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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20190819T083000
DTEND;TZID=America/New_York:20190820T164000
DTSTAMP:20260502T021524
CREATED:20230707T174003Z
LAST-MODIFIED:20250328T145128Z
UID:10000116-1566203400-1566319200@cmsa.fas.harvard.edu
SUMMARY:2019 Big Data Conference
DESCRIPTION:On August 19-20\, 2019 the CMSA hosted the fifth annual Conference on Big Data. The Conference will featured many 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. \nThe talks will take place in Science Center Hall D\, 1 Oxford Street. \nVideos can be found in the Youtube playlist.
URL:https://cmsa.fas.harvard.edu/event/2019-big-data-conference/
LOCATION: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-2019-Poster-5-2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20190502T090000
DTEND;TZID=America/New_York:20190505T170000
DTSTAMP:20260502T021524
CREATED:20230715T175235Z
LAST-MODIFIED:20250328T145104Z
UID:10000115-1556787600-1557075600@cmsa.fas.harvard.edu
SUMMARY:Conference on Differential Geometry\, Calabi-Yau theory and General Relativity: A conference in honor of the 70th Birthday of Shing-Tung Yau
DESCRIPTION:On May 2-5\, 2019 the Harvard Mathematics Department hosted a Conference on Differential Geometry\, Calabi-Yau Theory and General Relativity: A conference in honor of the 70th Birthday of Shing-Tung Yau. The conference was held in the  Science Center\, Lecture Hall C.  \nOrganizers:\n\nHorng-Tzer Yau (Harvard)\nWilfried Schmid (Harvard)\nClifford Taubes (Harvard)\nCumrun Vafa (Harvard)\n\nSpeakers:\n\nLydia Bieri\, University of Michigan\nTristan Collins\, MIT\nSimon Donaldson\, Imperial College\nFan Chung Graham\, UC San Diego\nNigel Hitchin\, Oxford University\nJun Li\, Stanford University\nKefeng Liu\, UCLA\nChiu-Chu Melissa Liu\, Columbia University\nAlina Marian\, Northeastern University\nXenia de la Ossa\, Oxford University\nDuong H. Phong\, Columbia University\nRichard Schoen\, UC Irvine\nAndrew Strominger\, Harvard University\nNike Sun\, MIT\nClifford Taubes\, Harvard University\nChuu-Lian Terng\, UC Irvine\nValentino Tosatti\, Northwestern University\nKaren Uhlenbeck\, University of Texas\nCumrun Vafa\, Harvard University\nMu Tao Wang\, Columbia University\nEdward Witten\, IAS\nStephen Yau\, Tsinghua University\, P.R. China
URL:https://cmsa.fas.harvard.edu/event/conference-on-differential-geometry-calabi-yau-theory-and-general-relativity-a-conference-in-honor-of-the-70th-birthday-of-shing-tung-yau/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Yau-2-2-791x1024-2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20190429T090000
DTEND;TZID=America/New_York:20190501T170000
DTSTAMP:20260502T021524
CREATED:20230715T174721Z
LAST-MODIFIED:20250304T214254Z
UID:10000114-1556528400-1556730000@cmsa.fas.harvard.edu
SUMMARY:Conference on Algebraic Geometry\, Representation theory and Mathematical Physics
DESCRIPTION:From April 29 to May 1\, 2019 the CMSA will be hosting a Conference on Algebraic Geometry\, Representation theory and Mathematical Physics. This workshop is organized by Bong Lian (Brandeis) and Artan Sheshmani (CMSA) . The workshop will be held in room G10 of the CMSA\, located at 20 Garden Street\, Cambridge\, MA.   \nVideos\nSpeakers: \n\nDan Abramovich\, Brown\nRoman Bezrukavnikov\, MIT\nFedor Bogomolov\, NYU\nQile Chen\, Boston College\nDawei Chen\, Boston College\nAlexander Efimov\, Moscow\nPavel Etingof\, MIT\nMaksym Fedorchuk\, Boston College\nDennis Gaitsgory\, Harvard\nAmin Gholampour\, Maryland\nBrendan Hassett\, Brown\nLudmil Katzarkov\, Miami & Moscow\nSi Li\, Tsinghua\nAndrei Negut\, MIT\nYuri Tschinkel\, NYU\nWei Zhang\, MIT\n\n  \nMonday\, April 29 \n\n\n\nTime\nSpeaker\nTitle/Abstract\n\n\n8:30 – 9:00am\nBreakfast\n\n\n\n9:00 – 10:00am\nWei Zhang\, MIT\nTitle: The arithmetic fundamental lemma for diagonal cycles \nAbstract: I’ll recall the Gross–Zagier theorem and a high dimensional generalization\, the arithmetic Gan-Gross-Prasad conjecture\, which relates the height pairing of arithmetic diagonal cycles on certain shimura varieties to the first order derivative of certain L-functions.  The arithmetic fundamental lemma conjecture arises from the relative trace formula approach to this conjecture. I will recall the statement of the arithmetic fundamental lemma and outline a proof.\n\n\n10:00 – 10:30am\nBreak\n\n\n\n10:30 – 11:30am\nYuri Tschinkel\, NYU\nTitle: Equivariant birational geometry and modular symbols \nAbstract: We introduce new invariants in equivariant birational geometry and study their relation to modular symbols and cohomology of arithmetic groups (joint with M. Kontsevich and V. Pestun).\n\n\n11:30 – 1:30pm\nLunch\n\n\n\n1:30 – 2:30pm\nAlexander Efimov\, Moscow\nTitle: Torsionness for regulators of canonical extensions \nAbstract: I will sketch a generalization of the results of Iyer and Simpson arXiv:0707.0372 to the general case of a normal-crossings divisor at infinity.\n\n\n2:30 – 3:00pm\nBreak\n\n\n\n3:00 – 4:00pm\nAmin Gholampour\, Maryland\nTitle: Euler Characteristics of punctual quot schemes on threefolds \nAbstract: Let F be a homological dimension 1 torsion free sheaf on a nonsingular quasi-projective threefold. The first cohomology of the derived dual of F is a 1-dimension sheaf G supported on the singular locus of F. We prove a wall-crossing formula relating the generating series of the Euler characteristics of Quot(F\, n) and Quot(G\,n)\, where Quot(-\,n) denotes the quot scheme of length n quotients. We will use this relation in studying the Euler characteristics of the moduli spaces of stable torsion free sheaves on nonsingular projective threefolds. This is a joint work with Martijn Kool.\n\n\n4:00 – 4:30pm\nBreak\n\n\n\n4:30 – 5:30pm\nMaksym Fedorchuck\, BC\nTitle:  Stability of one-parameter families of weighted hypersurfaces \nAbstract:  We define a notion of stability for fibrations over a curve with generic fibers being weighted hypersurfaces (in some weighted projective space) generalizing Kollár’s stability for families of hypersurfaces in a projective space.  The stability depends on a choice of an effective line bundle on the parameter space of weighted hypersurfaces and different choices pick out different birational model of the total space of the fibration. I will describe enumerative geometry that goes into understanding these stability conditions\, and\, if time permits\, examples where this machinery can be used to produce birational models with good properties.  Joint work with Hamid Ahmadinezhad and Igor Krylov.\n\n\n\n  \nTuesday\, April 30 \n\n\n\nTime\nSpeaker\nTitle/Abstract\n\n\n8:30 – 9:00am\nBreakfast\n\n\n\n9:00 – 10:00am\nBrendan Hassett\, Brown\nTitle: Rationality for geometrically rational threefolds \nAbstract: We consider rationality questions for varieties over non-closed fields that become rational over an algebraic closure\, like smooth complete intersections of two quadrics.  (joint with Tschinkel)\n\n\n10:00 – 10:30am\nBreak\n\n\n\n10:30 – 11:30am\nDennis Gaitsgory\, Harvard\nTitle: The Fundamental Local Equivalence in quantum geometric Langlands \nAbstract: The Fundamental Local Equivalence is statement that relates the q-twisted  Whittaker category of the affine Grassmannian for the group G and the category of modules over the Langlands dual “big” quantum group. The non-triviaiity of the statement lies is the fact that the relationship between the group and its  dual is combinatorial\, so to prove the FLE one needs to express both sides in combinatorial terms. In the talk we will indicate the proof of a related statement for the “small” quantum group. The combinatorial link is provided by the category of factorization modules over a certain factorization algebra\, which in itself is a geometric device that concisely encodes the root data.\n\n\n11:30 – 1:00pm\nLunch\n\n\n\n1:00- 2:00pm\nAndrei Negut\, MIT\nTitle: AGT relations in geometric representation theory \nAbstract: I will survey a program that seeks to translate the Alday-Gaiotto-Tachikawa correspondence (between gauge theory on R^4 and conformal field theory) into the language of algebraic geometry. The objects of study become moduli spaces of sheaves on surfaces\, and the goal is to connect them with the W-algebra of type gl_n.\n\n\n2:00 – 2:15pm\nBreak\n\n\n\n2:15 – 3:15pm\nDan Abramovich\, Brown\nTitle: Resolution in characteristic 0 using weighted blowing up \nAbstract: Given a variety $X$\, one wants to blow up the worst singular locus\, show that it gets better\, and iterate until the singularities are resolved. \nExamples such as the whitney umbrella show that this iterative process cannot be done by blowing up smooth loci – it goes into a loop. \nWe show that there is a functorial way to resolve varieties using \emph{weighted} blowings up\, in the stack-theoretic sense. To an embedded variety $X \subset Y$ one functorially assigns an invariant $(a_1\,\ldots\,a_k)$\, and a center locally of the form $(x_1^{a_1} \, \ldots \, x_k^{a_k})$\, whose stack-theoretic weighted blowing up has strictly smaller invariant under the lexicographic order. \nThis is joint work with Michael Tëmkin (Jerusalem) and Jaroslaw Wlodarczyk (Purdue)\, a side product of our work on functorial semistable reduction. A similar result was discovered by G. Marzo and M. McQuillan.\n\n\n3:15 – 3:30pm\nBreak\n\n\n\n3:30 – 4:30pm\nFedor Bogomolov\, NYU\nTitle: On the base of a Lagrangian fibration for a compact hyperkahler manifold. \nAbstract: In my talk I will discuss our proof with N. Kurnosov that the base of such fibration for complex projective manifold hyperkahler manifold of dimension $4$ is always a projective plane $P^2$. In fact we show that the base of such fibration can not have a singular point of type $E_8$. It was by the theorem of Matsushita and others that only quotient singularities can occur and if the base is smooth then the it is isomorphic to $P^2$. The absence of other singularities apart from $E_8$ has been already known and we show that $E-8$ can not occur either. Our method can be applied to other types of singularities for the study of  Lagrangian fibrations in higher dimensions More recently similar result was obtained by Huybrechts and Xu.\n\n\n4:30 – 4:45pm\nBreak\n\n\n\n4:45 – 5:45pm\nDawei Chen\, BC\nTitle: Volumes and intersection theory on moduli spaces of Abelian differentials \nAbstract: Computing volumes of moduli spaces has significance in many fields. For instance\, Witten’s conjecture regarding intersection numbers on moduli spaces of Riemann surfaces has a fascinating connection to the Weil-Petersson volume\, which motivated Mirzakhani to give a proof via Teichmueller theory\, hyperbolic geometry\, and symplectic geometry. In this talk I will introduce an analogue of Witten’s intersection numbers on moduli spaces of Abelian differentials to compute the Masur-Veech volumes induced by the flat metric associated with Abelian differentials. This is joint work with Moeller\, Sauvaget\, and Zagier (arXiv:1901.01785).\n\n\n\n  \nWednesday\, May 1 \n\n\n\nTime\nSpeaker\nTitle/Abstract\n\n\n8:30 – 9:00am\nBreakfast\n\n\n\n9:00 – 10:00am\nPavel Etingof\, MIT\nTitle: Short star-products for filtered quantizations \nThis is joint work with Eric Rains and Douglas Stryker.\n\n\n10:00 – 10:30am\nBreak\n\n\n\n10:30 – 11:30am\nRoman Bezrukavnikov\, MIT\nTitle: Stability conditions and representation theory \nAbstract: I will recall the concept of real variation of stabilities (introduced in my work with Anno and Mirkovic)\nand its relation to modular Lie algebra representations. I will also address a potential generalization of that picture\nto modular representations of affine Lie algebras related to the classical limit of geometric Langlands duality and its local counterpart.\n\n\n11:30 – 11:45am\nBreak\n\n\n\n11:45 – 12:45pm\nQile Chen\, BC\nTitle: Counting curves in critical locus via logarithmic compactification \nAbstract: An R-map consists of a pre-stable map to possibly non-GIT quotient together with sections of certain spin bundles. The moduli of R-maps are in general non-compact. When the target of R-maps is equipped with a super-potential W with compact critical locus\, using Kiem-Li cosection localization it has been proved by many authors in various settings that the virtual cycle of R-maps can be represented by the cosection localized virtual cycle which is supported on the proper locus consisting of R-maps in the critical locus of W. Though the moduli of R-maps is equipped with a natural torus action by scaling of the spin bundles\, the non-compactness of the R-maps moduli makes such powerful torus action useless. \nIn this talk\, I will introduce a logarithmic compactification of the moduli of R-maps using certain modifications of stable logarithmic maps. The logarithmic moduli space carries a canonical virtual cycle from the logarithmic deformation theory. In the presence of a super-potential with compact critical locus\, it further carries a reduced virtual cycle. We prove that (1) the reduced virtual cycle of the compactification can be represented by the cosection localized virtual cycle; and (2) the difference of the canonical and reduced virtual cycles is another reduced virtual cycle supported along the logarithmic boundary. As an application\, one recovers the Gromov-Witten invariants of the critical locus as the invariants of logarithmic R-maps of its ambient space in an explicit form. The latter can be calculated using the spin torus action. \nThis is a joint work with Felix Janda and Yongbin Ruan.\n\n\n12:45 – 2:30pm\nLunch\n\n\n\n2:30 – 3:30pm\nSi Li\, Tsinghua\nTitle: Semi-infinite Hodge structure: from BCOV theory to Seiberg-Witten geometry \nAbstract: I will explain how the semi-infinite Hodge theory extends Kodaira-Spencer gravity (Bershadsky-Cecotti-Ooguri-Vafa theory of B-twisted closed topological string field theory) into a full solution of Batalin-Vilkovisky master equation. This allows us to formulate quantum B-model via a rigorous BV quantization method and construct integrable hierarchies arising naturally from the background symmetry. In the second part of the talk\, I will explain the recent discovery of the connection between K.Saito’s primitive form and 4d N=2 Seiberg-Witten geometry arising from singularity theory.\n\n\n3:30 – 4:00pm\nBreak\n\n\n\n4:00 – 5:00pm\nLudmil Katzarkov\, Moscow\nTitle: PDE’s non commutative  motives and HMS. \nAbstract: In this talk we will discuss the theory of central manifolds and the new structures in geometry it produces. Application to Bir.  Geometry will be discussed.\n\n\n\n 
