Euro-Par 2024 | İlkay Altıntaş | International European Conference on Parallel and Distributed Computing İlkay AltıntaşEuro-par

İlkay Altıntaş

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 has reached more than a million learners across the globe. 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. Dr. Altıntaş received a Ph.D. degree from the University of Amsterdam in the Netherlands. For a list of the more than 25 journal papers and 100 refereed scientific articles that Dr. Altıntaş has published, visit her Google Scholar page.

Bridging the Data Gaps to Democratize AI in Science, Education and Society

The democratization of Artificial Intelligence (AI) necessitates an ecosystem where data and research infrastructure are seamlessly integrated and universally accessible. This talk overviews the imperative of bridging the gaps between these components through robust services, facilitating an inclusive AI landscape that empowers diverse research communities and domains. The National Data Platform (NDP) aims to lower the barriers to entry for AI research and applications through an integrated services approach to streamline AI workflows, from data acquisition to model deployment. This approach underscores the importance of open, extensible, and equitable systems in driving forward the capabilities of AI, ultimately contributing to the resolution of grand scientific and societal challenges. Through examining real case studies leveraging open data platforms and scalable research infrastructure, the talk will highlight the role of composable systems and services in NDP to catalyze a platform to empower users from all backgrounds to engage in meaningful research, learning, and discovery. 

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