American Family Funding Initiative Awards
Teams of UW-Madison faculty and collaborators have received support through the American Family Funding Initiative for data science projects ranging from furthering third-wave artificial intelligence to supporting student entrepreneurship.
Topics of Interest
American Family wants new ideas and tools in these areas:
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Behavioral economics and applied cognitive science
- Analytics driven “choice architecture”
- Cognitive bias identification
- Information overload
- Customer decision making
- Computational cognitive models
Signal processing and data fusion
- Computer vision
- Internet of Things (IoT) applications
- Speech recognition
- Natural language processing (NLP) and natural language understanding (NLU)
- Aerial satellite imagery (e.g., drones, GIS)
- Temporal data analytics
- Autonomous vehicles
- Weather prediction modeling
Bias, ethics and robustness
- Bias and ethics in AI models
- Bias and ethics in human-driven processes
- Model robustness
- Adversarial AI
Robotic process automation
- Customer Service automation
- Conversational agents
- Recommender systems
Optimization and operations research
- Scalable optimization
- Optimal decision-making
Knowledge Representation
- Knowledge driven information extraction
- Data-driven knowledge construction/expansion
- Inference in knowledge graphs
- Metadata organization and management
Data management and integration
- Entity matching
- Data cleaning
- Automation of data workflows
- Advances in exact, transform, load (ETL) or exact, load transform (ELT)
- Efficient data storage and retrieval
Fraud, insurance risk, marketing and claims analytics
- Claims fraud detection
- Customer retention and valuation models
- Real-time risk prediction during catastrophic events
- Digital underwriting
- Novel approaches to pricing
Artificial Intelligence (AI) and data science are becoming core components of the insurance industry, motivated by the increasing availability of data, including masses of unstructured data, scalable cloud computing, exponential growth in computing power, new modeling tools, and the ongoing drive for operational efficiency and cost reduction. With big data and new data sources, such as social media, Internet of Things (IoT), telematics, web logs, video and images, and clickstreams, the opportunity to apply artificial intelligence has never been greater across areas of insurance operation. American Family has partnered with UW through the American Family Insurance Data Science Institute (DSI) to offer this unique opportunity.
DSI is committed to working with researchers in all disciplines on campus and encourages anyone interested to apply. If you have questions or would like to discuss your project, please contact research@datascience.wisc.edu.
APPLY FOR FUNDING
American Family Insurance is interested in sponsoring research and applications of data science, artificial intelligence (AI), and machine learning (ML) that is directly or indirectly related to the insurance industry. Topics of interest include, but are not limited to those listed on the left.
DEADLINES
The deadline for Fall 2020 has passed. Our next funding cycle will begin in Spring 2021.
ELIGIBILITY
You must be a UW–Madison faculty member or a UW–Madison permanent PI. CHS faculty and academic staff without permanent PI status may participate in applications as co-PIs or co-investigators.
ABOUT THE APPLICATION PROCESS
Applications should explicitly address innovation, significance, risk, and impact. Funding will be provided for 1–2 years, depending on the needs and scope of the project. The average award will be approximately $75,000, with a maximum award of $150,000.
Each proposal will be evaluated according to the following five criteria:
- Potential Impact to Data Science
- Potential Impact for Practical Use
- Novelty of Methodological Approach, either through applications or foundations
- Alignment with AmFam Topics of Interest
- Overall Quality of the Proposal
Detailed instructions for proposal creation and submission can be found HERE.
View 2020 awards HERE.