BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CMSA - ECPv6.17.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://cmsa.fas.harvard.edu
X-WR-CALDESC:Events for CMSA
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:20260903T090000
DTEND;TZID=America/New_York:20260904T170000
DTSTAMP:20260825T143144Z
CREATED:20260217T174509Z
LAST-MODIFIED:20260825T143144Z
UID:10003846-1788426000-1788541200@cmsa.fas.harvard.edu
SUMMARY:Big Data Conference 2026
DESCRIPTION:Big Data Conference 2026 \nDates: Sep. 3–4\, 2026 \nLocation: Harvard University CMSA\, 20 Garden Street\, Cambridge MA & via Zoom \nThe Big Data Conference features speakers from the Harvard community as well as scholars from across the globe\, with talks focusing on computer science\, statistics\, math and physics\, and economics. \nRegister to attend in person \nRegister for Zoom Webinar \n  \nConfirmed Speakers \n\nSueYeon Chung\, Harvard\nBailey Flanigan\, MIT\nSergey Ovchinnikov\, MIT\nAriel Procaccia\, Harvard\nAdit Radhakrishnan\, MIT\nAndrew Sutherland\, MIT\nChris Wiggins\, Columbia\nRex Ying\, Yale\nWei Zhou\, Harvard\n\n  \nOrganizers \n\nMichael Desai\, Harvard\nMichael R. Douglas\, CMSA\nYannai Gonczarowski\, Harvard\nMelanie Weber\, Harvard\n\n  \n  \nThursday\, Sep. 3\, 2026 \n8:45–9:10 am\nBreakfast \n9:10–9:15 am\nIntroductions \n9:15–10:15 am\nRex Ying\, Yale \n10:15–10:30 am\nBreak \n10:30–11:30 am\nAdit Radhakrishnan\, MIT\nToward universal steering and monitoring of AI models\nAbstract: Artificial intelligence (AI) models contain much of human knowledge. Understanding the representation of this knowledge will lead to improvements in model capabilities and safeguards. Building on advances in feature learning\, we developed an approach for extracting linear representations of semantic notions or concepts in AI models. We showed how these representations enabled model steering\, through which we exposed vulnerabilities and improved model capabilities. We demonstrated that concept representations were transferable across languages and enabled multiconcept steering. Across hundreds of concepts\, we found that larger models were more steerable and that steering improved model capabilities beyond prompting. We showed that concept representations were more effective for monitoring misaligned content than for using judge models. Our results illustrate the power of internal representations for advancing AI safety and model capabilities. \n11:30 am–12:45 pm\nLunch \n12:45–1:45 pm\nAndrew Sutherland\, MIT\nCrowdsourcing mathematical databases\nAbstract: The L-functions and Modular Forms Database (LMFDB) is one of the largest online repositories of mathematical research data. It contains comprehensive catalogs of mathematical objects that arise in the context of the Langlands program\, including number fields\, elliptic curves\, modular forms\, and higher-dimensional analogs of these objects. In cooperation with the Foundation for Science and AI Research (SAIR)\, we recently ran a competition aimed at solving the inverse Galois problem over Q in degree 24 (IGP24). This goal was achieved by collecting more than 50 million candidate number fields submitted by more than 100 teams\, including examples that realize all 25\,000 transitive permutation groups of degree 24 as Galois groups. AI tools and computer algebra systems played a central role in this project\, both in building the infrastructure to run the contest and in enhancing the capabilities of participants. \n1:45–2:00 pm\nBreak \n2:00–3:00 pm\nBailey Flanigan\, MIT\nAlgorithmic Tools for Trading Off Sortition Ideals\nAbstract: Citizens’ assemblies and other deliberative minipublics — representative groups of everyday people convened to deliberate on a policy issue and then make recommendations — are now used by governments around the world. Choosing who sits on these panels is the problem of sortition: randomly selecting a small group of citizens that represents the broader population. Sortition has been the subject of substantial computer science research in recent years\, and the resulting algorithms are now widely used in practice. This talk will describe the key challenges that arise in the practice of sortition\, and the algorithmic tools that have been developed to navigate them optimally. \n3:00–3:15 pm\nBreak \n3:15–4:15 pm\nChris Wiggins\, Columbia\nPrescriptive Learning at Scale: Applied and Deployed Decision-Making\nAbstract: Many applications in health and industry require making decisions while learning how the world responds to them: e.g.