URL:https://cmsa.fas.harvard.edu/event/conference-on-algebraic-geometry-representation-theory-and-mathematical-physics/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/algebraic-geo-conference-final-795x1024-1-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20181116T080000
DTEND;TZID=America/New_York:20181117T170000
DTSTAMP:20260502T021524
CREATED:20230715T085736Z
LAST-MODIFIED:20241212T191652Z
UID:10000102-1542355200-1542474000@cmsa.fas.harvard.edu
SUMMARY:Current Developments In Mathematics 2018
DESCRIPTION:Current Developments in Mathematics 2018 Conference. \nFriday\, Nov. 16\, 2018 2:15 pm – 6:00 pm \nSaturday\, Nov. 17\, 2018  9:00 am – 5:00 pm \nHarvard University Science Center\, Hall B \nYoutube Playlist
URL:https://cmsa.fas.harvard.edu/event/current-developments-in-mathematics-2018/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/cdm-2018-poster.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20180823T083000
DTEND;TZID=America/New_York:20180824T163000
DTSTAMP:20260502T021524
CREATED:20230715T083801Z
LAST-MODIFIED:20250415T154139Z
UID:10000086-1535013000-1535128200@cmsa.fas.harvard.edu
SUMMARY:Big Data Conference 2018
DESCRIPTION:On August 23-24\, 2018 the CMSA hosted the fourth annual Conference on Big Data. The Conference featured 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. \nThe talks were held in Science Center Hall B\, 1 Oxford Street. \nSpeakers:  \n\nMohammad Akbarpour\, Stanford\nEmily Breza\, Harvard\nFrancesca Dominici\, Harvard\nChiara Farronato\, Harvard\nKobi Gal\, Ben Gurion\nJonah Kallenbach\, Reverie Labs\nSamuel Kou\, Harvard\nLaura Kreidberg\, Harvard\nDanielle Li\, MIT\nLibby Mishkin\, Uber\nJosh Speagle\, Harvard\nWilliam Stein\, University of Washington\nAlex Teyltelboym\, University of Oxford\nSergiy Verstyuk\, CMSA/Harvard\n\nOrganizers:  \n\nShing-Tung Yau\, William Caspar Graustein Professor of Mathematics\, Harvard University\nScott Duke Kominers\, MBA Class of 1960 Associate Professor\, Harvard Business\nRichard Freeman\, Herbert Ascherman Professor of Economics\, Harvard University\nJun Liu\, Professor of Statistics\, Harvard University\nHorng-Tzer Yau\, Professor of Mathematics\, Harvard University
URL:https://cmsa.fas.harvard.edu/event/2018-big-data-conference-2/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Big Data Conference,Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Big-Data-2018-4.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20180818T083000
DTEND;TZID=America/New_York:20180820T172000
DTSTAMP:20260502T021524
CREATED:20230715T083526Z
LAST-MODIFIED:20250304T213419Z
UID:10000084-1534581000-1534785600@cmsa.fas.harvard.edu
SUMMARY:From Algebraic Geometry to Vision and AI: A Symposium Celebrating the Mathematical Work of David Mumford
DESCRIPTION:On August 18 and 20\, 2018\, the Center of Mathematic Sciences and Applications and the Harvard University Mathematics Department hosted a conference on From Algebraic Geometry to Vision and AI: A Symposium Celebrating the Mathematical Work of David Mumford. The talks took place in Science Center\, Hall B. \nSaturday\, August 18th:  A day of talks on Vision\, AI and brain sciences \nMonday\, August 20th: a day of talks on Math \nSpeakers: \n\nStuart Geman\, Brown\nJanos Kollar\, Princeton\nTai Sing Lee\, CMU\nEmanuele Macri\, Northeastern\nJitendra Malik\, Berkeley / FAIR\nPeter Michor\, University of Vienna\nMichael Miller\, Johns Hopkins\nAaron Pixton\, MIT\nJayant Shah\, Northeastern\nJosh Tenenbaum\, MIT\nBurt Totaro\, UCLA\nAvi Wigderson\, IAS\nYing Nian Wu\, UCLA\nLaurent Younes\, Johns Hopkins\nSong-Chun Zhu\, UCLA\n\nOrganizers:\n\nChing-Li Chai\, University of Pennsylvania\nDavid Gu\, Stony Brook University\nAmnon Neeman\, Australian National University\nMark Nitzberg\, University of California at Berkeley\nYang Wang\, Hong Kong University of Science and Technology\nShing-Tung Yau\, Harvard University\nSong-Chun Zhu\, University of California\, Los Angeles\n\nPublication: \nPure and Applied Mathematics Quarterly\nSpecial Issue: In Honor of David Mumford\nGuest Editors: Ching-Li Chai\, Amnon Neeman \n 
URL:https://cmsa.fas.harvard.edu/event/from-algebraic-geometry-to-vision-and-ai-a-symposium-celebrating-the-mathematical-work-of-david-mumford/
LOCATION:Common Room\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Mumford-3.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20180124T090000
DTEND;TZID=America/New_York:20180125T170000
DTSTAMP:20260502T021524
CREATED:20230717T173945Z
LAST-MODIFIED:20250305T214037Z
UID:10000042-1516784400-1516899600@cmsa.fas.harvard.edu
SUMMARY:Blockchain Conference
DESCRIPTION:On January 24-25\, 2019 the Center of Mathematical Sciences will be hosting a conference on distributed-ledger (blockchain) technology. The conference is intended to cover a broad range of topics\, from abstract mathematical aspects (cryptography\, game theory\, graph theory\, theoretical computer science) to concrete applications (in accounting\, government\, economics\, finance\, management\, medicine). The talks will take place in Science Center\, Hall D. \nhttps://youtu.be/FyKCCutxMYo \nPhotos\n \nSpeakers: \n\nJoseph Abadi\, Princeton University\nBenedikt Bunz\, Stanford University\nJake Cacciapaglia\, Nebula Genomics/Harvard Medical School\nEduardo Castello\, Massachusetts Institute of Technology\nAlisa DiCaprio\, R3\nZhiguo He\, University of Chicago\nSteven Kou\, Boston University\nAnne Lafarre\, Tilburg University\nJacob Leshno\, University of Chicago\nBruce Schneier\, Harvard Kennedy School\nDavid Schwartz\, Ripple\nElaine Shi\, Cornell University/Thunder Research\nHong Wan\, NCSU
URL:https://cmsa.fas.harvard.edu/event/blockchain-conference/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/Blockchain-Final-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170818T154700
DTEND;TZID=America/New_York:20170819T154700
DTSTAMP:20260502T021524
CREATED:20230717T172600Z
LAST-MODIFIED:20250328T144515Z
UID:10000034-1503071220-1503157620@cmsa.fas.harvard.edu
SUMMARY:2017 Big Data Conference
