Cryptocurrency Analytics: Identifying Bad Actors
Many of the cryptocurrency transactions have involved fraudulent activities including ponzi schemes, ransomware as well money-laundering. The objective is to use Graph Machine Learning methods to identify the miscreants on Bitcoin and Etherium Networks. There are many challenges including the amount of data in 100s of Gigabytes, creation and scalability of algorithms.
One selected candidate will receive a stipend via the DSI Scholars program. Amount is subject to available funding.
- Professor: Siddhartha Dalal
- Department/School: Statistics Dept, and Applied Analytics,
- Location: Lewisohn 502E
- Over 100 publications in Machine Learning, Software Engineering and Statistics
- Earliest starting date: 3/1/2020
- End date: 8/31/2020
- Number of hours per week of research expected during Spring 2020: ~12
- Number of hours per week of research expected during Summer 2020: ~40
- Skill sets: Algorithm Coding using Python, Machine Learning, Statistical Analysis of the results:
- Student eligibility:
freshman, sophomore, junior, senior, master’s
- International students on F1 or J1 visa: eligible