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UID:20251109T203856EST-83140C4SSn@132.216.98.100
DTSTAMP:20251110T013856Z
DESCRIPTION:JOINT EBOH/CRM SEMINAR\n	Bios Seminar Series Fall 2025\n	\n	Sudipt
 o Banerjee\, PhD\n\nProfessor\, Department of Biostatistics\n	Fielding Scho
 ol of Public Health | UCLA\n\nNOTE: Meet & Greet Prof Sudipto Banerjee fro
 m 3-3:30pm in Room 1140\n\nWHEN: Friday\, November 21\, 2025\, from 3:30 t
 o 4:30 p.m.\n	WHERE: Hybrid | 2001 º£½Ç¾«Æ·ºÚÁÏ College Avenue\, Rm 1140\; Zoom\n
 	NOTE: Sudipto Banerjee will be presenting in-person at SPGH \n	 \n\nAbstrac
 t\n\nI will share my perspectives on the significant paradigm shift taking
  place in data analysis with the advent of AI technologies. This rapidly e
 volving field offers substantial intellectual space for statistical theory
  and methods to not only co-exist with other disciplines within computer s
 cience and machine learning\, but also play a crucial role in advancing da
 ta analysis and probabilistic inference at unprecedented scales. I will el
 ucidate three ideas that will synthesize into an artificially intelligent 
 inferential system. The first is 'amortized Bayesian inference' that consi
 ders training and calculating posterior distributions using generative AI.
  The second is Bayesian transfer learning for scaling Inference to massive
  datasets. The third is Bayesian predictive stacking that delivers exact s
 imulation-based inference without resorting to expensive iterative methods
  such as Markov chain Monte Carlo. I will base my talk on a case study tha
 t is a part of the University of California Los Angeles (UCLA) Physical Ac
 tivity and Sustainable Transportation Approaches (PASTA-LA) and is primari
 ly concerned with learning about a subject's metabolic levels as a functio
 n of their mobility attributes and other health attributes.\n\n\n	Speaker B
 io\n\nPlease visit website: https://ph.ucla.edu/about/faculty-staff-direct
 ory/sudipto-banerjee\n
DTSTART:20251121T203000Z
DTEND:20251121T213000Z
SUMMARY:Artificially Intelligent Geospatial Systems: A Case Study in Energe
 tics for Mobile Health Data
URL:/spgh/channels/event/artificially-intelligent-geos
 patial-systems-case-study-energetics-mobile-health-data-368717
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