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-Publications could not be loaded from Google Scholar API. - - View publications directly on Google Scholar →
- `; - } -} - -// Initialize when DOM is ready -document.addEventListener('DOMContentLoaded', () => { - const loader = new PublicationsLoader(); - loader.init(); -}); \ No newline at end of file diff --git a/index.md b/index.md index da446fd..d81c52f 100644 --- a/index.md +++ b/index.md @@ -4,106 +4,108 @@ layout: default --- London, UK • [linkedin.com/in/ctr26](https://linkedin.com/in/ctr26) • [github.com/ctr26](https://github.com/ctr26) • [Google Scholar](https://scholar.google.com/citations?user=XVt7BYQAAAAJ&hl=en) -*Focus:* Virtual cells, multi‑modal foundation models, omics + imaging, precision medicine +*Focus:* Virtual cells, multi-modal foundation models, omics + imaging, precision medicine ## Professional Summary -Machine Learning Scientist specialising in **virtual cell** development for drug discovery. Built and deployed **multi‑modal foundation models** that integrate knowledge graphs, text, transcriptomic and phenotypic imaging data. Experience spans molecular interactions to whole‑organism imaging. Comfortable leading across science and engineering—MLOps at TB‑scale, reproducible pipelines, and cross‑functional collaboration with biology, chemistry and platform teams. +Machine Learning Scientist building **virtual cells** for drug discovery. Builds and deploys **multi-modal foundation models** that fuse knowledge graphs, text, transcriptomics and phenotypic imaging, with experience spanning molecular interactions to whole-organism imaging. Leads across science and engineering: TB-scale MLOps, reproducible pipelines, and cross-functional collaboration with biology, chemistry and platform teams. ## Core Strengths -Foundation models • Representation/self‑supervised learning • Multi‑modal fusion • Knowledge graphs • Biological sequence & transcriptomics • High‑content imaging • GNNs • OOD/robustness • Scaling & performance • Reproducible ML (MLOps) • Scientific communication +Foundation models • Representation/self-supervised learning • Multi-modal fusion • Knowledge graphs • Biological sequence & transcriptomics • High-content imaging • GNNs • OOD/robustness • Scaling & performance • Reproducible ML (MLOps) • Scientific communication ## Experience **Senior Machine Learning Scientist — Valence Labs @ Recursion Pharmaceuticals** London, UK • Oct 2024 – Present -- **Virtual Cell initiative:** Fine‑tune multi‑modal LLMs over **knowledge graphs + text + RNA‑seq + phenotypic imaging** to model cell state and predict gene/drug responses; partnered closely with biology to design benchmark tasks and success metrics. -- **TxPert:** Co‑developed a **state‑of‑the‑art transcriptomic perturbation predictor** using systems‑biology KGs; contributed training code, data curation, and ablations. -- **Boltz2 project:** Contributed to proteome‑scale **virtual drug screening** components; supported evaluation strategy and error analysis across targets. -- **Community:** Organiser, **Virtual Cell Journal Club**; fostered reading group bridging ML and wet‑lab teams. +- **Virtual Cell initiative:** Fine-tuned multi-modal LLMs over knowledge graphs, text, RNA-seq and phenotypic imaging to model cell state and predict gene and drug responses; designed benchmark tasks and success metrics with biology partners. +- **TxPert:** Co-developed a state-of-the-art transcriptomic perturbation predictor built on systems-biology knowledge graphs; contributed training code, data curation and ablations. +- **Boltz-2:** Contributed proteome-scale virtual drug screening components; supported evaluation strategy and error analysis across targets. +- **Community:** Organised the Virtual Cell Journal Club, a reading group bridging ML and wet-lab teams. -**Senior Research Associate & AI Engineering Lead — EMBL‑EBI (Uhlmann Group & Bio‑Image Archive)** +**Senior Research Associate & AI Engineering Lead — EMBL-EBI (Uhlmann Group & BioImage Archive)** Cambridge, UK • Dec 2022 – Oct 2024 -- **Team leadership:** Supervised **6 PhD students**; established coding standards, CI, and peer‑review practices used across the lab. -- **Spatial biology:** Built deep‑learning pipelines for **high‑content cell morphology** and single‑cell feature learning; integrated with public bioimage resources. -- **Open‑source:** Created **[bioimage_embed](https://github.com/uhlmanngroup/bioimage_embed)** (self‑supervised biological images) and **[shape_embed](https://arxiv.org/abs/2507.01009)** (cell‑shape DL toolkit); productionised training/inference. -- **MLOps:** Designed scalable pipelines processing **TB‑scale microscopy datasets** across HPC and cloud; containerised workflows, automated experiment tracking. -- **Academic service:** Reviewer — ISBI 2022/2023, **ICASSP** 2024. +- **Team leadership:** Supervised 6 PhD students; set coding standards, CI and peer-review practices adopted across the lab. +- **Spatial biology:** Built deep-learning pipelines for high-content cell morphology and single-cell feature learning, integrated with public bioimage resources. +- **Open source:** Created [bioimage_embed](https://github.com/uhlmanngroup/bioimage_embed) (self-supervised learning for biological images) and co-developed [ShapeEmbed](https://arxiv.org/abs/2507.01009) (self-supervised 2D shape analysis, with the Uhlmann group); productionised training and inference. +- **MLOps:** Designed pipelines processing TB-scale microscopy datasets across HPC and cloud; containerised workflows and automated experiment tracking. +- **Academic service:** Reviewer for ISBI 2022/2023 and ICASSP 2024. **AI/ML Founding Engineer — Amun AI AB** Stockholm, Sweden • 2022 – 2024 -- Built **GKE/Kubernetes** platform for model serving with **NVIDIA Triton/KServe**; supported **100+ models** for **30+ daily users** with auth, monitoring and autoscaling. +- Built a GKE/Kubernetes model-serving platform on **NVIDIA Triton** and **KServe**: 100+ models, 30+ daily users, with auth, monitoring and autoscaling. **AI/ML Engineering Consultant — DeepMirror** Cambridge & London, UK • 2022 – 2024 -- **MouseMindMapper:** Automated brain‑histology segmentation product generating **£50k annual revenue**; delivered end‑to‑end data, training, packaging and docs. -- Wrote a high‑performance **C++ cheminformatics fingerprinting** library for production use. +- **MouseMindMapper:** Delivered an automated brain-histology segmentation product end to end (data, training, packaging, docs), generating **£50k annual revenue**. +- Wrote a high-performance **C++ cheminformatics fingerprinting** library for production use. -**Data Scientist — Brazma Group, EMBL‑EBI** +**Data Scientist — Brazma Group, EMBL-EBI** Cambridge, UK • Dec 2019 – Dec 2023 -- Co‑authored the successful **AI4LIFE €5M** grant (federated bioimage AI infrastructure); contributed to platform architecture and model‑sharing strategy. -- Drove **large‑scale AI microscopy** analyses in the Image Data Resource; collaborated with **Google Cloud** on representation learning. -- Taught annual deep‑learning courses to **40+ researchers** (PhD to PI). +- Co-authored the successful **AI4LIFE €5M** grant for federated bioimage AI infrastructure; shaped platform architecture and model-sharing strategy. +- Led large-scale AI microscopy analyses in the Image Data Resource; collaborated with **Google Cloud** on representation learning. +- Taught annual deep-learning courses to **40+ researchers**, from PhD students to PIs. -**Software Engineer (COVID‑19 Response) — European Nucleotide Archive, EMBL‑EBI** +**Software Engineer (COVID-19 Response) — European Nucleotide Archive, EMBL-EBI** Cambridge, UK • Mar 2020 – Sept 2020 -- Built CI/CD for the **COVID‑19 Data Portal** to enable **daily global data updates**. +- Built CI/CD for the **COVID-19 Data Portal**, enabling **daily global data updates**. - Scaled NGS alignment and **Nextflow/Kubernetes** ETL pipelines for surging data