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BEGIN:VEVENT
DTSTAMP:20261006T214340Z
DTSTART;VALUE=DATE-TIME:20251124T130000
DTEND;VALUE=DATE-TIME:20251124T140000
SUMMARY:WCPM: Mark Girolami\, University of Cambridge
TZID:Europe/London
UID:20251124-8ac672c598f027f20198f08e2f411401@warwick.ac.uk
CREATED:20251104T092000Z
DESCRIPTION:Location: Lecture Theatre 0.04 IMC Networking Lunch: The Rech
 arge Room\, next to Lecture Theatre 004\, from 12:30pm - 1pm. Title: Sta
 tistical Finite Element Methods Abstract: The finite element method (FEM
 ) is one of the great triumphs of applied mathematics\, numerical analys
 is and software development. Recent developments in sensor and signallin
 g technologies enable the phenomenological study of complex natural and 
 physical systems. The connection between sensor data and FEM has been re
 stricted to solving inverse problems placing unwarranted faith in the fi
 delity of the mathematical description of the system under study. If one
  concedes mis-specification between generative reality and the FEM then 
 a framework to systematically characterise this uncertainty is required.
  This talk will present a statistical construction of the FEM which syst
 ematically blends mathematical description with data observations by end
 owing the Hilbert space of FEM solutions with the additional structure o
 f a Probability Measure. Bio: Professor Mark Girolami is the Sir Kirby L
 aing Professor of Civil Engineering at the University of Cambridge\, whe
 re he also holds the Royal Academy of Engineering Research Chair in Data
 -Centric Engineering. He is a Fellow of Christ’s College\, Cambridge\, a
 nd currently serves as Chief Scientist of The Alan Turing Institute\, th
 e UK’s national institute for data science and artificial intelligence. 
 A computational statistician by background\, Professor Girolami’s resear
 ch focuses on computational statistics\, Bayesian methodology\, probabil
 istic numerics\, and their applications across engineering and the natur
 al sciences. His projects span areas such as data-centric engineering\, 
 computational statistical inference for engineering and security\, multi
 modal data analysis\, digital twins\, and urban systems modeling. He als
 o plays a leading role in the Centre for Smart Infrastructure and Constr
 uction as Data Lead. Before his appointment at Cambridge\, Professor Gir
 olami was Chair of Statistics at Imperial College London and one of the 
 founding Executive Directors of The Alan Turing Institute\, where he lat
 er became Strategic Programme Director and established the Lloyd’s Regis
 ter Foundation Programme on Data-Centric Engineering. Earlier in his car
 eer\, he spent a decade as a Chartered Engineer at IBM\, before moving f
 ully into academia. His contributions have been widely recognized: he is
  a Fellow of the Royal Academy of Engineering and the Royal Society of E
 dinburgh\, a past EPSRC Advanced and Established Career Fellow\, and rec
 ipient of the Royal Society Wolfson Research Merit Award. In 2023\, he w
 as awarded the Guy Medal in Silver by the Royal Statistical Society. He 
 has also delivered distinguished lectures including the IMS Medallion Le
 cture (2017)\, the Bernoulli Society Forum Lecture (2017)\, and the BCS 
 & IET Turing Talk (2020). Professor Girolami is also active in publishin
 g and editorial leadership: he is Editor-in-Chief of Statistics and Comp
 uting and the founding Editor-in-Chief of Data-Centric Engineering (Camb
 ridge University Press). Alongside his research\, he is committed to tea
 ching and mentoring\, leading courses in Mathematical Methods and Comput
 ational Statistics and Machine Learning\, and co-authoring the widely us
 ed textbook A First Course in Machine Learning.
LOCATION:Lecture Theatre 0.04 IMC
CATEGORIES:WCPM
LAST-MODIFIED:20251104T092000Z
ORGANIZER;CN=Jin Kang:
END:VEVENT
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