Dr. John D. Kirwan

Dr. John D. Kirwan

Bioinformatics Scientist

Arquimea Research Centre

Professional Summary

I'm a computational biologist working at the interface of data science and biology - applying statistical and machine learning approaches to uncover structure in complex biological data. I am a senior scientist at Arquimea Research Centre, La Laguna, Spain. My background spans experimental biology, computational modeling, and bioinformatics. After completing a PhD at Lund University focused on visual systems in invertebrates, I transitioned toward data-driven biology - developing analytical tools and predictive models that bridge biological insight and computation. I enjoy learning new analytical methods, writing code, and communicating science clearly. My goal is to continue growing as a biological data scientist, expanding across diverse fields within the life sciences while keeping biological meaning at the core of the analysis.

Education

PhD

Lund University

MSc

University College Dublin

BSc (Hons)

University College Dublin

Interests

Data Science Computational Biology
📚 My Research
My current research focuses on data science in the life science domain.
Featured Publications
Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows featured image

Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows

Post hoc uncertainty quantification for deep regression using contextualized normalizing flows without retraining the base model.

Adriel sosa marco
Phenotypic response to food availability in sea urchin larvae and impact of light during development and growth featured image

Phenotypic response to food availability in sea urchin larvae and impact of light during development and growth

Phenotypic plasticity, the ability of a genotype to produce different phenotypes in response to environmental conditions, plays a crucial role in adaptation and evolution and can …

Maria cocurullo
A Model of Decentralized Vision in the Sea Urchin Diadema africanum featured image

A Model of Decentralized Vision in the Sea Urchin Diadema africanum

Sea urchins can detect light and move in relation to luminous stimuli despite lacking eyes. They presumably detect light through photoreceptor cells distributed on their body …

Tianshu li
Recent Publications
(2025). Dancing in the dark: The annelid Platynereis dumerilii is re-envisioned for its climactic final night. Journal of Experimental Biology.
(2025). Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows. The Thirty-ninth Annual Conference on Neural Information Processing Systems.
(2025). Phenotypic response to food availability in sea urchin larvae and impact of light during development and growth. Frontiers in Ecology and Evolution.
(2023). A Model of Decentralized Vision in the Sea Urchin Diadema africanum. iScience.
(2021). Run and Hide: Visual Performance in a Brittle Star. Journal of Experimental Biology.
Recent & Upcoming Talks