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Dr. Frederic P Poitevin (SLAC): ” From Data Deluge to Self-Steering Experiments at LCLS-II”
Speaker: Dr. Frederic P Poitevin (SLAC)
Title: From Data Deluge to Self-Steering Experiments at LCLS-II
Video: Click here to view
Abstract: X-ray free-electron lasers are entering a regime where experiments can generate data faster than scientists can inspect, interpret, and act on it by hand. At LCLS-II, this challenge is also an opportunity: high repetition rates can transform experiments from sparse human-guided searches into statistically principled sampling of large, high-dimensional scientific spaces.
In this talk, I will describe how the Machine Learning and Computer Vision group at LCLS is building infrastructure for this transition. Our goal is to connect streaming detector data, online dimensionality reduction, physics-aware machine learning, and automated decision-making into workflows that can monitor experiments in real time and eventually steer data collection while the experiment is running. Together, these efforts point toward a new experimental paradigm in which instruments, analysis pipelines, and scientific hypotheses are coupled in a closed loop, enabling more reliable operation and deeper exploration of molecular structure and dynamics at XFEL facilities.
Bio: Frédéric Poitevin, Ph.D., is a Staff Scientist in LCLS Data Systems at SLAC National Accelerator Laboratory, where he leads the Machine Learning and Computer Vision group and serves as Head of AI for Science and Operations. He is a computational structural biologist whose work bridges theory, experiment, and scalable data analysis to study the structural dynamics of macromolecules. His group develops machine learning, computer vision, and automation methods for XFEL experiments, including online data reduction, experiment steering, detector calibration, and physics-aware reconstruction for X-ray and cryo-EM imaging. Before joining SLAC, he trained in chemistry and bioinformatics at École Normale Supérieure and Institut Pasteur in Paris, followed by postdoctoral work at CEA-Saclay and Stanford.
