Opportunities for Collaboration

We are actively seeking collaborations for Duke Faculty and Students with industrial partners for mutual research benefit. Below are listed some of the opportunities available.

TMLD Sponsorships

We are pleased to offer the opportunity to help sponsor the Triangle Machine Learning Day event. There are three levels of sponsorship available with specific benefits at each level. We welcome inquires and requests for additional information at the contacts listed at the bottom of this page.

"Conference Sponsor" Level ($500):
Logo and appreciation on TMLD website, any printed flyers/programs, and on an overhead presented during the conference opening remarks

"Conference Partner" Level ($1000):
All of the above, plus a table at the conference where company information can be distributed, or recruiters can be available to talk with students

"Duke Machine Learning Affiliate" Level ($5000 and above):
All of the above plus participation in the Duke Machine Learning Affiliates and Research Seed Fund Programs (see below)



Data+ is a 10-week summer research experience that welcomes Duke undergraduates interested in exploring new data-driven approaches to interdisciplinary challenges. Students join small project teams, working alongside other teams in a communal environment. They learn how to marshal, analyze, and visualize data, while gaining broad exposure to the modern world of data science. Industry partners are essential to Data+ and we welcome your participation. Information about partnering can be found at the link above.

Machine Learning Research Seed Fund Program

Becoming a Machine Learning Affiliate of the inDuke Industry Relations Program is a way for industry to gain access to world class Duke faculty and students in machine learning. See machinelearning.duke.edu/people for a list of some of the machine learning experts at Duke.

Benefits for becoming a Machine Learning Affiliate include:

If your company would like to become a member of the Machine Learning Affiliates Program, contact Richard Lucic (lucic@cs.duke.edu, or 919-660-6524) or Kirsten Shaw (koshaw@duke.edu, or 919-660-5533).