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a conference on Big Data from August 18 – 19\, 2017\, in Hall D of the Science Center at Harvard University.\nThe Big Data Conference features many 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. This is the third conference on Big Data the Center will host as part of our annual events\, and is co-organized by Richard Freeman\, Scott Kominers\, Jun Liu\, Horng-Tzer Yau and Shing-Tung Yau. \nConfirmed Speakers: \n\nMohammad Akbarpour\, Stanford University\nAlbert-László Barabási\, Northeastern University\nNoureddine El Karoui\, University of California\, Berkeley\nRavi Jagadeesan\, Harvard University\nLucas Janson\, Harvard University\nTracy Ke\, University of Chicago\nTze Leung Lai\, Stanford University\nAnnie Liang\, University of Pennsylvania\nMarena Lin\, Harvard University\nNikhil Naik\, Harvard University\nAlex Peysakhovich\, Facebook\nNatesh Pillai\, Harvard University\nJann Spiess\, Harvard University\nBradly Stadie\, Open AI\, University of California\, Berkeley\nZak Stone\, Google\nHau-Tieng Wu\, University of Toronto\nSifan Zhou\, Xiamen University\n\n  \nFollowing the conference\, there will be a two-day workshop from August 20-21. The workshop is organized by Scott Kominers\, and will feature: \n\nJörn Boehnke\, Harvard University\nNikhil Naik\, Harvard University\nBradly Stadie\, Open AI\, University of California\, Berkeley\n\n  \nConference Schedule \nA PDF version of the schedule below can also be downloaded here. \nAugust 18\, Friday (Full day)\n\n\n\nTime\nSpeaker\nTopic\n\n\n8:30 am – 9:00 am\n\nBreakfast\n\n\n9:00 am – 9:40 am\nMohammad Akbarpour \nVideo\nTitle: Information aggregation in overlapping generations and the emergence of experts \nAbstract: We study a model of social learning with “overlapping generations”\, where agents meet others and share data about an underlying state over time. We examine under what conditions the society will produce individuals with precise knowledge about the state of the world. There are two information sharing regimes in our model: Under the full information sharing technology\, individuals exchange the information about their point estimates of an underlying state\, as well as their sources (or the precision of their signals) and update their beliefs by taking a weighted average. Under the limited information sharing technology\, agents only observe the information about the point estimates of those they meet\, and update their beliefs by taking a weighted average\, where weights can depend on the sequence of meetings\, as well as the labels. Our main result shows that\, unlike most social learning settings\, using such linear learning rules do not guide the society (or even a fraction of its members) to learn the truth\, and having access to\, and exploiting knowledge of the precision of a source signal are essential for efficient social learning (joint with Amin Saberi & Ali Shameli).\n\n\n9:40 am – 10:20 am\nLucas Janson \nVideo\nTitle: Model-Free Knockoffs For High-Dimensional Controlled Variable Selection \nAbstract: Many contemporary large-scale applications involve building interpretable models linking a large set of potential covariates to a response in a nonlinear fashion\, such as when the response is binary. Although this modeling problem has been extensively studied\, it remains unclear how to effectively control the fraction of false discoveries even in high-dimensional logistic regression\, not to mention general high-dimensional nonlinear models. To address such a practical problem\, we propose a new framework of model-free knockoffs\, which reads from a different perspective the knockoff procedure (Barber and Candès\, 2015) originally designed for controlling the false discovery rate in linear models. The key innovation of our method is to construct knockoff variables probabilistically instead of geometrically. This enables model-free knockoffs to deal with arbitrary (and unknown) conditional models and any dimensions\, including when the dimensionality p exceeds the sample size n\, while the original knockoffs procedure is constrained to homoscedastic linear models with n greater than or equal to p. Our approach requires the design matrix be random (independent and identically distributed rows) with a covariate distribution that is known\, although we show our procedure to be robust to unknown/estimated distributions. As we require no knowledge/assumptions about the conditional distribution of the response\, we effectively shift the burden of knowledge from the response to the covariates\, in contrast to the canonical model-based approach which assumes a parametric model for the response but very little about the covariates. To our knowledge\, no other procedure solves the controlled variable selection problem in such generality\, but in the restricted settings where competitors exist\, we demonstrate the superior power of knockoffs through simulations. Finally\, we apply our procedure to data from a case-control study of Crohn’s disease in the United Kingdom\, making twice as many discoveries as the original analysis of the same data. \nSlides\n\n\n10:20 am – 10:50 am\n\nBreak\n\n\n10:50 pm – 11:30 pm\nNoureddine El Karoui \nVideo\nTitle: Random matrices and high-dimensional statistics: beyond covariance matrices \nAbstract: Random matrices have played a central role in understanding very important statistical methods linked to covariance matrices (such as Principal Components Analysis\, Canonical Correlation Analysis etc…) for several decades. In this talk\, I’ll show that one can adopt a random-matrix-inspired point of view to understand the performance of other widely used tools in statistics\, such as M-estimators\, and very common methods such as the bootstrap. I will focus on the high-dimensional case\, which captures well the situation of “moderately” difficult statistical problems\, arguably one of the most relevant in practice. In this setting\, I will show that random matrix ideas help upend conventional theoretical thinking (for instance about maximum likelihood methods) and highlight very serious practical problems with resampling methods.\n\n\n11:30 am – 12:10 pm\nNikhil Naik \nVideo\nTitle: Understanding Urban Change with Computer Vision and Street-level Imagery \nAbstract: Which neighborhoods experience physical improvements? In this work\, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the physical appearance of five US cities with economic and demographic data and find three factors that predict neighborhood improvement. First\, neighborhoods that are densely populated by college-educated adults are more likely to experience physical improvements. Second\, neighborhoods with better initial appearances experience\, on average\, larger positive improvements. Third\, neighborhood improvement correlates positively with physical proximity to the central business district and to other physically attractive neighborhoods. Together\, our results illustrate the value of using computer vision methods and street-level imagery to understand the physical dynamics of cities. \n(Joint work with Edward L. Glaeser\, Cesar A. Hidalgo\, Scott Duke Kominers\, and Ramesh Raskar.)