There is a small but diverse community of professionals that work at the intersection of academic research and Campus IT. Alternatively referred to as research computing facilitators, research data experts, system administrators etc. and broadly referred to as RCD (Research Computing and Data) staff, this is a community of experts that plays a critical role in the adoption and usage of technology for academic scientific research, bridging the worlds of microchips and microscopes.
The future of AI in Science hinges on acknowledging and empowering the role of these professionals, and building tools that ease the pain-points faced by these invaluable allies.
The history of research computing is almost as vast and storied as the history of computing itself. In fact, the very first programmable, electronic computers (ENIAC, EDVAC) were designed as tools for academic research at Universities. The first programming languages (FORTRAN) and the precursor to the current Internet (ARPANET) were built in the 60’s and 70’s as tools for researchers to more effectively collaborate and use these cumbersome machines.
While in the early days, it was the researchers (specially physicists and mathematicians) themselves who stepped into research computing roles, with the advent of personal computing and the democratization of access, a specialized field of experts emerged that excelled in understanding both Science and how Computing can be used to accelerate scientific discovery.
Over the years as computing evolved this community has shown a remarkable resilience in adapting to and exploiting the frontiers of technology for supporting research. From personal computers to national scale super-computers, High performance computing(HPC) to distributed cloud computing, they have built and rely on a strong community of practice and organizations that support the ongoing development of this field.
Some examples include (Sourced from my personal experience of working with these institutions and not exhaustive in any way) :
CARCC (Campus Research Computing Consortium) – An organization comprised of professionals who are dedicated to developing, advocating for, and advancing campus research computing and data, as well as associated professions.
PEARC (Practice and Experience in Advanced Research Computing) and ACM (Association for Computing Machinery) – PEARC is the go-to conference for anyone interested in keeping up to date with the latest in research computing
ACCESS (Advanced Cyberinfrastructure Coordination Ecosystem : Services and Support) – Funded and supported by the National Science Foundation to provide no-cost access to US national research computing infrastructure
ask.CI (ask Cyberinfrastructure) : My personal favorite source to go look for answers to specially complex research computing questions
Software Carpentry : A an exhaustive collections of educational resources and hands-on examples of scientific software and their applications
Today, as we stand on the cusp of the AI revolution in academic science, the role of research computing is more critical than ever. AI promises to transform all aspects of the scientific workflow, from Knowledge Assimilation to Discovery (ref. Edition 1). However, integrating AI into research workflows presents unique challenges, including a highly fragmented and ever-changing tech stack (ref. Edition 2) . Research computing professionals, with their deep understanding of both the technical and practical aspects of academic research, emerge as invaluable allies in this journey. By equipping these professionals with AI-centric tools and tailored training the path to widespread AI adoption in science becomes not just smoother but significantly accelerated.