Short Version in 3rd Person
Alex Rutherford is an interdisciplinary data scientist with more than 10 years of experience across academia, the public sector and industry. Following a training in computational physics, he subsequently spent several years applying data driven analysis and computational modeling to problems such as ethnic violence, the evolution of corruption, global communication networks, and social search. He has helped to pioneer the use of data science within the United Nations system with Global Pulse and UNICEF Office of Innovation including analysis of vaccine sentiment, migration, poverty mapping, epidemiology and constitutional reform. Alex continues to improve his Arabic language after living for several years in Syria and the United Arab Emirates. He is currently a Research Scientist focusing on problems of human-machine cooperation with Scalable Cooperation in MIT Media Lab.
Informal Pieces On My Background
PhD Career Stories podcast
Selected Media Coverage
How Mobile Phone Data Reveals Food Consumption Patterns in Central Africa - Technology Review
[German] Verräterisches Gezwitscher: Twitter als Seismograf der Welt - Heise
Computational Model of Peace Predicts Social Violence, Harmony - Wired
What countries' constitutions reveal about how societies evolve - Nature
Long Version in 1st Person
I am presently a research scientist with the Scalable Cooperation group in MIT Media Lab, as well as Director of Data Apparel. This follows tenures at Facebook in Silicon Valley, as a Research Scientist within UNICEF Office of Innovation and before that, in the Headquarters of the United Nations Global Pulse network. My work at the UN used data-driven research to protect vulnerable children and to understand how the UN can use data to set policy. And coffee, lots of coffee. A non-exhaustive and high level list of topics in which I am interested include; the spread of information and opinions via online social networks, human mobility and its role in epidemiology, data privacy and economic aspects of migration and social mobility. My toolbox contains concepts from statistical physics, artificial intelligence, generative approaches and data driven analysis.
I was born and grew up in the beautiful British city of Bath. After an adolescence spent reading Stephen Hawking and Carl Sagan, I left to study Physics (MPhys, Warwick University, 2004). Following a brief sampling of the finance sector, I returned to academia for my PhD. My thesis investigated numerical simulation of radiation damage in the context of fusion reactors (University College London, 2008).
After this, I spent a year learning Arabic at the University of Damascus, accidentally boarding night buses to Iraq, drinking sweet black tea and generally developing a passion for the Middle East.
My first postdoctoral position was at the New England Complex Systems Institute in Cambridge, MA where I began to analyse social systems. I extended previous work which predicted locations of ethnic violence in the former Yugoslavia using pattern finding techniques on census data (coverage in Wired and New Scientist and New York Times).
My next position charted a course towards computational social science via computer science; a postdoctoral researcher with the Social Computing and Artifical Intelligence Laboratory at Masdar Institute. I investigated the DARPA Balloon Challenge via numerical simulation, which appeared in the Proceedings of the National Academy of Sciences. I was also part of the 2011 Tag Challenge winning team, my work analysing the recruitment dynamic in this simulated manhunt has also received publicity in Nature, New Scientist and Technology Review (twice) and NBC among others.
More recently, I joined United Nations Global Pulse as a data scientist. In this position I helped to pioneer the practical use of data science to assist humanitarian and development policy through collaborative research pilots with development agencies including World Food Program, World Bank, Gates Foundation and the UN Population Fund (UNFPA). My work during this time applied techniques such as natural language processing, network analysis and time series analysis to emerging data sources such as mobile phone records, social media content and search logs. Notable projects included analysis of vaccine sentiment through social and mainstream media, mapping of displaced people during flooding using mobile phone records and proxying of indicators of wellbeing through global postal records.
In my role as a Research Scientist in UNICEF Office of Innovation I have investigated the quantitative dynamics of constitutional reforms to protect children and analysed mobility patterns and ento-epidemiological modelling of the Zika virus. I have also been part of teams undertaking technical collaborations with Google, IBM, Amadeus and Bloomberg to develop data analysis software and research projects.