\n\n\n12:10 pm – 12:25 pm\nVideo #1 \nVideo #2\nData Science Lightning Talks\n\n\n12:25 pm – 1:30 pm\n\nLunch\n\n\n1:30 pm – 2:10 pm\nTracy Ke \nVideo\nTitle: A new SVD approach to optimal topic estimation \nAbstract: In the probabilistic topic models\, the quantity of interest—a low-rank matrix consisting of topic vectors—is hidden in the text corpus matrix\, masked by noise\, and Singular Value Decomposition (SVD) is a potentially useful tool for learning such a low-rank matrix. However\, the connection between this low-rank matrix and the singular vectors of the text corpus matrix are usually complicated and hard to spell out\, so how to use SVD for learning topic models faces challenges. \nWe overcome the challenge by revealing a surprising insight: there is a low-dimensional simplex structure which can be viewed as a bridge between the low-rank matrix of interest and the SVD of the text corpus matrix\, and which allows us to conveniently reconstruct the former using the latter. Such an insight motivates a new SVD-based approach to learning topic models. \nFor asymptotic analysis\, we show that under a popular topic model (Hofmann\, 1999)\, the convergence rate of the l1-error of our method matches that of the minimax lower bound\, up to a multi-logarithmic term. In showing these results\, we have derived new element-wise bounds on the singular vectors and several large deviation bounds for weakly dependent multinomial data. Our results on the convergence rate and asymptotical minimaxity are new. We have applied our method to two data sets\, Associated Process (AP) and Statistics Literature Abstract (SLA)\, with encouraging results. In particular\, there is a clear simplex structure associated with the SVD of the data matrices\, which largely validates our discovery.\n\n\n2:10 pm – 2:50 pm\nAlbert-László Barabási \nVideo\nTitle: Taming Complexity: From Network Science to Controlling Networks \nAbstract: The ultimate proof of our understanding of biological or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered and natural systems towards a desired state\, we lack a framework to control complex self-organized systems. Here we explore the controllability of an arbitrary complex network\, identifying the set of driver nodes whose time-dependent control can guide the system’s entire dynamics. We apply these tools to several real networks\, unveiling how the network topology determines its controllability. Virtually all technological and biological networks must be able to control their internal processes. Given that\, issues related to control deeply shape the topology and the vulnerability of real systems. Consequently unveiling the control principles of real networks\, the goal of our research\, forces us to address series of fundamental questions pertaining to our understanding of complex systems. \n \n\n\n2:50 pm – 3:20 pm\n\nBreak\n\n\n3:20 pm – 4:00 pm\nMarena Lin \nVideo\nTitle: Optimizing climate variables for human impact studies \nAbstract: Estimates of the relationship between climate variability and socio-economic outcomes are often limited by the spatial resolution of the data. As studies aim to generalize the connection between climate and socio-economic outcomes across countries\, the best available socio-economic data is at the national level (e.g. food production quantities\, the incidence of warfare\, averages of crime incidence\, gender birth ratios). While these statistics may be trusted from government censuses\, the appropriate metric for the corresponding climate or weather for a given year in a country is less obvious. For example\, how do we estimate the temperatures in a country relevant to national food production and therefore food security? We demonstrate that high-resolution spatiotemporal satellite data for vegetation can be used to estimate the weather variables that may be most relevant to food security and related socio-economic outcomes. In particular\, satellite proxies for vegetation over the African continent reflect the seasonal movement of the Intertropical Convergence Zone\, a band of intense convection and rainfall. We also show that agricultural sensitivity to climate variability differs significantly between countries. This work is an example of the ways in which in-situ and satellite-based observations are invaluable to both estimates of future climate variability and to continued monitoring of the earth-human system. We discuss the current state of these records and potential challenges to their continuity.\n\n\n4:00 pm – 4:40 pm\nAlex Peysakhovich\n Title: Building a cooperator \nAbstract: A major goal of modern AI is to construct agents that can perform complex tasks. Much of this work deals with single agent decision problems. However\, agents are rarely alone in the world. In this talk I will discuss how to combine ideas from deep reinforcement learning and game theory to construct artificial agents that can communicate\, collaborate and cooperate in productive positive sum interactions.\n\n\n4:40 pm – 5:20 pm\nTze Leung Lai \nVideo\nTitle: Gradient boosting: Its role in big data analytics\, underlying mathematical theory\, and recent refinements \nAbstract: We begin with a review of the history of gradient boosting\, dating back to the LMS algorithm of Widrow and Hoff in 1960 and culminating in Freund and Schapire’s AdaBoost and Friedman’s gradient boosting and stochastic gradient boosting algorithms in the period 1999-2002 that heralded the big data era. The role played by gradient boosting in big data analytics\, particularly with respect to deep learning\, is then discussed. We also present some recent work on the mathematical theory of gradient boosting\, which has led to some refinements that greatly improves the convergence properties and prediction performance of the methodology.\n\n\n\nAugust 19\, Saturday (Full day)\n\n\n\nTime\nSpeaker\nTopic\n\n\n8:30 am – 9:00 am\n\nBreakfast\n\n\n9:00 am – 9:40 am\nNatesh Pillai \nVideo\nTitle: Accelerating MCMC algorithms for Computationally Intensive Models via Local Approximations \nAbstract: We construct a new framework for accelerating Markov chain Monte Carlo in posterior sampling problems where standard methods are limited by the computational cost of the likelihood\, or of numerical models embedded therein. Our approach introduces local approximations of these models into the Metropolis–Hastings kernel\, borrowing ideas from deterministic approximation theory\, optimization\, and experimental design. Previous efforts at integrating approximate models into inference typically sacrifice either the sampler’s exactness or efficiency; our work seeks to address these limitations by exploiting useful convergence characteristics of local approximations. We prove the ergodicity of our approximate Markov chain\, showing that it samples asymptotically from the exact posterior distribution of interest. We describe variations of the algorithm that employ either local polynomial approximations or local Gaussian process regressors. Our theoretical results reinforce the key observation underlying this article: when the likelihood has some local regularity\, the number of model evaluations per Markov chain Monte Carlo (MCMC) step can be greatly reduced without biasing the Monte Carlo average. Numerical experiments demonstrate multiple order-of-magnitude reductions in the number of forward model evaluations used in representative ordinary differential equation (ODE) and partial differential equation (PDE) inference problems\, with both synthetic and real data.