Chief Data Science Officer, San Diego Supercomputer Center, California, US.

“Societal Computing: Designing AI-Ready Ecosystems for a More Resilient Future“

Wednesday 18 February 2026

Abstract

Societal Computing reframes computing as an innovation engine for collective resilience and impact —linking cutting edge science, data, models, AI systems, and communities to solve complex challenges at scale. In this talk, I will outline a vision for building AI-ready data ecosystems that empower researchers, educators, policymakers, and the public to work from a shared digital fabric. Drawing on lessons from wildfire science, resilient agriculture, public health, and education, I will describe how structured collaboration, national cyberinfrastructure, and responsible AI create a new kind of societal operating system. Through examples from the National Data Platform and the Wildfire Science and Technology Commons, I will show how convergence research becomes actionable when we bridge data stewardship, computational workflows, multi-modal AI, and community-centered design. The talk will highlight emerging opportunities for building trustworthy, inclusive, and durable socio-technical systems that enable science and society to learn, adapt, and innovate together.

Bio

Dr. İlkay Altıntaş, a research scientist at the University of California San Diego, is the Chief Data Science Officer of the San Diego Supercomputer Center as well as a Founding Fellow of the Halıcıoğlu Data Science Institute. She is the Founding Director of the Workflows for Data Science (WorDS) Center of Excellence and the WIFIRE Lab. The WoRDS Center specializes in the development of methods, cyberinfrastructure, and workflows for computational data science and its translation to practical applications. The WIFIRE Lab is focused on artificial intelligence methods for an all-hazards knowledge cyberinfrastructure, becoming a management layer from the data collection to modeling efforts, and has achieved significant success in helping to manage wildfires. Since joining SDSC in 2001, she has been a principal investigator and a technical leader in a wide range of cross-disciplinary projects. With a specialty in scientific workflows, she leads collaborative teams to deliver impactful results through making computational data science work more reusable, programmable, scalable, and reproducible. Her work has been applied to many scientific and societal domains including bioinformatics, geoinformatics, high-energy physics, multi-scale biomedical science, smart cities, and smart manufacturing. She is also a popular MOOC instructor in the field of “big” data science and reached out to more than a million learners across any populated continent. Among the awards she has received are the 2015 IEEE TCSC Award for Excellence in Scalable Computing for Early Career Researchers and the 2017 ACM SIGHPC Emerging Woman Leader in Technical Computing Award. Ilkay received a Ph.D. degree from the University of Amsterdam in the Netherlands.

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