Promoting the use of data science in marketing.


Every year, Adobe funds a university faculty research program to promote the understanding and use of data science in the area of marketing. Our goal is to encourage both theoretical and empirical development of solutions to problems in marketing.


Adobe will provide funding support of up to $50,000 to a North American academic institution, college, or university for each selected research proposal. Awards will be in the form of an unrestricted gift to the academic institution under the names of the researchers who submitted the proposal.


Each proposal will address an area of interest relative to Adobe Experience Cloud. This comprehensive set of cloud services gives businesses access to an integrated set of solutions to build campaigns, manage advertising, and gain deep intelligence about the business. It’s everything a company needs to drive brand growth and orchestrate an amazing customer experience.


Topics for research include, but are not limited to, the following areas:

Transforming insights from the trillions of customer touch points that we track on behalf of brands into advanced analytical algorithms to make high-value predictions about consumer experiences.
Analyzing data to better deliver personalized digital experiences to customers across websites, applications, emails and notifications.
Using data to help brands design and deliver effective advertising campaigns across search, display, social, video and mobile channels to reach and acquire customers efficiently.


Grant Submission Guidelines & FAQ


Who is eligible to receive the grant?

Full-time faculty members from North American universities


How long should the proposal be?

Preferably two pages


Submission requirements:

Title, proposer name and contact information, research goals, description of project(s), use of funds


Award Range:

Up to $50,000 (US)

*Adobe does not pay for overhead on unrestricted gifts. This unrestricted gift should not be used for indirect costs, administrative costs, and overhead charges.



August 13, 2021

Send proposals and questions to



February 2021 Award Winners


Rice University's Prof. Anshumali Shrivastava

Theory and Practice of Efficient Graph-Based Near-Neighbor at Scale


University of Illinois at Chicago's Elena Zheleva

Heterogeneous treatment effect estimation with guarantees


Massachusetts Institute of Technology's Ramesh Raskar

Learning Behavioral Policies over Networks of Interacting Agents


Northeastern University, Boston's Y. Raymond Fu, Ph.D.

Time-Aware Causal Embedding for Personalized Digital Marketing


August 2020 Award Winners


Pennsylvania State University's Lingzhou Xue and University of Nebraska-Lincoln's Qian Chen

Scalable Graphical Event Models for Marketing Attribution


Purdue University's Wreetabrata Kar and Mohammad Rahman

An Advertiser’s Dilemma with Marketing Interventions: At Scale Heterogenous Treatment Effects to Rescue


The University of Texas at Austin's Zhangyang “Atlas” Wang

Towards Automated Design of Efficient Deep Multi-Modal Recommendation Models


University of Southern California's Adel Javanmard 

Learn your customer novel statistical methods for segmenting online users and their behaviors


Visit Adobe Research for more information.

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