\n\n\n9:40 am – 10:20 am\nRavi Jagadeesan \nVideo\nTitle: Designs for estimating the treatment effect in networks with interference \nAbstract: In this paper we introduce new\, easily implementable designs for drawing causal inference from randomized experiments on networks with interference. Inspired by the idea of matching in observational studies\, we introduce the notion of considering a treatment assignment as a quasi-coloring” on a graph. Our idea of a perfect quasi-coloring strives to match every treated unit on a given network with a distinct control unit that has identical number of treated and control neighbors. For a wide range of interference functions encountered in applications\, we show both by theory and simulations that the classical Neymanian estimator for the direct effect has desirable properties for our designs. This further extends to settings where homophily is present in addition to interference.\n\n\n10:20 am – 10:50 am\n\nBreak\n\n\n10:50 am – 11:30 am\nAnnie Liang \nVideo\nTitle: The Theory is Predictive\, but is it Complete? An Application to Human Generation of Randomness \nAbstract: When we test a theory using data\, it is common to focus on correctness: do the predictions of the theory match what we see in the data? But we also care about completeness: how much of the predictable variation in the data is captured by the theory? This question is difficult to answer\, because in general we do not know how much “predictable variation” there is in the problem. In this paper\, we consider approaches motivated by machine learning algorithms as a means of constructing a benchmark for the best attainable level of prediction.  We illustrate our methods on the task of predicting human-generated random sequences. Relative to a theoretical machine learning algorithm benchmark\, we find that existing behavioral models explain roughly 15 percent of the predictable variation in this problem. This fraction is robust across several variations on the problem. We also consider a version of this approach for analyzing field data from domains in which human perception and generation of randomness has been used as a conceptual framework; these include sequential decision-making and repeated zero-sum games. In these domains\, our framework for testing the completeness of theories provides a way of assessing their effectiveness over different contexts; we find that despite some differences\, the existing theories are fairly stable across our field domains in their performance relative to the benchmark. Overall\, our results indicate that (i) there is a significant amount of structure in this problem that existing models have yet to capture and (ii) there are rich domains in which machine learning may provide a viable approach to testing completeness (joint with Jon Kleinberg and Sendhil Mullainathan).\n\n\n11:30 am – 12:10 pm\nZak Stone \nVideo\nTitle: TensorFlow: Machine Learning for Everyone \nAbstract: We’ve witnessed extraordinary breakthroughs in machine learning over the past several years. What kinds of things are possible now that weren’t possible before? How are open-source platforms like TensorFlow and hardware platforms like GPUs and Cloud TPUs accelerating machine learning progress? If these tools are new to you\, how should you get started? In this session\, you’ll hear about all of this and more from Zak Stone\, the Product Manager for TensorFlow on the Google Brain team.\n\n\n12:10 pm – 1:30 pm\n\nLunch\n\n\n1:30 pm – 2:10 pm\nJann Spiess \nVideo\nTitle: (Machine) Learning to Control in Experiments \nAbstract: Machine learning focuses on high-quality prediction rather than on (unbiased) parameter estimation\, limiting its direct use in typical program evaluation applications. Still\, many estimation tasks have implicit prediction components. In this talk\, I discuss accounting for controls in treatment effect estimation as a prediction problem. In a canonical linear regression framework with high-dimensional controls\, I argue that OLS is dominated by a natural shrinkage estimator even for unbiased estimation when treatment is random; suggest a generalization that relaxes some parametric assumptions; and contrast my results with that for another implicit prediction problem\, namely the first stage of an instrumental variables regression.\n\n\n2:10 pm – 2:50 pm\nBradly Stadie\nTitle: Learning to Learn Quickly: One-Shot Imitation and Meta Learning \nAbstract: Many reinforcement learning algorithms are bottlenecked by data collection costs and the brittleness of their solutions when faced with novel scenarios.\nWe will discuss two techniques for overcoming these shortcomings. In one-shot imitation\, we train a module that encodes a single demonstration of a desired behavior into a vector containing the essence of the demo. This vector can subsequently be utilized to recover the demonstrated behavior. In meta-learning\, we optimize a policy under the objective of learning to learn new tasks quickly. We show meta-learning methods can be accelerated with the use of auxiliary objectives. Results are presented on grid worlds\, robotics tasks\, and video game playing tasks.\n\n\n2:50 pm – 3:20 pm\n\nBreak\n\n\n3:20 pm – 4:00 pm\nHau-Tieng Wu \nVideo\nTitle: When Medical Challenges Meet Modern Data Science \nAbstract: Adaptive acquisition of correct features from massive datasets is at the core of modern data analysis. One particular interest in medicine is the extraction of hidden dynamics from a single observed time series composed of multiple oscillatory signals\, which could be viewed as a single-channel blind source separation problem. The mathematical and statistical problems are made challenging by the structure of the signal which consists of non-sinusoidal oscillations with time varying amplitude/frequency\, and by the heteroscedastic nature of the noise. In this talk\, I will discuss recent progress in solving this kind of problem by combining the cepstrum-based nonlinear time-frequency analysis and manifold learning technique. A particular solution will be given along with its theoretical properties. I will also discuss the application of this method to two medical problems – (1) the extraction of a fetal ECG signal from a single lead maternal abdominal ECG signal; (2) the simultaneous extraction of the instantaneous heart/respiratory rate from a PPG signal during exercise; (3) (optional depending on time) an application to atrial fibrillation signals. If time permits\, the clinical trial results will be discussed.