Research Scholarships for Ph.D. Students and Postdocs

Congratulations to the Fall 2020 recipients!

Chi-Heng Lin

Gregory Canal

Henry Shaowu Yuchi

Jiaming Liang

Jiaojiao Fan

Jun-Kun Wang

Li Chen

Liyan Xie

Majid Farhadi

Mehrdad Ghadiri

Minshuo Chen

Nathan Somavarapu

Rachel Kuske

Ramon Auad

Siva Theja Maguluri

Tim Lieuwen

Weiwei “William” Kong

Yan Li

The Institute for Data Engineering and Science (IDEaS) and Transdisciplinary Research Institute for Advancing Data Science (TRIAD) will support scholarships to support Ph.D. students or post-doctoral researchers in high-impact cross-disciplinary data science related areas. Each scholarship will co-fund a GRA appointment or a postdoc position with rest contributed by the faculty advisor. Priority will be given to projects that are close to the theme of foundation of data science. Examples include, but are not limited to:

  • Theoretical research on optimal transport and its relation to the foundations of data science
  • Theoretical research on the foundations of deep learning (e.g., recent activities on neural tangent kernels, mean field views, implicit regularization, etc.) and their explanatory power on the effectiveness of deep learning methods
  • Partial differential equation-based models with applications in data science
  • Other research exploration in a new direction with potential for establishing new foundations of data science, especially in the area of reinforcement learning, 

The program is not intended as a source for routine research support.

Applications are closed. We will update when future opportunities become available. 

Microsoft Azure Credit Awards

IDEaS has partnered with Microsoft to make Azure cloud credits available to support data intensive research. The awards are intended to support:

  • Open data, data collaboration, and data sharing projects that seek to make more data available and accessible for research, including curated, labeled training data sets for AI/ML models.
  • Data intensive research and projects in different domain areas; e.g. biomedical and health, climate and sustainability, life sciences, materials and manufacturing, smart cities, social sciences, etc.

Proposals are solicited from academic or research faculty in the form of a single pdf file including:

  • A brief technical description of the proposed research and how the Azure cloud credits will be utilized.
  • Justification of the need for cloud credits in the context of other computational resources available for the project.
  • The dollar value of the cloud credits requested (minimum: $5K; maximum: $25K) and justification for the magnitude of the request. The Azure calculator may be useful for estimating credits, and is available at:

At least $100K Azure cloud credits are available to be allocated under this program. The allocated credits expire on June 30, 2021. Online training resources are available at and


Applications are closed.