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DTSTART;TZID=Australia/Sydney:20241213T140000
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DTSTAMP:20260416T065654
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SUMMARY:Veridical data science and alignment in medical AI
DESCRIPTION:Professor Bin Yu\, Statistics\, EECS\, Center for Computational Biology\, Simons Institute for the Theory of Computing\, UC Berkeley \n\n\n\n \n\n\n\n\n\n\n\n\n\n\n\n\nAbout the seminar\n\n\n\nAlignment and trust are crucial for the successful integration of AI in healthcare including digital twin projects\, a field involving diverse stakeholders such as medical personnel\, patients\, administrators\, public health officials\, and taxpayers\, all of whom influence how these concepts are defined. This talk presents a series of collaborative medical case studies where AI algorithms progressively become\, from transparency to more opaque thus with increasing difficulty of alignment assessment. These range from tree-based methods for trauma diagnosis\, to LLM-based emergency department co-pilot\, and mechanistic circuits for structured data extraction from pathology reports. They are guided by Veridical Data Science (VDS) principles—Predictability\, Computability\, and Stability (PCS)—for the goal of building trust and interpretability\, enabling doctors to assess alignment. The talk concludes with a discussion on applying VDS to digital twins and medical foundation models and next steps for evaluating AI algorithm alignment in healthcare. \n\n\n\n\n\n\n\n\n\nAbout Bin Yu\n\n\n\nBin Yu is CDSS Chancellor’s Distinguished Professor in Statistics\, EECS\, and Computational Biology\, and Scientific Advisor at the Simons Institute for the Theory of Computing\,  all at UC Berkeley. Her research focuses on the practice and theory of statistical machine learning\, veridical data science\, and solving interdisciplinary data problems in neuroscience\, genomics\, and precision medicine. She and her team have developed algorithms such as iterative random forests (iRF)\, stability-driven NMF\, and adaptive wavelet distillation (AWD) from deep learning models. She is a member of the National Academy of Sciences and of the American Academy of Arts and Sciences. She was a Guggenheim Fellow\, IMS President\, and delivered the IMS Rietz and Wald Lectures and Distinguished Achievement Award and Lecture (formerly Fisher Lecture) of COPSS. She holds an Honorary Doctorate from The University of Lausanne
URL:https://spds.sydney.edu.au/event/veridical-data-science-and-alignment-in-medical-ai/
LOCATION:Lecture Theatre 173\, Carslaw Building (F07.01.173)
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DTSTART;TZID=Australia/Sydney:20241216T130000
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DTSTAMP:20260416T065654
CREATED:20241128T003907Z
LAST-MODIFIED:20250110T033323Z
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SUMMARY:Incorporating experimental medicine into single-cell multi-omics
DESCRIPTION:Special Statistical Bioinformatics Seminar\n\n\n\n\n\nDr Jacqueline Siu\, Kennedy Institute of Rheumatology\, University of Oxford \n\n\n\n \n\n\n\n\n\nAbout the seminar: Coordinated global efforts to create a comprehensive map of the human body using single-cell technologies has opened up avenues in computational biology and AI. However\, there remains a pressing need to increase the data diversity from the ancestral diversity of participants to increasing the types of immune perturbations captured. This talk will focus on incorporating single-cell multi-omics to different experimental medicine approaches–such as deceased organ donors\, vaccine and xenogeneic-antigen challenge trials–in order to understand healthy immune responses in lymphoid organs. \n\n\n\nAbout the speaker: Jacqueline Siu received her PhD at the University of Cambridge where she combined bioinformatics and experimental medicine to understand the function and differentiation of homeostatic human B cells in matched secondary lymphoid organs. To extend her interest in human tissue immunity especially after perturbation\, Jacqueline joined the labs of Professor Mark Coles/ Professor Calliope Dendrou as a postdoctoral fellow\, where she explored the influenza vaccine response of human axillary lymph nodes. In 2023\, Jacqueline received the Wellcome Trust Early Career award to continue her interest in integrating human challenge models and single-cell genomics to understand early responding human B cells and their impact on long-lived antibodies.
URL:https://spds.sydney.edu.au/event/statistical-bioinformatics-seminar-judith-david-coffey-invited-speaker-special-seminar/
LOCATION:Mackenzie Room\, Level 6\, Charles Perkins Centre\, University of Sydney\, Johns Hopkins Drive\, University of Sydney\, NSW\, 2006\, Australia
ATTACH;FMTTYPE=image/jpeg:https://spds.sydney.edu.au/wp-content/uploads/2024/10/AdobeStock_552748421.jpg
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