\n\n\n4:00 pm – 4:40 pm\nSifan Zhou \nVideo\nTitle: Citing People Like Me: Homophily\, Knowledge Spillovers\, and Continuing a Career in Science \nAbstract: Forward citation is widely used to measure the scientific merits of articles. This research studies millions of journal article citation records in life sciences from MEDLINE and finds that authors of the same gender\, the same ethnicity\, sharing common collaborators\, working in the same institution\, or being geographically close are more likely (and quickly) to cite each other than predicted by their proportion among authors working on the same research topics. This phenomenon reveals how social and geographic distances influence the quantity and speed of knowledge spillovers. Given the importance of forward citations in academic evaluation system\, citation homophily potentially put authors from minority group at a disadvantage. I then show how it influences scientists’ chances to survive in the academia and continue publishing. Based on joint work with Richard Freeman.\n\n\n\n  \nTo view photos and video interviews from the conference\, please visit the CMSA blog. \n\n \n\n  \n\n\n\nBig Data\,CMSA\,Harvard\,Math\nEvents\,Past Events
URL:https://cmsa.fas.harvard.edu/event/2017-big-data-conference-aug-18-19/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Big Data Conference,Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Big-Data-2017_2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170605T090000
DTEND;TZID=America/New_York:20170606T170000
DTSTAMP:20260502T021524
CREATED:20230717T175551Z
LAST-MODIFIED:20250305T182141Z
UID:10000032-1496653200-1496768400@cmsa.fas.harvard.edu
SUMMARY:A Celebration of Symplectic Geometry: 15 Years of JSG
DESCRIPTION:In celebration of the Journal of Symplectic Geometry’s 15th anniversary\, the Center of Mathematical Sciences and Applications will be hosting A Celebration of Symplectic Geometry: 15 Years of JSG on June 5-6\, 2017. \nConfirmed speakers: \n\nRoger Casals\, MIT\nChen He\, Northeastern University\nYael Karshon\, University of Toronto\nAilsa Keating\, Institute of Advanced Study\nEckhard Meinrenken\, University of Toronto\nAna Rita Pires\, Fordham University\nSobhan Seyfaddini\, Institute of Advanced Study\nAlejandro Uribe\, University of Michigan\nJonathan Weitsman\, Northeastern University\n\nThe conference is co-organized by Denis Auroux and Victor Guillemin. Additional information on the conference will be announced closer to the event. \nSchedule:\nJune 5\, Monday (Full day)\n\n\n\nTime\nSpeaker\nTopic\n\n\n8:30am – 9:0am\n\nBreakfast\n\n\n9:00am – 10:00am\nJonathan Weitsman\nTitle: On the geometric quantization of (some) Poisson manifolds\n\n\n10:30am – 11:30am\nEckhard Meinrenken\nTitle: On Hamiltonian loop group spaces \nAbstract: Let G be a compact Lie group. We explain a construction of an LG-equivariant spinor module over any Hamiltonian loop group space with proper moment map. It may be regarded as its `canonical spin-c structure’. We show how to reduce to finite dimensions\, resulting in actual spin-s structure on transversals\, as well as twisted spin-c structures for the associated quasi-hamiltonian space. This is based on joint work with Yiannis Loizides and Yanli Song.\n\n\n\n11:30am – 1:30pm\n\nBreak\n\n\n1:30pm – 2:30pm\nAna Rita Pires\nTitle: Infinite staircases in symplectic embedding problems \nAbstract: McDuff and Schlenk studied an embedding capacity function\, which describes when a 4-dimensional ellipsoid can symplectically embed into a 4-ball. The graph of this function includes an infinite staircase related to the odd index Fibonacci numbers. Infinite staircases have been shown to exist also in the graphs of the embedding capacity functions when the target manifold is a polydisk or the ellipsoid E(2\,3). I will describe how we use ECH capacities\, lattice point counts and Ehrhart theory to show that infinite staircases exist for these and a few other target manifolds\, as well as to conjecture that these are the only such target manifolds. This is a joint work with Cristofaro-Gardiner\, Holm and Mandini. \nVideo\n\n\n3:00pm – 4:00pm\nSobhan Seyfaddini\nTitle: Rigidity of conjugacy classes in groups of area-preserving homeomorphisms \nAbstract: Motivated by understanding the algebraic structure of groups of area-preserving homeomorphims F. Beguin\, S. Crvoisier\, and F. Le Roux were lead to the following question: Can the conjugacy class of a Hamiltonian homeomorphism be dense? We will show that one can rule out existence of dense conjugacy classes by simply counting fixed points. This is joint work with Le Roux and Viterbo.\n\n\n4:30pm – 5:30pm\nRoger Casals\nTitle: Differential Algebra of Cubic Graphs\nAbstract: In this talk we will associate a combinatorial dg-algebra to a cubic planar graph. This algebra is defined by counting binary sequences\, which we introduce\, and we shall provide explicit computations and examples. From there we study the Legendrian surfaces behind these constructions\, including Legendrian surgeries\, the count of Morse flow trees involved in contact homology\, and the relation to microlocal sheaves. Time permitting\, I will explain a connection to spectral networks.Video\n\n\n\nJune 6\, Tuesday (Full day) \n\n\n\nTime\nSpeaker\nTopic\n\n\n8:30am – 9:00am\n\nBreakfast\n\n\n9:00am – 10:00am\nAlejandro Uribe\nTitle: Semi-classical wave functions associated with isotropic submanifolds of phase space \nAbstract: After reviewing fundamental ideas on the quantum-classical correspondence\, I will describe how to associate spaces of semi-classical wave functions to isotropic submanifolds of phase space satisfying a Bohr-Sommerfeld condition. Such functions have symbols that are symplectic spinors\, and they satisfy a symbol calculus under the action of quantum observables. This is the semi-classical version of the Hermite distributions of Boutet the Monvel and Guillemin\, and it is joint work with Victor Guillemin and Zuoqin Wang. I will inlcude applications and open questions. \nVideo\n\n\n10:30am – 11:30am\nAlisa Keating\nTitle: Symplectomorphisms of exotic discs \nAbstract: It is a theorem of Gromov that the group of compactly supported symplectomorphisms of R^4\, equipped with the standard symplectic form\, is contractible. While nothing is known in higher dimensions for the standard symplectic form\, we show that for some exotic symplectic forms on R^{4n}\, for all but finitely n\, there exist compactly supported symplectomorphisms that are smoothly non-trivial. The principal ingredients are constructions of Milnor and Munkres\, a symplectic and contact version of the Gromoll filtration\, and Borman\, Eliashberg and Murphy’s work on existence of over-twisted contact structures. Joint work with Roger Casals and Ivan Smith. \nVideo\n\n\n11:30am – 1:30pm\n\nBreak\n\n\n1:30pm – 2:30pm\nChen He\nTitle: Morse theory on b-symplectic manifolds \nAbstract: b-symplectic (or log-symplectic) manifolds are Poisson manifolds equipped with symplectic forms of logarithmic singularity. Following Guillemin\, Miranda\, Pires and Scott’s introduction of Hamiltonian group actions on b-symplectic manifolds\, we will survey those classical results of Hamiltonian geometry to the b-symplectic case. \nVideo\n\n\n3:00pm – 4:00pm\nYael Karshon\nTitle: Geometric quantization with metaplectic-c structures \nAbstract: I will present a variant of the Kostant-Souriau geometric quantization procedure that uses metaplectic-c structures to incorporate the “half form correction” into the prequantization stage. This goes back to the late 1970s but it is not widely known and it has the potential to generalize and improve upon recent works on geometric quantization. \nVideo\n\n\n\n 
