prediction in pooled CRISPR screens | 2018-2019 | MSc Computer Science (TU Delft) |
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BSc Life Science and Technology | prediction of gene essentiality in cancer cell lines | 2017-2018 | PhD (Robert Koch Institute) |
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BSc Nanobiology | analysis of DNA end structures generated by CRISPR-Cas9 | 2017-2018 | MSc Nanobiology (TU Delft) |