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Speaker:Dragan Radulović Date & Time: Tuesday Oct 7th, 2pm Location: HDSI Multipurpose Room 123, 1st floor Title: A New Paradigm for the Analysis of Large Text Files Talk Abstract: The problem is as follows: a large text file containing information on thousands of individuals serves as the input. The output is a simple yes-or-no prediction. For example, […]
Speaker: Anupam Datta Date & Time: Friday Oct 17th, 10am Location: HDSI Multipurpose Room 123, 1st floor Talk title: What is your Agent’s GPA? Subtitle: Toward Trustworthy Data Agents Abstract: We introduce the Agent GPA (Goal-Plan-Action) framework: an evaluationparadig m based on an agent’s operational loop of setting goals, devising plans, and executing actions. The framework includes […]
Speaker: Tianhao Wang Date & Time: Monday Nov 10th, 2pm Location: HDSI Multipurpose Room 123, 1st floor Title: Adaptive Optimizers: From Structured Preconditioners to Adaptive Geometry Abstract: Adaptive optimizers such as Adam and Shampoo are workhorses of modern machine learning, enabling efficient training of large-scale models across architectures and domains. In this talk, we will present a unified framework […]
Please note this event is only open to postdocs and graduate students and will be held in Stanford CA. For more information, including how to apply, and other registration links please visit: https://datascience.stanford.edu/events/workshop/rising-stars-data-science Workshop Overview The Rising Stars in Data Science workshop, hosted November 11-12 by Stanford University in collaboration with the University of California, San Diego, […]
The next TILOS-HDSI seminar will be Wednesday, November 12 at 11am PST with Adam Oberman (McGill University). The title is AI Safety Theory: The Missing Middle Ground. Talk Information Speaker: Adam Oberman (McGill University) Date & Time: Wednesday, November 12 @ 11am PST Venue: HDSI 123 Abstract: Over the past few years, the capabilities of generative artificial intelligence (AI) systems have advanced rapidly. Along with the […]
TITLE Design, Measure, Interpret: Foundation Models in the Scientific Loop ABSTRACT "As foundation models become powerful scientific priors, a central question emerges: how can they drive the full cycle of discovery—from designing experiments to interpreting results? This talk presents a probabilistic framework that unites experiment design and inverse problems under a common foundation model. I […]
Talk Details TBA
Speaker: Ila Fiete Date & Time: Mon Dec 8th, 2:00pm NEW LOCATION: Jacobs Hall, Qualcomm Conference Center B, 1st Floor Abstract: Modular and hierarchical structures are ubiquitous in the brain, and the decomposition of tasks into invariant subfactors of variation are arguably the basis for robust, efficient learning, compositional generalization, and lack of forgetting. In this talk, I […]
Talk Time: Mon Jan 12th, 2026 | 2:00pm Location: Data Science Building 1st Floor, Room 123 Talk Abstract As we interact with the world around us, we experience a constant stream of sensory inputs, and must generate a constant stream of behavioral actions. What makes brains more than simple input-output machines is their capacity to […]
Title: A geometric model for anatomic objects targeted for statistical analysis Speaker: Stephen Pizer, Kenan Professor of Computer Science, University of North Carolina at Chapel Hill Abstract: A novel representation called the evolutionary s-rep represents anatomic objects by encompassing an unusually rich collection of geometric features, image intensity based features, genetic features, etc. It can […]