Our lab conducts research in machine learning and blockchains. We have published more than 150 publications/patents/monographs to date. Prediction Markets have been used to forecast outcomes of research interest using market mechanisms (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 develops a new hybrid model for decentralized collaborative prediction market that can be used to elicit opinions of university researchers on socially important issues. Specifically, the project uses Ethereum based platform to develop a smart contract and an ERC-20 compliant token for researchers to participate in the new market. The smart contract is being developed in Solidity and Javascript. The corresponding frontend and backend uses Django and python on AWS cloud. The UI part is in JS which needs to get a more user friendly design.

Selected candidate(s) can receive a stipend directly from the faculty advisor. This is not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: Siddhartha Dalal
  • Center/Lab: Statistics
  • Location: Lewisohn 502 E
  • Research in Machine Learning and Blockchains. Published more than 150 publications/patents/monographs.

Project Timeline

  • Earliest starting date: 3/1/22
  • End date: Flexible
  • Number of hours per week of research expected during Spring 2022: ~12
  • Number of hours per week of research expected during Summer 2022: ~20

Candidate requirements

  • Skill sets: Required:

    • Strong interest in decentralized application on blockchain
    • Familiar with common algorithms and data structures
    • There are openings for 3 different roles- Please let us know your interest. 1 . Exposure to full stack development (Python Django, Javascript, AWS Lambda)
    1. Or, exposure to solidity smart contracts, Truffle/Infura
    2. Or, exposure HCI to Web UI design Nice-to-have
    • Exposure to privacy and security as well as the testing of these
    • Understanding of Blockchain, smart contracts and cryptocurrency methodology
    • Decentralized storage such as IPFS
  • Student eligibility: freshman, sophomore, junior, senior, master’s

  • International students on F1 or J1 visa: eligible

  • Academic Credit Possible: Yes