Conference: Workshop to Build a Vision and Strategy for Creating a National Network of Academic Cloud and Self-Driving Labs

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

The Workshop to Build a Vision and Strategy for Creating a National Network of Academic Cloud and Self-Driving Labs will support a national-scale workshop focused on accelerating science through innovations provided by self-driving labs (SDLs), cloud labs, and automated science. The workshop will bring together academics, industry representatives, and government partners to understand the state-of-the-art in cloud labs and SDLs, and develop a roadmap for a national network of resources. Investing in these technologies can help the US retain its international leadership in scientific innovation, and can foster a virtuous cycle of innovation and discovery. A national network of cloud labs and SDLs can democratize access to advanced scientific equipment, enhance reproducibility, accelerate the translation of basic research into commercialization, and promote open science principles. The workshop will bring together a mixture of academics from multiple types of universities, from R1 research universities through community colleges, representatives from foundations, and government and industry leaders to explore the broad set of issues. Participants with diverse backgrounds and experience will be recruited for the workshop, including faculty/researchers from HBCU’s and MSI’s, as well as early and late career faculty, with the goal of building a roadmap for a national network that is inclusive from the very beginning. Discussions will focus on the transition from trial-and-error research to automated research workflows driven by artificial intelligence (AI) and machine learning (ML). The workshop will explore integration of computing in scientific advancements to enable a new model of scientific discovery through continuous refinement of models within the data generation feedback loop using automated research workflows. The vision being pursued is the automation of experiments and utilization of AI/ML methods to fine-tune models in order to much more quickly understand complex phenomena and guide future experiments towards rapid refinement and discovery. The workshop will address challenges that one may encounter in the process including the need for advanced innovations in instrumentation, incorporation of active learning, fostering collaborations, and adapting education and training to the use of such remote laboratories. The workshop includes plenary sessions, breakout tracks, and discussions led by experts from academia, industry, and national scientific infrastructure networks. The outcome of the workshop will inform the roadmap for the development of a national network of academic self-driving labs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.