BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//White City Innovation District - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:White City Innovation District
X-ORIGINAL-URL:https://www.whitecityinnovationdistrict.org.uk
X-WR-CALDESC:Events for White City Innovation District
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:20231029T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:20240331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:20241027T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:20251026T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20240912T133000
DTEND;TZID=Europe/London:20240912T143000
DTSTAMP:20260410T111608
CREATED:20240830T105704Z
LAST-MODIFIED:20240830T110821Z
UID:2972-1726147800-1726151400@www.whitecityinnovationdistrict.org.uk
SUMMARY:I-X Seminar: Rough Analysis and Anomalous Streams with Professor Terry Lyons
DESCRIPTION:Hybrid event: link to join online via Teams. \nFor on-site attendees\, a networking lunch will be provided at the end of the seminar.  \nSeminar description: \nMulti modal streams of information arise naturally in many engineering contexts. Rough path theory is an area of mathematics that fuses the control theory of Sussmann\, Brockett and Fleiss with the analysis of Young to form a calculus that can efficiently describe the interaction and evolution of complex oscillatory systems. \nOne mathematical tool coming from this theory is the signature of a stream. Using software packages like RoughPy one can reduce an interval of streamed data to a relatively parsimonious vector representation known as the signature that is independent of the intensity of sampling in the stream. RoughPy provides tools for working with streams. The signature feature has many significant mathematics properties and has emerged as a suitable starting point in a range of practical challenges\, leading to a number of prize winning and innovative outcomes. \nOne challenge in streamed data is to start with a corpus of ‘normal’ streamed data and recognise that a new stream is not plausibly from the same family defined by the corpus. One advantage of the theoretical perspectives is that one can design methods\, such as this outlier detection methodology that respects natural invariants of streamed data. For example\, outlier scores should produce the same outcomes if \n\nthe corpus and the data are rescaled (e.g. from Fahrenheit to centigrade)\na channel is duplicated or not\nthe streams are pre or post pended by common meta data.\n\nA signature based method that achieves all these invariants has shown value in several real world applications. \nSpeaker Bio\nProfessor Terry Lyons is the Wallis Professor Emeritus and Professor of Mathematics at the University of Oxford and visiting Professor at Imperial College London. He is currently PI of the DataSıg program (primarily funded by EPSRC)\, and of the complementary research programme CIMDA-Oxford. He was a founding member (2007) of\, and then Director (2011-2015) of\, the Oxford Man Institute of Quantitative Finance; he was the Director of the Wales Institute of Mathematical and Computational Sciences (WIMCS; 2008-2011). He came to Oxford in 2000 having previously been Professor of Mathematics at Imperial College London (1993-2000)\, and before that he held the Colin Maclaurin Chair at Edinburgh (1985-93). \nProfessor Lyons’s long-term research interests are all focused on Rough Paths\, Stochastic Analysis\, and applications to the use of data science with streamed data particularly to finance\, healthcare\, human computer interfaces and more generally to the summarising of large complex data. More specifically\, his interests are in developing mathematical tools such as neural rough differential equations and software tools like RoughPy that deal with mathematical operations like shuffle product and logarithm for elements of the tensor algebra. These tools\, and rough analysis more generally\, can be used to effectively model and describe high dimensional systems that exhibit randomness as well as the complex multimodal data streams that arise in human activity. Professor Lyons is involved in a wide range of problems from pure mathematical ones to questions of efficient numerical calculation. DataSıg is a project that bridges from the fundamental mathematics to application contexts where novel techniques for analysing streamed data have potential to contribute value; these contexts include mental health\, action recognition\, astronomy\, cybersecurity\, … The CIMDA-Oxford research partnership aims to address a broader range of mathematical and engineering challenges arising from multi-dimensional big data. \n 
URL:https://www.whitecityinnovationdistrict.org.uk/event/i-x-seminar-rough-analysis-and-anomalous-streams-with-professor-terry-lyons/
LOCATION:I-HUB\, Imperial White City Campus\, 84 Wood Lane\, London\, W12 0BZ\, United Kingdom
ATTACH;FMTTYPE=image/png:https://www.whitecityinnovationdistrict.org.uk/wp-content/uploads/sites/10/2024/08/Professor-Terry-Lyons-e1725016094996.png
END:VEVENT
END:VCALENDAR