Joint appointment in the Machine Learning Department and the Heinz College of Information Systems and Public Policy, working at the intersection of AI/ML/Data Science and Public Policy/Social Good.Working with governments and non-profits across health, education, criminal justice, social services, economic development, public safety.Research Focus on Fairness, Equity, Interpretability in Human-AI collaborative systems

http://dssgfellowship.orgThe Data Science for Social Good fellowship is a University of Chicago summer program for aspiring data scientists to work on data mining, machine learning, big data, and data science projects with social impact.Working closely with governments and nonprofits, fellows take on real-world problems in education, health, energy, transportation, and more. For three months in Chicago they apply their coding and analytics skills, collaborate in a fast-paced atmosphere, and learn from mentors coming from industry and academia.

Our goal is to change the empirical foundation of social science, statistical and public agencies in the United States and transform understanding of how our society works. We are a fast growing university-based startup that has already created dozens of pilot projects, worked with over 100 agencies – federal, state and local - and trained over 250 agency staff. Our offerings include data analytics trainings for governments, non-profits, and organizations who work with them, collaborative projects in public policy areas, and a secure, collaborative, data infrastructure to make this work possible.

Helping non-profits, charities, and advocacy groups turn their supporters into advocates for fundraising, content sharing, advocacy, volunteer recruiting, and event publicity. Our Targeted Sharing product is based on a similar tool built by us during the Obama Campaign that allowed us to use data, analytics and social network analysis to turn an online army of volunteers into advocates.

Chief Scientist at Obama 2012 Re-election Campaign working on Analytics, Social Media, Data, and Technology.

Leading a research group focused on applied research in machine learning, data mining, predictive analytics, text analytics. Recent Projects include:- Text Analytics for Social Media: Sentiment Analysis, Topic Modeling, Interactive joint topic sentiment detection, Active learning for cross-domain sentiment classification, entity sentiment detection- Predicting Errors in Health Insurance Claims- Text analytics for email compliance- Machine learning for Text Redaction- ACTIVE: EU-funded project on using machine learning and semantic technologies to improve knowledge management and collaboration in enterprises- Interactive Attribute Discovery & Extraction for Product Catalogs: semi-supervised and active learning for information extraction- HR Analytics: attrition prediction, engagement and performance prediction- Text Analytics for survey analysis and optimization- Enterprise Search & Knowledge Management- Entity Retrieval & Ranking (applied to Expert Search) - Data Anonymization: Guessing anonymity based anonymization algorithm- Data Mining for Personalized Promotions and Customer Targeting using Individual Consumer Models- Price Prediction & Price Insurance for Auction Marketplaces - Robust Reasoning for Sensor Networks