Hybrid Cloud, Smarter Research

The Anant Madabhushi Lab at Emory University leverages AWS as a critical extension of its on-premises infrastructure to support cutting-edge research in biomedical imaging and machine learning. The lab focuses on applying machine learning (ML) techniques to various stages of the drug discovery and development pipeline, including target validation, prognostic biomarker identification, and digital pathology analysis in clinical trials. These projects often involve high-dimensional, complex datasets that require scalable and flexible computing resources.

While the lab’s local infrastructure supports many routine and long-term computational needs, AWS provides the agility to scale rapidly for high-demand or time-sensitive projects. Services like Amazon EC2 and Amazon S3 are used extensively to run ML models and store large volumes of imaging and clinical data. The cost-efficiency and scalability of AWS have enabled the lab to expand its computational inventory without the need for significant hardware investments.

AWS at Emory has been instrumental in this hybrid model, offering competitive cloud storage rates and seamless integration with the lab’s workflows. This setup allows researchers to dynamically allocate resources based on project demands, significantly improving turnaround times and enabling more iterative experimentation.

The lab’s AWS usage is managed by Krunal Pandav, the designated data custodian, in collaboration with the AWS at Emory team, who provide ongoing support and ensure smooth operation of cloud resources. This partnership has been essential in maintaining a secure and efficient research environment.