In this webcast/podcast, host and Caltech Affiliate Director of AI Programs Nicholas Beaudoin talks with special guest Dr. Matthew Graham co-PI and Project Scientist for the Zwicky Transient Facility (ZTF) at Caltech—a revolutionary sky survey capturing hundreds of thousands of cosmic events each night. Dr. Graham brings deep expertise in the computational and statistical challenges of large-scale astronomy, applying machine learning to phenomena like supermassive black holes and time-series analysis. Beyond the stars, we’ll explore how the lessons learned from big data ingestion, real-time AI inferencing, and reinforcement learning in astronomy are offering valuable insights for industry—from scalable AI deployment to intelligent decision systems.
Welcome to the Making AI Possible Podcast—your new monthly deep dive into the latest breakthroughs in artificial intelligence and how they’re shaping the world around us. Produced at Caltech in Pasadena, California, this series features in-depth conversations with the people driving AI innovation forward.
This podcast series features the latest AI advancements with some of the brightest minds in the field, such as groundbreaking research from AI industry leaders, labs here on campus, and the Jet Propulsion Laboratory (JPL), which Caltech manages for NASA. Discover how cutting-edge research is being applied to transform and streamline healthcare, energy, manufacturing, and finance. Tune in to discover how the latest research becomes transformative technology.
Dr. Matthew Graham, Research Professor of Astronomy at the California Institute of Technology received his MA in Physics from the University of Oxford and his PhD in Astronomy from the University of Central Lancashire in the UK. After a postdoc at Imperial College London, he came to Caltech in 2003, initially as a Senior Postdoctoral Scholar and then transitioning to a Computational Scientist within the Center for Advanced Computing Research. He has been a Member of the Professional Staff at Caltech and in 2017, he became research faculty in astronomy. Matthew has extensive experience in large sky surveys and their computational challenges, particularly the application of machine learning and advanced statistical methodologies to astrophysical problems. Matthew is currently the co-PI and Project Scientist for the Zwicky Transient Facility (ZTF), the first of a next generation of time-domain sky surveys producing hundreds of thousands of public transient alerts per night. He also has ongoing research projects on real-time low latency inferencing— real-time AI at scale —the application of reinforcement learning to optimize follow-up observations of short lived phenomena, the development of neural differential models for modeling black holes, and the functional analysis modeling of multivariate time series. ♦
As Caltech CTME's Affiliate Director of AI Programs, Nicholas Beaudoin intersects strategic program development with hands-on curriculum design, positioning AI/ML education programs at the forefront of technological transformation. Leading the AI programs at Caltech's Center for Technology & Management Education, Nicholas' focus is on delivering impactful learning experiences tailored to a diverse clientele, including private and public sectors, as well as government and non-profit organizations