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New York Scientific Data Summit (NYSDS) is a premier annual conference that brings together researchers and thought leaders from academia, national labs and industry to exchange ideas and foster collaboration focused on data-driven science and technology. Co-hosted by Brookhaven National Laboratory and the Institute for Advanced Computational Science (IACS) at Stony Brook University, NYSDS 2025 will take place on September 11-12, 2025, in the SUNY Global Center in New York City.
NYSDS 2025 will spotlight artificial intelligence (AI), machine learning (ML) and robotics - fields currently at a pivotal point with transformative impacts on science and technology. From accelerating computationally demanding simulations to discerning signals from noisy data, AI/ML has become an integral part of the scientific workflows. Despite many advances, challenges remain to ensure that AI/ML applications are reliable, explainable and trustworthy.
Robotics, a growing field that couples AI with physically actuated mechanical bodies, has seen increased interest in areas spanning science, technology and manufacturing. The need for real-time decision-making and control, along with the intricate morphology of robots, makes robotics an intriguing application of AI, advanced computing and optimization.
This NYSDS 2025 is open to the public. To be eligible to attend, all participants must register online by August 30, 2025. For questions or assistance with registering, please contact the Summit Coordinator.
Register here.
| Abstract: Astronomers slowly made sense of the cosmos by following the stars night after night. I suggest we examine human identity in a similar way. Let's observe the words individuals use to describe themselves day after day. In this presentation, I will introduce ipseology - a new approach to studying human selves. Ipseology is the systematic, empirical study of ipseity: selfhood, individuality and the elements of identity. The primary idea is that we can learn a lot about people from their self-authored self-descriptions - especially if we follow their revisions over time. I will discuss results from sampling millions of social media bios over more than a decade and present new approaches for observation in the Post-API age. Bio: Dr. Jason Jeffrey Jones is a computational social scientist whose expertise includes online experiments, social networks, high-throughput text analysis and machine learning. He is interested in humans' perceptions of themselves and the developing role of artificial intelligence in society. Dr. Jones is the director of CSSERG (pronounced sea surge): the Computational Social Science of Emerging Realities Group. CSSERG is a team of scholars committed to cross-disciplinary collaboration, united by common computational methodologies and always with eyes on the near future. CSSERG has studied the effectiveness of virtual reality in evoking empathy, the dynamics of gender stereotypes in language over decades and temporal trends in personally expressed identity. This seminar will take place in person and online (zoom link below): Join Zoom Meeting https://stonybrook.zoom.us/j/ Meeting ID: 936 8660 9778 Passcode: 638699 |