The Colorado Data Science Team is a team of data scientists, machine learners, number crunchers, and statisticians at the University of Colorado Boulder. Our primary goal is educational: to get hands on experience working in teams applying modern machine learning tools to real problems with real data. As part of this goal, we compete in internal prediction challenges, as well as representing CU Boulder in global competitions as seen on Kaggle, DrivenData, Quantopian, and other platforms.

CODATA was inspired by our sister team, the Michigan Data Science Team (MDST). We owe our initial success to the generosity and guidance of the team and its faculty advisor, Jake Abernethy.

Co-President: Brad Gordon

Brad Gordon
  • Full-time software engineer at Fusionbox with a passion for computational statistics and machine learning
  • Attends CSCI and APPM courses at CU on a part-time basis
  • Systems minded data scientist
  • Graduated from Grinnell College with a dual MA in Mathematics and Philosophy
  • Ardent consumer of political data (polls, economic/social policy analysis, you name it)

Co-President: Monal Narasimhamurthy

Monal Narasimhamurthy
  • First year PhD student, advised by Prof Matthew Hammer
  • Member of the Programming Languages and Verification group at CU Boulder (CUPLV)
  • Research focus on Programming Languages and Incremental Computation
  • Worked or interned previously at Amazon, and Apigee
  • Code at, LinkedIn

Team Captain: Pedro Rodriguez

Pedro Rodriguez

Communications Officer: Nicolas Metts

  • 2nd year PhD student advised by Christine Lv.
  • Primarily interested in classification with unbalanced data, but also interested in music information retrieval and network science applications to social sciences
  • Data scientist at CableLabs in Louisville
  • LinkedIn
  • Musician, father, husband, and amateur chef

Treasurer: Apoorva

Webmaster: Mahesh Kumar Ravindranathan

Mahesh Kumar Ravindranathan
  • 2nd year Computer Science Master Student
  • Interested in Big Data - Distributed Systems, Scalability, Data Engineering
  • Worked or interned previously at Oracle Managed Cloud Services and Oracle Data Cloud
  • Website at, Code at, LinkedIn

Faculty Advisor: Rafael Frongillo

Rafael Frongillo
  • Assistant professor of computer science at CU Boulder, and affiliate faculty in applied math.
  • Research is at the interface of theoretical machine learning and economics,encompassing topics such as information elicitation, crowdsourcing, and markets.
  • Was previously a postdoc at MSR-NYC and then at Harvard's CRCS with Yiling Chen and Yaron Singer in the EconCS group
  • Completed Ph.D. in theoretical computer science at Berkeley, advised by Christos Papadimitriou and funded by the NDSEG Fellowship
  • Website , LinkedIn