About Me

I am a humanitarian and data scientist, working at the intersection of computer science, economics, and public policy. As a data scientist I uncover signals hidden in complex datasets using machine learning, advanced statistics, mathematical modeling, and rich visualization. As a humanitarian I seek to connect these discoveries to applications that create meaningful change in people's lives. Through a deeper, richer understanding of human society and history, I seek to give data 'a voice' - letting it speak for itself - enabling human action to advance social equality, economic opportunity, and environmental sustainability.

Professional Specializations
Other Skills
• Programming: R, Python, MATLAB • Public Speaking
• Database: SQL, MongoDB, Neo4J • Macro & Micro-economics
• Machine Learning: Neural Networks,
   Gaussian Processes, Online
• Food Security/Conflict Analysis
• Statistics: Bayesian, Geospatial, Econometrics,
• Solidity/Blockchain programming
• Data-Collection Methods: Survey Design, Design of
   Experiments, Remote Sensing, Institutional Data
• Film-making/Video-editing
• Visualization: QGIS, Tableau • Web programming

Professional Experience

Co-founder & CEO


Amsterdam, Netherlands
Mar 2019 - Present

Co-founder of a social-enterprise using machine-learning, network science, and blockchain to create completely decentralized credit systems, allowing individuals to assess risk, receive loans, and earn interest on savings without banks or other financial intermdiaries. We are striving to create a future with not only 100% financial inclusion, but also minimal barriers to capital, empowering individuals to take their future in their own hands by seeding sustainable cycles of opportunity.

Lead Data Scientist (UN-P3)

UN World Food Programme
Policy & Program Division (VAM)

Rome, Italy
Sep 2014 - Sep 2018

Founded a data-science team that continues to transform the way WFP gathers, measures, and disseminates information on the food security of nations during times of war, climate shocks, and other extreme events. We devised ways to provide near real-time information on food prices, food security, and scarcity of essentials using a combination of mobile-based surveys, call-detail records, satellite imagery, and crowd-sourcing. It was and continues to be an immense challenge, comprising original research in social statistics, applied research in a multitude of mathematical modeling domains (econometrics, simulatation, machine learning, etc), while building practical tools and infrastructure aimed at empowering individuals in the field.

Junior Fellow

William Davidson Institute
Public Health Supply Chains

Ann Arbor, Michigan, USA
July 2013 - Aug 2014

Researched and modeled vaccine and essential medicine supply chains for rural public health clinics under a grant from the Bill & Melinda Gates Foundation. I delivered two projects. The first, an impact evaluation study on mobile-phone-based inventory systems, required field data collection in the tribal areas of Arunachal Pradesh, India. The second project comprised a model and recommendation system for minimizing stockout at public health clinics in Tanzania via trans-shipment of essential medicines between neighboring clinics.

Analytics Consultant & Developer

Technology Labs

Chicago, Illinois, USA
Jan 2010 - June 2011

Lead developer for a machine-learning based work-queue optimization tool for health payers, that automatically detected, categorized, and prioritized manual claim adjudication rework. This was an industry first, and a novel application within the field of analytics. I also researched active learning and multi-classification SVMs. I co-authored and presented a paper at the International Journal Conference on Neural Networks


Health & Public Service

Chicago, Illinois, USA
July 2007 - Dec 2009

Engaged in several projects ranging from IT to strategy. Most notably, I lead statistical analysis for Accenture's 2009 High Performance Metrics Study for Health Payers, collecting and profiling operating and financial performance across 517 different measures for health plans across the country. I was the primary author of the resulting white paper, and presented findings to C-level staff for interested clients.


University of Michigan

Ann Arbor, Michigan, USA

July 2011 - May 2014

Masters of Economics

Former Joint PhD Candidate in Information Science and Economics—completed all PhD course requirements

Masters of Information

STIET Fellow: NSF IGERT fellowship awarded to develop researchers at the intersection of Computer Science and Economics as part of University of Michigan's STIET Lab (Socio-Technical Infrastructure for Electronic Transactions)

Purdue University

West Lafayette, Indiana, USA

Sep 2002 - May 2007

Bachelors of Mechanical

additional minors in electrical engineering, economics, philosophy

Selected Publications

A novel approach using Gaussian Processes to produce de-biased estimates of food insecurity in Yemen from noisy data sources

Now-casting food insecurity in Yemen
Singhal G, Flaxman S, Gelman A, et al.
Lancet, The (under review)

Proving the efficacy of mobile-phone based surveys for studying women's diets

Strengths and limitations of computer assisted telephone interviews (CATI) for nutrition data collection in rural Kenya
Lamanna C, Hachhethu K, Singhal G, et al.
PloS ONE (2019)

Premiere UN Report on Food Security and Nutrition - showed existence of structural break in trands

State of Food Security & Nutrition in the World 2017
UN Annual Report (2017)

Best Paper award at Humanitarian Tech Conference, 2016.

mVAM: A New Contribution to the Information Ecology of Humanitarian Work
Mock N, Singhal G, Olander W, et al.
Procedia Engineering (2016)

At the time a novel, ultra-fast method for doing multi-classification with SVMs

Piecewise Multi-Class Support Vector Machines
Oladunni T. & Singhal G.
IJCNN (2009)



View Gaurav Singhal's profile on LinkedIn