Joseph Aylett-bullock is a data scientist with nine years of research and applied AI experience at the United Nations, currently supporting peace operations from New York. He combines a PhD in theoretical and mathematical physics with hands-on machine learning practice developed at UN Global Pulse and industry research roles at NYU’s RiskEcon Lab and Numerati® Partners. His work spans ethical AI governance—helping draft UN-wide principles—to operational data science for humanitarian and epidemic management, showing rare fluency across policy, research and deployment. Comfortable bridging academic rigor and real-world impact, he has translated PhD-level modelling into production-ready imaging and analytics tools and teaches peers through workshops and advisory roles.
9 years of coding experience
4 years of employment as a software developer
Doctorate of Philosophy, Theoretical and Mathematical Physics, Doctorate of Philosophy, Theoretical and Mathematical Physics at Durham University
Mini-MBA, Business Administration and Management, General, Mini-MBA, Business Administration and Management, General at Durham University Business School
CS50, Computer Science, CS50, Computer Science at Harvard Extension School
English, german (gcse a* and additionally classes at university), arabic (writing, speaking, reading and listening) cefr a2
Agent-based model for simulating the spread of epidemics in refugee and IDP settlements. Adapted from the JUNE framework.
Contributions:1 release, 237 commits, 2 PRs in 2 years 5 months
model-basedepidemic-modelagent-basedidpadapted
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Joseph Aylett-bullock - Data Scientist (Department Of Peace Operations)