\, which article to recommend\, which treatment to assign\, or when to show a paywall. This problem is prescriptive\, what to do rather than what is true. Statistical decision theory has taken up the problem repeatedly since Neyman’s interwar work; recent decades have brought a new wave of results\, motivated in large part by the opportunity to make and evaluate decisions at scale online. I will highlight a thread of 21st-century results running through adaptive experimentation\, contextual bandits\, and off-policy evaluation: they combine advances in supervised learning with fundamental ideas from statistical sampling\, and now shape digital products\, from content recommendation to marketing\, as well as adaptive interventions in health. \n  \nFriday\, Sep. 4\, 2026 \n8:45–9:15 am\nBreakfast \n9:15–10:15 am\nAriel Procaccia\, Harvard\nNo Generation Without Representation\nAbstract: AI systems and democratic processes are confronting similar challenges around representation. I examine two related questions that cut across both domains. First\, how can AI enable democratic processes that handle vast spaces of opinions or statements while ensuring proportional representation of a population’s views? Second\, when AI systems themselves provide normative guidance\, whose viewpoints do they reflect\, and can we make this precise? Drawing on social choice theory\, I present formal frameworks and algorithms for both problems\, showing that meaningful representation guarantees are feasible and practical. \n10:15–10:30 am\nBreak \n10:30–11:30 am\nWei Zhou\, Harvard\nBiobank-scale genetic discovery: from association testing to global meta-analysis\nAbstract: Biobanks linking genomic data with electronic health records provide unprecedented opportunities for genetic discovery for complex human diseases\, but they also pose analytical challenges that extend well beyond sample size. Within a biobank\, association studies must account for population structure and relatedness\, highly unbalanced case–control ratios\, rare genetic variants\, longitudinal and censored outcomes\, and the computational demands of analyzing hundreds of thousands of individuals and millions of genetic variants. Across biobanks\, additional challenges arise from differences in ancestry\, phenotype definitions\, recruitment strategies and genetic effects.In this talk\, I will discuss statistical and computational methods developed to address these challenges at successive stages of biobank analysis. These include scalable generalized linear mixed models for binary traits\, survival mixed models for censored time-to-event outcomes\, and gene- and region-based tests that aggregate rare variants. I will describe statistical approximations and computational strategies that make these analyses feasible at biobank scale while maintaining calibration in the presence of relatedness and highly unbalanced phenotypes. I will then introduce the Global Biobank Meta-analysis Initiative (GBMI) and describe how genetic evidence can be combined across biobanks without sharing individual-level data. Examples from GBMI will illustrate how combining evidence across biobanks can increase statistical power through larger sample sizes and broaden genetic discovery through greater ancestral diversity. \n11:30 am–12:45 pm\nLunch \n12:45–1:45 pm\nSergey Ovchinnikov\, MIT \n1:45–2:00 pm\nBreak \n2:00–3:00 pm\nSueYeon Chung\, Harvard \n\n 
URL:https://cmsa.fas.harvard.edu/event/bigdata_2026/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Big Data Conference,Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Big-Data-2026_ad.crop_.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260908T090000
DTEND;TZID=America/New_York:20260911T170000
DTSTAMP:20260825T140015Z
CREATED:20260217T174544Z
LAST-MODIFIED:20260825T140015Z
UID:10003847-1788858000-1789146000@cmsa.fas.harvard.edu
SUMMARY:The Geometry of Machine Learning 2026
DESCRIPTION:The Geometry of Machine Learning 2026 \nDates: September 8–11\, 2026 \nLocation: Harvard CMSA\, Room G10\, 20 Garden Street\, Cambridge MA 02138 & via Zoom Webinar \nRegister to attend in person \nRegister for Zoom Webinar \nLarge language models are presently\, and will increasingly\, be complemented by other dimensions of intelligence: formal verification and energy-based optimizers\, becoming parts of larger ecosystems. Can AIs reason geometrically and can we use geometry to reveal how data is currently processed in NNs? Can AIs reveal the geometry of mathematics\, as well as studying geometry as a subject within math. This conference is intended to continue the discussion of these topics. \nConfirmed Speakers: \n\nNada Amin\, Harvard\nRandall Balestriero\, Brown\nMichael Brenner\, Harvard and Google\nBennet Chow\, UCSD\nSurya Ganguli\, Stanford\nBoris Hanin\, Princeton\nRoi Holtzman\, Oxford\nRobert Koirala\, UCSD\nDmitry Krotov\, Dynamical Mind\nSlava Krushkal\, Virginia\nJared Duker Lichtman\, Stanford\nMike Mulligan\, UCR\, Logical Intelligence\nLuca Pesce\, Harvard\nGabriel Poesia\, U Michigan\nMathew