The project has collected a large set of data (>200GB) from a cryptocurrency block chain. It is developing methods for detecting anomalies in transactions based on newer Social Networks, Graph Analysis and Machine Learning methods. The work involves data cleaning/wrangling and creation and implementation of various algorithms and analyzing the transactions for identifying different set of anomalies and manipulations.

One selected candidate will receive a stipend via the DSI Scholars program. Amount is subject to available funding.

Faculty Advisor

  • Professor Siddhartha Dalal
  • Department/School: SPS/Arts and Science
  • Location: Morningside Campus
  • Siddhartha Dalal is a Professor of Practice at Columbia University with more than 100 peer-reviewed publications, patents and monographs covering the areas of machine learning (NLP, Computer Vision), Bayesian Statistics, software engineering, etc. Prior to Columbia he was Chief Data Scientist at AIG, CTO at RAND, VP of Research at Xerox and Chief Scientist at Bellcore.

Project timeline

  • Earliest starting date: 03/01/2019
  • End date: 07/30/2019
  • Number of hours per week of research expected during Spring 2019: ~15
  • Number of hours per week of research expected during Summer 2019: ~40

Candidate requirements

  • Skill sets: Knowledge and experience of: Python and CUDA; – Architecture of GPUs and heterogeneous systems; – Data structures and algorithms for massively parallel systems- clusters and clouds; – Profiling and performance optimization of GPUs or other compute accelerators using different frameworks.
  • Student eligibility (as of Spring 2019): freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible