Convergence Research at the Digital Continuum
Session Chair: Rafael Ferreira da Silva (ORNL)
University of California San Diego
This talk will address the growing use of machine learning and AI in science and convergence research applications, driven by advancements in data and computing. It will introduce a novel approach that employs adaptable systems for collaborative research at the intersection of scientific computing, AI, and remote sensing. Highlighting the first working example of an integrated infrastructure that combines Expanse supercomputer with Nautilus GPU cluster and Sage edge AI, the talk will also overview case studies that blend data from various sources, including edge sensors and AI, in the context of wildfire management. In addition, it will overview our approach approach to problem-solving that integrates knowledge, methods, and expertise from different disciplines to form a comprehensive framework for addressing complex societal challenges.
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.
Embodied Agents as Scientific Assistants
Session Chair: Rosa Filgueira (University of St Andrews)
Ian T. Foster
University of Chicago and Argonne National Laboratory
The integration of embodied agents in the scientific domain presents unprecedented opportunities and challenges. In this talk I delve into the transformative potential of these agents as next-generation scientific assistants. I begin by defining embodied agents — computational entities that interact with the world through physical bodies or representations, often leveraging sensorimotor experiences to learn and act. I then explore three primary facets of their integration:
- Cognitive Collaboration: How embodied agents, with their machine learning and data-processing capabilities, complement the cognitive processes of human scientists, offering real-time data analysis, hypothesis generation, and even experimental design suggestions.
- Physical Interaction: The unique advantage of embodied agents lies in their ability to physically engage with the scientific environment, be it a laboratory or field setting. I will highlight applications ranging from precision tasks in bio-labs and advanced simulations on supercomputers.
- Ethical and Philosophical Implications: As with all technological advancements, the rise of embodied agents introduces pertinent questions about their ethical use, the preservation of human intuition in science, and the possible redefinition of scientific discovery in an age where machines can potentially theorize and validate.
Concluding, I invite participants to envision a future where human scientists and embodied agents collaborate seamlessly, fostering an era of accelerated scientific discoveries and broader horizons of understanding.
Bio. Ian Foster is the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago, and Senior Scientist and Distinguished Fellow, and director of the Data Science and Learning Division, at Argonne National Laboratory. He has a BSc degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science. His research is in distributed, parallel, and data-intensive computing technologies, and their applications to scientific problems. He is a fellow of the AAAS, ACM, BCS, and IEEE, and has received the BCS Lovelace Medal; IEEE Babbage, Goode, and Kanai awards; and ACM/IEEE Ken Kennedy award.
From Data to Impact
Session Chair: George A. Papadopoulos (University of Cyprus)
The National Innovation Centre for Data (NICD) was created by the UK government and Newcastle University to generate economic and societal benefit from data. Most commercial and public sector organisations are drowning in data. They can often see that this could help them gain insights into their business, optimise existing operations, and launch new data-driven products and services. However, few organisations have the skills needed to realise the potential of data to transform their business. Since 2019, NICD has been addressing this challenge by transferring data science and AI skills into organisations. It does this through projects in which its team of data scientists collaborate with staff in the external organisation on a project that addresses a business need within that organisation. To date, it has run 80 successful projects with companies of all sizes, across a wide variety of domains. The talk will explain the systematic way NICD scopes and runs data science projects to ensure that they successfully deliver value to the external organisation. This will be illustrated with a set of case studies. It will end with a checklist of the key points to consider when designing a project to successfully exploit data science and AI.
Bio. Paul Watson FREng FBCS CEng is Director of the UK's National Innovation Centre for Data, Professor of Computer Science at Newcastle University, and a Fellow of the Alan Turing Institute. He began his career at Manchester University before moving to industry to design parallel database servers. In 1995 he joined Newcastle University where his research and teaching has focussed on scalable data engineering. Professor Watson is a Fellow of the Royal Academy of Engineering, a Fellow of the British Computer Society, and a Chartered Engineer. He received the 2014 Microsoft Jim Gray eScience Award.