Joseph Aylett-Bullock,PhD is a Science Advisor for Remote Sensing and Imaging to Numerati^® Partners LLC focusing on remote sensing and imaging, and an affiliated research advisor at RiskEcon^® Lab for Decision Metrics @ Courant Institute of Mathematical Sciences NYU, having also formerly served for over two years concurrently as an Affiliated Expert with Numerati^® Partners and an Industry Research Associate at RiskEcon^® Lab.

Joseph is currently a Researcher at United Nations Global Pulse, an innovation initiative of the United Nations (UN) to harness emerging technologies for humanitarian development and part of the Executive Office of the UN Secretary-General. Through his research at UN Global Pulse, Joseph has worked on projects involving the UN Department for Political and Peacebuilding Affairs (UNDPPA), the UN High Commissioner for Refugees (UNHCR), UN Peacekeeping (UNP), the UN Office for the Coordination of Humanitarian Affairs (UNOCHA) and UNOSAT, the UN’s satellite program. His work at UN has included: developing Artificial Intelligence (AI) methods for automating satellite image analysis for mapping refugee camps, damage assessment and flood detection; helping UN field missions understand political sentiment in social media posts; assessing the risks of automated text generation; and investigating the human rights implications of AI. Joseph has spoken widely on the use of AI in the humanitarian sector, and has served as Track Chair for the AI for Social Good workshop at NeurIPS, the most widely attended AI conference, and Senior Program Chair for the Social Impact Track at AAAI 2020.

Joseph recently completed his doctorate at the Institute for Particle Physics Phenomenology, the UK national particle physics research laboratory and part of Durham University, working on approximating high precision calculations for complex particle collision processes at CERN using Machine Learning. He is also an affiliate of the Institute for Data Science at Durham University, where he conducts research on applications of AI to a variety of real-world problems.

In his prior role as a Numerati^® Partners Affiliated Expert, Joseph participated in technical testing of remote sensing and imaging technologies. As an Industry Research Associate at RiskEcon^® Lab, he co-advised lab team research of machine learning algorithms across image recognition and segmentation domains. Joseph has also consulted for private industry, working primarily with insurance and medical sector participants, including developing a new methodology for automatic X-Ray image segmentation now being used in production.

 
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