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.

This project is eligible for a matching fund stipend from the Data Science Institute. This is not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: Siddhartha Dalal
  • Department/School: Statistics Dept/CAS & Applied Analytics/SPS
  • Location: Lewisohn 502E
  • Teaching and research on Machine Learning, and Blockchains & Cryptocurrencies

Project Timeline

  • Earliest starting date: 3/1/2021
  • End date: 9/1/2021
  • Number of hours per week of research expected during Spring 2021: ~12
  • Number of hours per week of research expected during Summer 2021: ~30

Candidate requirements

  • Skill sets:
    • Required:
      • Java, Javascript, and/or Python
      • Familiar with common algorithms and data structures
    • Nice-to-have
      • Exposure to privacy and security as well as the testing of these
      • Exposure to cryptography
      • Understanding of Blockchain, smart contracts and cryptocurrency methodology
      • Blockchain programming frameworks including Solidity, Truffle, Ganache
      • Decentralized storage such as IPFS
      • Front end programming in HTML, CSS, Javascript, Node.js, React.js
      • Knowledge of C, C++
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes