Cristian Soitu

Computational Biology Researcher & ML/AI Scientist

An ML Engineer with a strong background in developing and applying machine learning models to complex biological data. Experienced in the end-to-end development of computational tools for 3D bio-imaging and multi-modal data analysis. A proficient Python developer focused on leveraging advanced AI techniques, including Transformers and CNNs, to solve challenges in oncology and neuroscience.

AI for Oncology Tissue Profiling 3D Bio-imaging and Image Registration Spatial Omics Analysis Deep Learning for Biological Data Multi-modal Data Integration Transformers & CNNs

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HFSP Senior Postdoctoral Research Fellow

University of Oxford

Oxford, United Kingdom

Professional Experience & Education

Career Journey & Academic Background

08/2024 - Present

HFSP Senior Postdoctoral Research Fellow

University of Oxford

Developed AI models for oncology tissue profiling by integrating multi-modal spatialomics data. Utilized Transformers, ResNet architectures, and generative models (VAEs) for tissue morphology analysis. Analyzed single-nucleotide variants (SNVs) and copy number alterations in prostate cancer using data mining methods.

01/2021 - 07/2024

HFSP Postdoctoral Research Fellow

Cold Spring Harbor Laboratory, USA

Led the development of scalable computational workflows to analyze large-scale, multimodal neuroscience imaging data. Designed and deployed user-facing Python-based GUIs, creating human-in-the-loop pipelines to accelerate scientific discovery. Led a technical team of 4 scientists and mentored 2 interns, driving project execution and fostering innovation.

2021

DPhil in Engineering Science

University of Oxford

Research in microfluidics, neuronal cell culture, and computational pipeline development.

2016

MEng in Mechanical Engineering

University of Aberdeen

1st Class Honors; IMechE Best Project Award.

Featured Projects

Computational Biology Research & Development

Glomeralign

An AI-based image registration tool for aligning brain slices in the olfactory system to 3D volumes.

Python • Deep Learning • Image Processing • 3D Registration

Revvie

Built a computational framework for in-vivo to ex-vivo registration of individual neurons.

Python • Computer Vision • Neural Registration • Microscopy

Spatial-Omics AI Integration

Built models for automated tissue profiling in oncology using multi-modal data.

Transformers • ResNet • VAEs • Spatial Analysis

Aissda

A pipeline for processing and analysing in-situ sequencing images.

Python • Image Processing • Bioinformatics • Sequencing

Bioinformatics Workflow Automation

Created scalable pipelines for sequencing and imaging data using tools like Snakemake.

Snakemake • Python • HPC • Cloud Computing

Visualization Tools

Interactive visualization tools for biological data exploration including Embedly for high-dimensional embeddings and Spatial-Embedly for dual-window spatial analysis.

Python • Dash • Plotly • UMAP • Interactive Visualization

Technical Skills

Expertise in AI/ML, Bioinformatics & Software Engineering

🤖 Machine Learning & AI

Python PyTorch TensorFlow Transformers CNNs VAEs Self-Supervised Learning Dimensionality Reduction (PCA, UMAP, t-SNE) Clustering

🧬 Bioinformatics & Data Analysis

Spatial-omics Multi-omics Integration Imaging Pipelines Sequencing Data Analysis Variant Calling R Data Mining

💻 Software & Engineering

C++ Git Snakemake Cloud Computing High-Performance Computing (HPC) Containerization GUI Development

Interactive Data Visualizations

Explore biological data through interactive demos

🔬 Prostate Cancer Sample - PESO Dataset

Explore latent embeddings of prostate tissue patches from the PESO dataset. Each point represents different tissue types. Hover over points to see the original histology images.

🌍 Spatial-Embedly: Dual Window Visualization

Explore the relationship between spatial coordinates and embedding space with synchronized highlighting across both views.

🧬 MNIST Digit Embeddings

Classic MNIST digit visualization demonstrating UMAP dimensionality reduction techniques.

🧠 Revvie - Registration of Ex-vivo to In-vivo

Registration of ex-vivo to in-vivo of single neurons in the brain. Built using Napari, a human-in-the-loop GUI with a point cloud registration algorithm in the background.