BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//ARNI - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://arni-institute.org
X-WR-CALDESC:Events for ARNI
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20270314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20271107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260424T150000
DTEND;TZID=America/New_York:20260424T163000
DTSTAMP:20260418T104509
CREATED:20260406T154309Z
LAST-MODIFIED:20260406T154309Z
UID:2430-1777042800-1777048200@arni-institute.org
SUMMARY:ARNI Distinguished Seminar Series: Ellie Pavlick (Brown University)
DESCRIPTION:Ellie Pavlick \n(Assistant Professor of Computer Science and Linguistics\, Brown University and Director\, NSF Institute on Interaction for AI Assistants (ARIA)) \nLocation: ZI Kavli Auditorium 9th Floor\nTime: 3:00pm \nTitle: (How) Does AI Think? \nAbstract: The increasingly human-like behavior of AI has led to a fascination with ascribing it human-like internal properties — notions like thinking\, understanding\, and reasoning. In this talk\, I will take a step back and discuss a range of results from the past several years of interpretability which present an increasingly consistent view of AI’s internal processing. Specifically\, I will discuss how AI represents a surprising amount of internal structure\, and yet remains primarily idiosyncratic and context-sensitive. I use the opportunity to talk about the philosophical nature of human-AI comparison–when such analogies are fruitful for scientific and technological progress\, and when they mislead. \nZoom: Upon request @arni@columbia.edu
URL:https://arni-institute.org/event/arni-distinguished-seminar-series-ellie-pavlick-brown-university/
LOCATION:Zuckerman Institute- Kavli Auditorium 9th Fl\, 3227 Broadway\, NY
ORGANIZER;CN="ARNI":MAILTO:arni@columbia.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260427T150000
DTEND;TZID=America/New_York:20260427T160000
DTSTAMP:20260418T104509
CREATED:20260402T193102Z
LAST-MODIFIED:20260402T193102Z
UID:2426-1777302000-1777305600@arni-institute.org
SUMMARY:Speaker: Ziwei (Sara) Gong - ARNI Language and Vision Working Group
DESCRIPTION:Title: Decoding Human Emotions: From Psychological Theories to Multimodal NLP Models\nAbstract: Understanding and modeling human emotions is essential for natural language processing (NLP) applications\, from conversational AI to mental health assessment. This talk explores the intersection of emotion theory\, dataset development\, and multimodal machine learning\, highlighting key challenges and innovations in emotion recognition. We discuss the alignment of psychological emotion frameworks with computational models\, strategies for improving multimodal emotion recognition\, and advances in self-supervised learning for low-resource languages. Additionally\, we examine how multimodal signals enhance model performance and interpretability.
URL:https://arni-institute.org/event/speaker-ziwei-sara-gong-arni-language-and-vision-working-group/
LOCATION:Virtual
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260511T150000
DTEND;TZID=America/New_York:20260511T160000
DTSTAMP:20260418T104509
CREATED:20260402T192942Z
LAST-MODIFIED:20260414T131131Z
UID:2425-1778511600-1778515200@arni-institute.org
SUMMARY:Speaker: Hubert Banville\, Meta – ARNI Frontier Models for Neuroscience and Behavior Working Group
DESCRIPTION:Hubert Banville\, Meta\n\nTitle: A foundation model of vision\, audition\, and language for in-silico neuroscience\n\nAbstract: Cognitive neuroscience is fragmented into specialized models\, each tailored to specific experimental paradigms\, hence preventing a unified model of cognition in the human brain. Here\, we introduce TRIBE v2\, a tri-modal (video\, audio and language) foundation model capable of predicting human brain activity in a variety of naturalistic and experimental conditions. Leveraging a unified dataset of over 1\,000 hours of fMRI across 720 subjects\, we demonstrate that our model accurately predicts high-resolution brain responses for novel stimuli\, tasks and subjects\, superseding traditional linear encoding models\, delivering several-fold improvements in accuracy. Critically\, TRIBE v2 enables in silico experimentation: tested on seminal visual and neuro-linguistic paradigms\, it recovers a variety of results established by decades of empirical research. Finally\, by extracting interpretable latent features\, TRIBE v2 reveals the fine-grained topography of multisensory integration. These results establish artificial intelligence as a unifying framework for exploring the functional organization of the human brain. We will be hosting Hubert Banville from Meta who will discuss their latest TRIBE fMRI foundation model.
URL:https://arni-institute.org/event/speaker-tbd-arni-frontier-models-for-neuroscience-and-behavior-working-group/
LOCATION:Virtual
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260512T130000
DTEND;TZID=America/New_York:20260512T190000
DTSTAMP:20260418T104509
CREATED:20260327T171344Z
LAST-MODIFIED:20260327T171344Z
UID:2415-1778590800-1778612400@arni-institute.org
SUMMARY:Memory\, Neuroscience and AI: Zuckerman Institute’s Local Circuits Symposium
DESCRIPTION:Register Here! \nHow are memories formed\, organized\, and used to guide behavior? And what can artificial intelligence teach us about how the brain remembers? \nJoin faculty and early-career researchers from across Columbia for the Local Circuits symposium\, exploring the science of memory across biological and artificial systems. Talks will span systems and cognitive neuroscience\, machine learning\, and theoretical modeling\, examining how brain circuits encode and retrieve memories and how AI is helping researchers probe these processes in new ways. \nPart of the Zuckerman Institute’s Local Circuits series\, this symposium brings together researchers from across the university to spark collaboration around mind\, brain\, and behavior. \nAll Columbia ID holders are welcome. Registration is required. \nPresented by the Alan Kanzer Center for Cognition and Reasoning \nOpening Remarks:\nAngela V. Olinto\, Provost of the University; Professor of Astronomy and of Physics\, Columbia University \nSpeakers include:\nChris Baldassano\, PhD\, Associate Professor of Psychology\, Columbia University\nChristine Denny\, PhD\, Associate Professor of Clinical Neurobiology (in Psychiatry)\, Columbia University Irving Medical Center\nStefano Fusi\, PhD\, Professor of Neuroscience\, Principal Investigator in the Zuckerman Institute\, Columbia University\nScott Small\, MD\, Boris and Rose Katz Professor of Neurology\, Director of the Alzheimer’s Disease Research Center\, Columbia University Irving Medical Center\nKim Stachenfeld\, PhD\, Senior Research Scientist at Google DeepMind in NYC and Adjunct Assistant Professor at the Center for Theoretical Neuroscience\, Columbia University\nRichard Zemel\, PhD\, Trianthe Dakolias Professor of Engineering and Applied Science; Professor of Computer Science; Director of the NSF AI Institute for Artificial and Natural Intelligence (ARNI)\, Columbia University \nModerator:\nDaphna Shohamy\, PhD\, Kavli Professor of Brain Science; Director of the Zuckerman Institute; Co-director of the Kavli Institute for Brain Science\, Columbia University
URL:https://arni-institute.org/event/memory-neuroscience-and-ai-zuckerman-institutes-local-circuits-symposium/
LOCATION:Zuckerman Institute- Kavli Auditorium 9th Fl\, 3227 Broadway\, NY
ORGANIZER;CN="Zuckerman Institute":MAILTO:events@zi.columbia.edu
END:VEVENT
END:VCALENDAR