volumes. **Computational Microscopist — National Physical Laboratory** London, UK • 2018 – Dec 2019 -- Developed novel **3D organoid segmentation** methods for cancer research; delivered consultancy to MSquared on advanced imaging. +- Developed **3D organoid segmentation** methods for cancer research; consulted for MSquared on advanced imaging. ## Education -**PhD, Engineering — University of Cambridge** • 2014 – 2018 (EPSRC PES‑CDT) -*Thesis:* “Light‑sheet microscopy for tracking particles in large specimens” -- Designed & built a novel light‑sheet microscope with automated acquisition. -- Algorithms for particle tracking, signal optimisation, and micrometre‑scale tomography. -- Supervision: 2× MRes, 1× BSc. +**PhD, Engineering — University of Cambridge** • 2014 – 2018 (EPSRC PES-CDT) +*Thesis:* "Light-sheet microscopy for tracking particles in large specimens" +- Designed and built a light-sheet microscope with automated acquisition. +- Developed algorithms for particle tracking, signal optimisation and micrometre-scale tomography. +- Supervised 2 MRes and 1 BSc students. **MRes, Photonics — University of Cambridge & UCL** • 2013 – 2014 (EPSRC Photonics CDT) -- Structured‑illumination microscopy reconstruction; modules in Computer Vision, Quantum Mechanics, Photonics. +- Structured-illumination microscopy reconstruction; modules in Computer Vision, Quantum Mechanics and Photonics. -**MSci, Physics (First‑Class Honours) — Nottingham Trent University** • 2009 – 2013 +**MSci, Physics (First-Class Honours) — Nottingham Trent University** • 2009 – 2013 - Top physics graduate; President, Mountaineering Club (2011–2012). ## Selected Publications & Preprints -1. **Wenkel F**, Tu W, Masschelein C, Shirzad H, Eastwood C, Whitfield ST, Bendidi I, **Russell CT**, et al. *TxPert: Leveraging Biochemical Relationships for Out‑of‑Distribution Transcriptomic Perturbation Prediction.* arXiv:2505.14919 (2025) +1. Wenkel F, Tu W, Masschelein C, Shirzad H, Eastwood C, Whitfield ST, Bendidi I, **Russell C**, et al. *TxPert: Leveraging Biochemical Relationships for Out-of-Distribution Transcriptomic Perturbation Prediction.* [arXiv:2505.14919](https://arxiv.org/abs/2505.14919) (2025) -2. Harrison PW, Lopez R, Rahman N, Allen SG, Aslam R, Buso N, **Russell CT**, et al. *The COVID‑19 Data Portal: accelerating SARS‑CoV‑2 and COVID‑19 research through rapid open access data sharing.* Nucleic Acids Research 49(W1):W619–W623 (2021) +2. Foix Romero A, **Russell C**, Krull A, Uhlmann V. *ShapeEmbed: a self-supervised learning framework for 2D contour quantification.* [arXiv:2507.01009](https://arxiv.org/abs/2507.01009) (2025) -3. Ouyang W, Beuttenmueller F, Gómez‑de‑Mariscal E, Pape C, Burke T, Garcia‑López‑de Haro C, **Russell C**, et al. *Bioimage model zoo: a community‑driven resource for accessible deep learning in bioimage analysis.* BioRxiv 2022.06.07.495102 (2022) +3. Hidalgo-Cenalmor I, Pylvänäinen JW, Ferreira MG, **Russell CT**, et al. *DL4MicEverywhere: deep learning for microscopy made flexible, shareable and reproducible.* [Nature Methods 21(6):925–927](https://doi.org/10.1038/s41592-024-02295-6) (2024) -4. Ahlers J, Moré DA, Amsalem O, Anderson A, Bokota G, Boone P, **Russell C**, et al. *napari: a multi‑dimensional image viewer for Python.* Zenodo 1–2 (2023) +4. Ahlers J, Moré DA, Amsalem O, Anderson A, Bokota G, Boone P, **Russell C**, et al. *napari: a multi-dimensional image viewer for Python.* Zenodo (2023) -5. Hidalgo‑Cenalmor I, Pylvänäinen JW, Ferreira MG, **Russell CT**, et al. *DL4MicEverywhere: deep learning for microscopy made flexible, shareable and reproducible.* Nature Methods 21(6):925–927 (2024) +5. Ouyang W, Beuttenmueller F, Gómez-de-Mariscal E, Pape C, Burke T, Garcia-López-de Haro C, **Russell C**, et al. *BioImage Model Zoo: a community-driven resource for accessible deep learning in bioimage analysis.