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X-ORIGINAL-URL:https://www.ashoka.edu.in
X-WR-CALDESC:Events for Ashoka University
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TZID:Asia/Kolkata
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260508T100000
DTEND;TZID=Asia/Kolkata:20260508T110000
DTSTAMP:20260506T071209Z
CREATED:20260506T032929Z
LAST-MODIFIED:20260506T071209Z
UID:92997-1778234400-1778238000@www.ashoka.edu.in
SUMMARY:ARCHITECTURES OF SURVIVAL
DESCRIPTION:Dear All\, \nThe Department of Visual Arts invites you to a capstone thesis presentation by Nylaa Ahmad\, a History major with a minor in Visual Arts\, supervised by Professor Latika Gupta. \nTitled “Architectures of Survival: The Sacred Object\, Contested Space\, and the Cultural Biography of Madin Sahib Shrine\, Srinagar\,” the thesis takes the locked door of Madin Sahib shrine as its central provocation and argues that the sacredness of a Kashmiri Sufi shrine is not a condition that can be administratively revoked. It proposes that sacred value is biographical\, accumulated through six centuries of patronage\, architectural elaboration\, sectarian contestation\, and communal memory and that administrative closure is one chapter in that biography\, not the final one. \nBased on fieldwork at Madin Sahib\, research in the J&K Archives\, and primary sources including Persian and Sanskrit chronicles\, ASI records\, and INTACH documentation\, the thesis is located at the intersection of art history\, Islamic material culture\, and critical heritage studies. \nDate: 8th May\, Friday \nTime: 10:00 AM-11:00 AM \nZoom Link: https://zoom.us/j/94569212493?pwd=5PjOW74RfZbw2zKfB667walm0EVR1S.1 \nOpen to all \n  \nWe look forward to your active participation in the presentation. \nwarm regards\, \nVisual Arts Department
URL:https://www.ashoka.edu.in/event/architectures-of-survival/
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260508T110000
DTEND;TZID=Asia/Kolkata:20260508T120000
DTSTAMP:20260506T071119Z
CREATED:20260506T071119Z
LAST-MODIFIED:20260506T071119Z
UID:93007-1778238000-1778241600@www.ashoka.edu.in
SUMMARY:From The Horse’s Mouth: The Folk Artist As Author
DESCRIPTION:Dear All\, \nThe Department of Visual Arts invites you to a capstone thesis presentation by Mihika Kulkarni\, a Philosophy major with a minor in Visual Arts\, supervised by Srinivas Aditya Mopidevi.  \nTitled “From The Horse’s Mouth: The Folk Artist As Author\,”  the thesis examines how the category of the “folk” is constructed within cultural discourse through assumptions of anonymity\, suggesting a lack of artistic self-consciousness. Combining close textual analysis with exhibition and curatorial analysis\, it studies how institutions\, as well as exhibitions continue to produce and circulate particular understandings of folk and artisanal practices. It identifies major digressions from this trend through the exploration of projects by Dr. Jyotindra Jain and Annapurna Garimella. Finally\, it attempts to argue that artistic subjectivity and reflexive agency have not been absent from folk traditions\, but have often been obscured by the frameworks through which the “folk” is institutionally written and represented.  \nDate: Friday\, 8th May \nTime: 11:00 AM-12:00 PM \nVenue: https://zoom.us/j/94569212493?pwd=5PjOW74RfZbw2zKfB667walm0EVR1S.1 \n  \nWe look forward to you active participation in the presentation. \nwarm regards\, \nVisual Arts Department
URL:https://www.ashoka.edu.in/event/from-the-horses-mouth-the-folk-artist-as-author/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260508T160000
DTEND;TZID=Asia/Kolkata:20260508T170000
DTSTAMP:20260508T102157Z
CREATED:20260504T044827Z
LAST-MODIFIED:20260508T102157Z
UID:92598-1778256000-1778259600@www.ashoka.edu.in
SUMMARY:Noise estimation of SDE from a single data trajectory - Purba Das
DESCRIPTION:Colloquium announcement\nNoise estimation of SDE from a single data trajectory\nPurba Das \nKing’s College London \n \n\nAbstract: We propose a data-driven framework for model discovery of stochastic differential equations (SDEs) from a single trajectory\, without requiring the ergodicity or stationary assumption on the underlying continuous process. By combining (stochastic) Taylor expansions with Girsanov transformations\, and using the drift function’s initial value as input\, we construct drift estimators while simultaneously recovering the model noise. This drift is unique up to the fixed underlying Brownian sample path\, in line with pathwise unique Rough-Smooth decomposition (Ananova-Cont 2017). This allows us to recover the underlying P-Brownian motion increments for the observer path ω. Building on these estimators\, we introduce the first stochastic Sparse Identification of Stochastic Differential Equation (SSISDE) algorithm\, capable of identifying the governing SDE dynamics from a single observed trajectory without requiring ergodicity or stationarity. To validate the proposed approach\, we conduct numerical experiments with both linear and quadratic drift–diffusion functions. Among these\, the Black–Scholes SDE is included as a representative case of a system that does not satisfy ergodicity or stationarity. If time permits\, we will talk about the extension of these results in the context of pathwise Föllmer SDE. \nAbout the speaker: Purba Das is a Lecturer in Financial Mathematics in the Department of Mathematics\, King’s College London. Before that\, she was a Byrne Research Assistant Professor of Mathematics at the University of Michigan (2022-2023). Purba completed her DPhil in Mathematical Institute at the University of Oxford under the supervision of Professor Rama Cont (Oct. 2018- July 2022). Previously Purba received her Master’s degree in Applied Mathematics from Chennai Mathematical Institute (2016-2018)\, and Bachelor’s degree in Mathematics and Computer Science from Chennai Mathematical Institute (2013-2016). \n\nDate: Friday\, May 08\, 2026Time: 4:00 PM – 5:00 PM\nVenue: TBAEmail: scdlds@ashoka.edu.inZoom link: https://zoom.us/j/91705656549?pwd=fbDOvSjhOro5dedw0TCbhOPgb93dbW.1
URL:https://www.ashoka.edu.in/event/scdlds-coll16/
ORGANIZER;CN="SCDLDS":MAILTO:ashoka-cdlds@ashoka.edu.in
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260508T160000
DTEND;TZID=Asia/Kolkata:20260508T170000
DTSTAMP:20260507T235920Z
CREATED:20260507T232649Z
LAST-MODIFIED:20260507T235920Z
UID:93044-1778256000-1778259600@www.ashoka.edu.in
SUMMARY:Noise estimation of SDE from a single data Trajectory
DESCRIPTION:
URL:https://www.ashoka.edu.in/event/noise-estimation-of-sde-from-a-single-data-trajectory/
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