ARTISAN develops scalable, high-performance distributed systems that power AI and scientific research. Our work focuses on efficient data processing, storage, and computation to address complex scientific challenges.
We develop and deploy efficient AI and Machine Learning (ML) tools for science. Our team’s aim is to create and deploy MLops (Machine Learning Operations) practices tailored explicitly for a range of scientific research disciplines. We seek to support the Georgia Tech research community by working with faculty to develop infrastructure to streamline research workflows, reduce redundancies and ensure reproducibility, create benchmarking processor types, and ensure scalability across multiple GPUs for parallel codes in scientific ML applications.