* [bioRxiv 2022.06.07.495102](https://doi.org/10.1101/2022.06.07.495102) (2022) -See **Google Scholar** for complete publication list: [scholar.google.com/citations?user=XVt7BYQAAAAJ](https://scholar.google.com/citations?user=XVt7BYQAAAAJ&hl=en) +6. Harrison PW, Lopez R, Rahman N, Allen SG, Aslam R, Buso N, **Russell CT**, et al. *The COVID-19 Data Portal: accelerating SARS-CoV-2 and COVID-19 research through rapid open access data sharing.* [Nucleic Acids Research 49(W1):W619–W623](https://doi.org/10.1093/nar/gkab417) (2021) + +Full list on [Google Scholar](https://scholar.google.com/citations?user=XVt7BYQAAAAJ&hl=en). ## Patents -- **Virtual Cell Foundation Model** • Patent pending • 2024 • Multi‑modal integration of knowledge graphs, transcriptomics and imaging for cellular state prediction (Hook1/Recursion) -- **TxPert: Transcriptomic Perturbation Prediction** • Patent pending • 2024 • Systems‑biology knowledge graph integration for gene expression response forecasting (Recursion) +- **Virtual Cell Foundation Model** • Patent pending • 2024 • Multi-modal integration of knowledge graphs, transcriptomics and imaging for cellular state prediction (Hook1/Recursion) +- **TxPert: Transcriptomic Perturbation Prediction** • Patent pending • 2024 • Systems-biology knowledge graph integration for gene expression response forecasting (Recursion) ## Open Source (Selected) -- **[bioimage_embed](https://github.com/uhlmanngroup/bioimage_embed)** — Self‑supervised learning for biological images. -- **[shape_embed](https://arxiv.org/abs/2507.01009)** — Deep‑learning toolkit for cell‑shape analysis. +- **[bioimage_embed](https://github.com/uhlmanngroup/bioimage_embed)** — Self-supervised learning for biological images. +- **[ShapeEmbed](https://arxiv.org/abs/2507.01009)** — Self-supervised representation learning for 2D shape analysis (Uhlmann group). - Contributions to **Hypha Platform**, **BioImage Model Zoo**, **BIA Binder**, **Hypha Helm Charts**, **COVID Workflow Manager**. ## Skills -**ML & AI:** Foundation‑model fine‑tuning, contrastive/self‑supervised learning, OOD & uncertainty, evaluation/ablation design -**Frameworks:** PyTorch, TensorFlow, Lightning, Pyro, Hugging Face, scikit‑learn -**Vision & Bio:** Bioimage analysis, 3D reconstruction, segmentation/super‑resolution, **snRNA‑seq/bulk RNA‑seq**, histopathology, fluorescence imaging, **GNNs**, knowledge graphs +**ML & AI:** Foundation-model fine-tuning, contrastive/self-supervised learning, OOD & uncertainty, evaluation/ablation design +**Frameworks:** PyTorch, TensorFlow, Lightning, Pyro, Hugging Face, scikit-learn +**Vision & Bio:** Bioimage analysis, 3D reconstruction, segmentation/super-resolution, **snRNA-seq/bulk RNA-seq**, histopathology, fluorescence imaging, **GNNs**, knowledge graphs **Languages:** Python (primary), R, MATLAB, C++, Java -**Compute:** Multi‑GPU training (A100/V100), CUDA, distributed training, SLURM, HPC, GCP/AWS GPU instances +**Compute:** Multi-GPU training (A100/V100), CUDA, distributed training, SLURM, HPC, GCP/AWS GPU instances **MLOps/Infra:** Kubernetes, Docker, **NVIDIA Triton**, **KServe**, MLflow, CI/CD, Terraform **Workflows:** Nextflow, Snakemake, Apache Airflow ## Grants & Awards -- **AI4LIFE** (2022) — Co‑investigator on **€5M** EU grant (federated bioimage AI) +- **AI4LIFE** (2022) — Co-investigator on **€5M** EU grant (federated bioimage AI) - **EPSRC CDT Studentship** (2013–2018) — Photonic & Electronic Systems CDT (£120k) -- **Nuffield Research Bursary** (2012) — Computer vision for liquid‑crystal flows +- **Nuffield Research Bursary** (2012) — Computer vision for liquid-crystal flows - **Institute of Physics** grant support (2009–2012) ## Teaching, Mentoring & Service @@ -112,5 +114,3 @@ See **Google Scholar** for complete publication list: [scholar.google.com/citati - **Peer review:** Nature Methods, Scientific Reports, Journal of Microscopy, ISBI, **ICASSP** - **Talks & conferences:** FOM (2018, 2022, 2023), MMC (2018, 2022), CBIAS (2023) - **Community leadership:** Rowing captain/coach (Magdalene College), Mountaineering Club President (NTU) - -*References available upon request.*