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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:20240101T000000
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DTSTART;TZID=Asia/Kolkata:20251104T133000
DTEND;TZID=Asia/Kolkata:20251104T144500
DTSTAMP:20251013T054632Z
CREATED:20251013T054632Z
LAST-MODIFIED:20251013T054632Z
UID:84607-1762263000-1762267500@www.ashoka.edu.in
SUMMARY:Psychology Seminar Series: Critical and Sociocultural Perspectives in Psychology
DESCRIPTION:Abstract: The idea “mindless crowds” has long dominated classical psychology and much of our public understanding for over a century. This imagination reduced collective gatherings to irrational\, dangerous\, and easily manipulated masses. Such views\, rooted in colonial and elitist thought\, not only pathologized public gatherings but also dismissed their potential for collective joy\, social identity\, and social transformation. In this talk\, I revisit and challenge this reductionist notion and attempt to shift the lens from “mindless crowds” to communities. I share ethnographic findings from public gathering at Deekshabhumi\, Nagpur to highlight how collective participation at Deekshabhumi embodies identity change\, critical consciousness\, and the anti-caste vision of Indian society.   \nAbout the Speaker: Yashpal Jogdand is an Associate Professor of Psychology in the Department of Humanities and Social Sciences\, Indian Institute of Technology Delhi\, India. His research examines the issues of prejudice\, stereotyping\, humiliation\, leadership\, caste/casteism\, and coping/resistance. He serves on the editorial boards of British Journal of Social Psychology\, Asian Journal of Social Psychology\, and Journal of Social & Political Psychology. He is also serving as Associate Editor and Book Review Editor of the J-Caste (Caste – A Global Journal on Social Exclusion). He is a recipient of the Young Psychologist Award by the National Academy of Psychology India (NAOP) and his recent publications include edited special issue of J-Caste on ‘Caste and Psychology’. 
URL:https://www.ashoka.edu.in/event/psychology-seminar-series-critical-and-sociocultural-perspectives-in-psychology/
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20251104T133000
DTEND;TZID=Asia/Kolkata:20251104T144500
DTSTAMP:20251029T014646Z
CREATED:20251029T013220Z
LAST-MODIFIED:20251029T014646Z
UID:85709-1762263000-1762267500@www.ashoka.edu.in
SUMMARY:Learning Human Preferences: From Clicks to Conversations
DESCRIPTION:Abstract- People routinely reveal their preferences online\, e.g.\, when choosing search results\, videos\, or products. Such data is used by algorithms to learn human tastes. Recently\, curated datasets of human preferences have been used to fine-tune language models\, substantially improving their alignment with human intent. These successes raise a natural question: can recommender systems learn more effectively from comparisons rather than ratings? The talk will trace a path from basic models of choice behaviour to new frameworks for recommender systems. The main focus will be on our theoretical result showing that personalised recommendations can be learned efficiently from comparison data\, despite the underlying optimisation problem being nonconvex. I will then describe a bandit formulation that addresses the classical exploration-exploitation trade-off in a novel way. Finally\, I’ll share empirical insights motivating richer models of human choice. I will conclude by arguing that learning from human preferences is key to building interactive AI systems that reliably serve human needs. \nBio- Suryanarayana Sankagiri is a postdoctoral researcher at EPFL\, Switzerland\, in the Information and Network Dynamics Laboratory. He obtained his B.Tech. in Electrical Engineering from IIT Bombay in 2016\, and his M.S. and Ph.D. in Electrical and Computer Engineering from the University of Illinois Urbana-Champaign in 2018 and 2022. During his Ph.D.\, he worked on the design and analysis of network protocols—ranging from message-passing algorithms for graph clustering\, to consensus mechanisms in blockchains\, to pricing protocols for payment channel networks. At EPFL\, his research focuses on recommender systems that learn from comparisons and choices\, designing new algorithms as well as models that better capture human behaviour. More broadly\, his interests lie in understanding modern human-in-the-loop intelligent systems. \nHere is a zoom link for online aattendees: https://zoom.us/j/92550826231?pwd=w0KQ9NmqB3DAHxOnlWkYNXUchUbvzA.1
URL:https://www.ashoka.edu.in/event/learning-human-preferences-from-clicks-to-conversations/
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DTSTART;TZID=Asia/Kolkata:20251104T140000
DTEND;TZID=Asia/Kolkata:20251104T150000
DTSTAMP:20251031T023732Z
CREATED:20251031T023732Z
LAST-MODIFIED:20251031T023732Z
UID:85928-1762264800-1762268400@www.ashoka.edu.in
SUMMARY:Mathematics Colloquium
DESCRIPTION:Dear All\, \nThe Department of Mathematics invites you to the Colloquium ​on November 04\, 2025. \nTitle: â€‹Skew left braces and solutions of the Yang-Baxter Equation \n​Abstract: â€‹I am planning to present a mostly pedagogical treatment of a very recently introduced concept​ called skew left brace. It was invented in​ connection with solutions of the Yang-Baxter equation​ (or equivalently\, the braid relation or the first reidemeister move). I’ll indicate this connection​ and mention some recent developments on the topic with adequate details. To satisfy curiosity\,​ if any\, an algebraic structure (G\, +\, â—¦) is said to be a skew left brace if (G\, +) and (G\, â—¦) are​ groups\, and + and â—¦ speak to each other as follows: a â—¦ (b + c) = a â—¦ b − a + a â—¦ c for all​ a\, b\, c ∈ G. For any group (G\, +)\, (G\, +\, +) is obviously a skew left brace. An easy check reveals​ that (G\, +\, +op) is also skew left brace\, where +op denotes the opposite operation of + on G​ (that is\, a +op b := b + a for all a\, b ∈ G). \n​We look forward to having you with us. 
URL:https://www.ashoka.edu.in/event/mathematics-colloquium/
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