Vanherreweghe\, Logical Intelligence\nSean Welleck\, CMU (via Zoom)\nMattiew Wyart\, JHU\n\nOrganizers: Michael R. Douglas (CMSA) and Mike Freedman (CMSA) \n  \nSchedule \n\n\n\nTuesday\, Sep. 8\, 2026\n\n\n8:15–8:45 am\nBreakfast\n\n\n8:45–9:30 am\nTalk\n\n\n9:45–10:30 am\nTalk\n\n\n10:30–11:00 am\nBreak\n\n\n11:00–11:45 am\nTalk\n\n\n12:00–12:45 pm\nTalk\n\n\nWednesday\, Sep. 9\, 2026\n\n\n8:15–8:45 am\nBreakfast\n\n\n8:45–9:30 am\nTalk\n\n\n9:45–10:30 am\nTalk\n\n\n10:30–11:00 am\nBreak\n\n\n11:00–11:45 am\nTalk\n\n\n12:00–12:45 pm\nTalk\n\n\nThursday\, Sep. 10\, 2026\n\n\n8:15–8:45 am\nBreakfast\n\n\n8:45–9:30 am\nTalk\n\n\n9:45–10:30 am\nTalk\n\n\n10:30–11:00 am\nBreak\n\n\n11:00–11:45 am\nTalk\n\n\n12:00–12:45 pm\nTalk\n\n\nFriday\, Sep. 11\, 2026\n\n\n8:15–8:45 am\nBreakfast\n\n\n8:45–9:30 am\nTalk\n\n\n9:45–10:30 am\nTalk\n\n\n10:30–11:00 am\nBreak\n\n\n11:00–11:45 am\nTalk\n\n\n12:00–12:45 pm\nTalk\n\n\n\n  \n  \nSupport provided by Logical Intelligence. \n \n  \n 
URL:https://cmsa.fas.harvard.edu/event/gml_2026/
LOCATION:CMSA 20 Garden Street Cambridge\, Massachusetts 02138 United States
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/GML2026-Poster.4.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260909T140000
DTEND;TZID=America/New_York:20260909T150000
DTSTAMP:20260729T181924Z
CREATED:20260729T181924Z
LAST-MODIFIED:20260729T181924Z
UID:10003893-1788962400-1788966000@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_9926/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260916T140000
DTEND;TZID=America/New_York:20260916T150000
DTSTAMP:20260729T193738Z
CREATED:20260729T193738Z
LAST-MODIFIED:20260729T193738Z
UID:10004009-1789567200-1789570800@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_91626/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260923T140000
DTEND;TZID=America/New_York:20260923T150000
DTSTAMP:20260729T193809Z
CREATED:20260729T193809Z
LAST-MODIFIED:20260729T193809Z
UID:10004010-1790172000-1790175600@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_92326/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260930T140000
DTEND;TZID=America/New_York:20260930T150000
DTSTAMP:20260729T193839Z
CREATED:20260729T193839Z
LAST-MODIFIED:20260729T193839Z
UID:10004011-1790776800-1790780400@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_93026/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261007T140000
DTEND;TZID=America/New_York:20261007T150000
DTSTAMP:20260729T193913Z
CREATED:20260729T193913Z
LAST-MODIFIED:20260729T193913Z
UID:10004012-1791381600-1791385200@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_10726/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261014T140000
DTEND;TZID=America/New_York:20261014T150000
DTSTAMP:20260729T193937Z
CREATED:20260729T193937Z
LAST-MODIFIED:20260729T193937Z
UID:10004013-1791986400-1791990000@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_101426/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261021T140000
DTEND;TZID=America/New_York:20261021T150000
DTSTAMP:20260729T194008Z
CREATED:20260729T194008Z
LAST-MODIFIED:20260729T194008Z
UID:10004014-1792591200-1792594800@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_102126/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261028T140000
DTEND;TZID=America/New_York:20261028T150000
DTSTAMP:20260729T194034Z
CREATED:20260729T194034Z
LAST-MODIFIED:20260729T194034Z
UID:10004015-1793196000-1793199600@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_102826/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261104T140000
DTEND;TZID=America/New_York:20261104T150000
DTSTAMP:20260729T194242Z
CREATED:20260729T194242Z
LAST-MODIFIED:20260729T194242Z
UID:10004016-1793800800-1793804400@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_11426/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261118T140000
DTEND;TZID=America/New_York:20261118T150000
DTSTAMP:20260729T194502Z
CREATED:20260729T194502Z
LAST-MODIFIED:20260729T194502Z
UID:10004017-1795010400-1795014000@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_111826/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261125T140000
DTEND;TZID=America/New_York:20261125T150000
DTSTAMP:20260729T194526Z
CREATED:20260729T194526Z
LAST-MODIFIED:20260729T194526Z
UID:10004018-1795615200-1795618800@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_112526/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261202T140000
DTEND;TZID=America/New_York:20261202T150000
DTSTAMP:20260729T194554Z
CREATED:20260729T194554Z
LAST-MODIFIED:20260729T194554Z
UID:10004019-1796220000-1796223600@cmsa.fas.harvard.edu
SUMMARY:New Technologies in Mathematics Seminar
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: tba
URL:https://cmsa.fas.harvard.edu/event/newtech_12226/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
END:VEVENT
END:VCALENDAR