About the Research Center

We aim to explore the design, analysis and application of massive-scale computing systems for processing data, in the most general sense.

The goal is to address the underlying systems aspects of big data—including data processing, storage and retrieval—which are central to some of the key research and societal challenges of the 21st Century.

The AI for Sciences and Engineering Center explores the design, analysis, and application of scale-appropriate AI and computing platforms that advance scientific reasoning and discovery. The Center’s mission is to build and understand the next generation of AI architectures and algorithms, not just trained on scientific data, but designed to reflect the structure of the sciences themselves.

The AI for Sciences and Engineering Center serves as a hub for large-scale AI and computing research, fostering the collaborations and systems innovation that make scientific discovery faster, deeper, and more explainable. It connects two core communities at Columbia:

  1. Researchers developing new computational tools and AI systems, such as novel learning paradigms,  scientific databases and large-scale software for learning, distributed and energy-efficient architectures, and  high-performance processors.
  2. Researchers applying AI methodology and systems to scientific problems across fields such as physics, climate science, materials research, oceanography, neuroscience, and biomedical informatics—where breakthroughs depend on innovations in computation and data modeling.

This dual focus creates a continuous exchange between AI platform builders and scientific practitioners, accelerating discovery through collaboration.

As scientific research becomes increasingly computational, the Center focuses on challenges where extreme-scale learning algorithms, data processing, model design, and scientific reasoning converge. Columbia’s interdisciplinary strengths—paired with growing partnerships across academia and industry—position AISE to help shape what the next generation of scientific AI will look like.

AI for Sciences and Engineering: Monthly Seminar Series

The AI for Sciences and Engineering Monthly Seminar Series, hosted by the DSI Computing Systems for Data-Driven Science Center, will run monthly throughout the 2025–26 academic year. Designed to spark collaboration across disciplines, the series alternates between invited talks from external experts and Columbia-led lightning sessions, with a focus on four core themes: Quantum, Astrophysics, Environment/Climate, and Engineering.

Open to Columbia faculty, the series provides a forum to exchange ideas, share expertise, and build research connections across domains.