Prediction Markets have been used to forecasts outcomes of research interest using market mechanism (See https://www.nature.com/news/the-power-of-prediction-markets-1.20820). A decentralized prediction market, Augur, has been created on blockchain for betting purposes (See, https://www.augur.net/). An alternative approach to prediction market has been proposed in Dalal et al (https://www.sciencedirect.com/science/article/abs/pii/S0040162511000734). This project proposes to develop a new model for decentralized prediction market which can be used to elicit opinions of university researchers on socially important issues. Specifically, the project will use Ethereum based platform to develop a smart contract and an ERC-20 compliant token for researchers to participate in the new market.

Continue reading

Water joined gold, oil and other commodities traded on Wall Street, highlighting worries that the life-sustaining natural resource may become scarce across more of the world. In the state of California, the biggest U.S. agriculture market and world’s fifth-largest economy, this challenge is particularly prevalent. Farmers, hedge funds and municipalities are now able to prepare for the risk that future water availability issues can bring in the state of California.

Continue reading

The objective of this project is to construct linkages across disparate public health data systems using machine learning tools and assess them for bias and equitable representation of subpopulations defined by demographic and socioeconomic factors.

Continue reading

The amount of video content that is being distributed over the Internet is increasing. Video providers rely on HTTP adaptive streaming approaches to deliver video clips to users. Complementary to the video provider, the service provider must determine the priority of each network stream. As part of the project, students will explore wireless network assisted strategies for http adaptive streaming by use of TOS/DSCP. This includes using machine-learning tools to analyze network video traffic and the design of reinforcement learning algorithms to improve users' video Quality of Experience.

Continue reading

Data is central to the NYC Department of Health’s mission to protect and promote the health of all New Yorkers. The agency’s many programs often require large scale record linkages that integrate data from individuals across multiple public health data systems and disease registries. We are implementing a Master Person Index (MPI) system in order to centralize, optimize and standardize matching methodology for administrative data across the Department of Health.

Continue reading