Nathanael Sheehan

My research explores data in the post-genomic age, focusing on the politics and philosophy of ‘open science’: a new ap- proach to the scientific process based on cooperative work and new ways of diffusing knowledge by using digital technolo- gies and new collaborative tools. Combining approaches from philosophy of science, computer science and science and technology studies, my doctoral thesis is grounded in the case of genomic surveillance, examining the historical and cul- tural elements at play in the dissemination and preservation of data in a crisis. Central to my research is the publication of free and open-source software. I am interested in the application of machine learning/deep learning tools and techniques in the context of pattern recognition in large scale data analytics, while also focusing on creative and artistic plotting of scientific data