URL:https://cmsa.fas.harvard.edu/event/a-celebration-of-symplectic-geometry-15-years-of-jsg-june-5-6-2017/
LOCATION:20 Garden Street\, Cambridge\, MA 02138\, MA\, MA\, 02138\, United States
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Shlomo_orange.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170501T090000
DTEND;TZID=America/New_York:20170502T170000
DTSTAMP:20260502T021524
CREATED:20230717T175324Z
LAST-MODIFIED:20240209T152357Z
UID:10000031-1493629200-1493744400@cmsa.fas.harvard.edu
SUMMARY:Working Conference on Covariance Analysis in Biology\, May 1-4\, 2017
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a working Conference on Covariance Analysis in Biology\, May 1-4\, 2017.  The conference will be hosted in Room G10 of the CMSA Building located at 20 Garden Street\, Cambridge\, MA 02138. \nThis event is open and free.  If you would like to attend\, please register here to help us keep a headcount. A list of lodging options convenient to the Center can also be found on our recommended lodgings page. \nSpeakers: \nOrr Ashenberg\, Fred Hutchinson Cancer Research Center \nJohn Barton\, Massachusetts Institute of Technology \nSimona Cocco\, Laboratoire de Physique Statistique de l’ENS \nSean Eddy\, Harvard University \nEfthimios Kaxiras\, Harvard University \n\n\n\nMichael Laub\, Massachusetts Institute of Technology \nDebora S. Marks\, Harvard University \n\n\n\nGovind Menon\, Brown University \nRémi Monasson\, Laboratoire de Physique Théorique de l’ENS \nAndrew Murray\, Harvard University \nIlya Nemenman\, Emory College \n\n\n\nChris Sander\, Dana-Farber Cancer Institute\, Harvard Medical School \n\n\n\nDave Thirumalai\, University of Texas at Austin \nMartin Weigt\, IBPS\, Université Pierre et Marie Curie \nMatthieu Wyart\, EPFL \nMore speakers will be confirmed soon. \n  \n\n\n\nSchedule:\n(Please click here for a downloadable version of the schedule.)\nPlease note that the schedule for both days is currently tentative and is subject to change.\nMay 1\, Monday \n\n\n\n\n\nTime\nSpeaker\nTopic\n\n\n9:00-10:00am\nSean Eddy\nTBA\n\n\n10:00-11:00am\nMike Laub\nTBA\n\n\n11:00am-12:00pm\nIlya Nemenman\nTBA\n\n\n\n\nMay 2\, Tuesday\n\n\n\n\n\nTime\nSpeaker\nTopic\n\n\n9:00-10:00am\nOrr Ashenberg\nTBA\n\n\n10:00-11:00am\nDebora Marks\nTBA\n\n\n11:00am-12:00pm\nMartin Weigt\nTBA\n\n\n4:30pm-5:30pm\nSimona Cocco\nCMSA Colloquia\n\n\n\n  \n\nMay 3\, Wednesday\n\n\n\n\n\nTime\nSpeaker\nTopic\n\n\n9:00-10:00am\nAndrew Murray\nTBA\n\n\n10:00-11:00am\nMatthieu Wyart\nTBA\n\n\n11:00am-12:00pm\nRémi Monasson\nTBA\n\n\n\n  \n\nMay 4\, Thursday\n\n\n\n\nTime\nSpeaker\nTopic\n\n\n9:00-10:00am\nDavid Thirumalai\nTBA\n\n\n10:00-11:00am\nChris Sander\nTBA\n\n\n11:00am-12:00pm\nJohn Barton\nTBA\n\n\n\n  \n\n\nOrganizers: \n\n\n\nMichael Brenner\, Lucy Colwell\, Elena Rivas\, Eugene Shakhnovich \n\n\n\n* This event is sponsored by CMSA Harvard University. \n\n\n\n\nPast Events
URL:https://cmsa.fas.harvard.edu/event/working-conference-on-covariance-analysis-in-biology-may-1-4-2017/
LOCATION:20 Garden Street\, Cambridge\, MA 02138\, MA\, MA\, 02138\, United States
CATEGORIES:Conference,Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170428T090000
DTEND;TZID=America/New_York:20170502T170000
DTSTAMP:20260502T021524
CREATED:20230717T175015Z
LAST-MODIFIED:20250305T215930Z
UID:10000030-1493370000-1493744400@cmsa.fas.harvard.edu
SUMMARY:JDG 2017 Conference
DESCRIPTION:In celebration of the Journal of Differential Geometry’s 50th anniversary\, the Harvard Math Department will be hosting the Tenth Conference on Geometry and Topology (JDG 2017) from April 28 – May 2\, 2017. \nConfirmed Speakers \n\nMina Aganagic\, UC Berkeley\nDenis Auroux\, UC Berkeley\nCaucher Birkar\, University of Cambridge\nHuai-Dong Cao\, Lehigh University\nTristan Collins\, Harvard University\nCamillo De Lellis\, ETH Zurich\nJean-Pierre Demailly\, Grenoble Alpes University\nSimon Donaldson\, Stony Brook University\nDan Freed\, University of Texas at Austin\nKenji Fukaya\, Stony Brook University\nDavid Gabai\, Princeton University\nLarry Guth\, Massachusetts Institute of Technology\nRichard Hamilton\, Columbia University\nYujiro Kawamata\, University of Tokyo\nFrances Kirwan\, Oxford University\nBlaine Lawson\, Stony Brook University\nJun Li\, Stanford University\nSi Li\, Tsinghua University\nBong Lian\, Brandeis University\nChiu-Chu Melissa Liu\, Columbia University\nCiprian Manolescu\, University of California\, Los Angeles\nFernando Marques\, Princeton University\nWilliam Meeks\, University of Massachusetts Amherst\nWilliam Minicozzi\, Massachusetts Institute of Technology\nJohn Pardon\, Princeton University\nDuong Phong\, Columbia University\nAlena Pirutka\, Courant Institute of New York University\nRichard Schoen\, University of California\, Irvine\nArtan Sheshmani\, QGM Aarhus University/Harvard University\nCliff Taubes\, Harvard University\nCumrun Vafa\, Harvard University\nMu-Tao Wang\, Columbia University\nShing-Tung Yau\, Harvard University\nSteve Zelditch\, Northwestern University\n\n* This event is co-sponsored by Lehigh University and partially supported by the National Science Foundation.
URL:https://cmsa.fas.harvard.edu/event/jdg-2017-conference-april-28-may-2-2017/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/JDG-2017-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170327T153400
DTEND;TZID=America/New_York:20170330T153400
DTSTAMP:20260502T021524
CREATED:20240209T021031Z
LAST-MODIFIED:20240307T105730Z
UID:10001796-1490628840-1490888040@cmsa.fas.harvard.edu
SUMMARY:Working Conference on Materials and Data Analysis\, March 27-30\, 2017
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a 5-day working Conference on Materials and Data Analysis and related areas\, March 27-30\, 2017.  The conference will be hosted in Room G10 of the CMSA Building located at 20 Garden Street\, Cambridge\, MA 02138. \nPhotos of the event can be found on CMSA’s Blog. \n Participants:\n\nRyan P. Adams\, Harvard University\nJörg Behler\, University of Göttingen\nKieron Burke\, University of California\, Irvine\nLucy Colwell\, University of Cambridge\nGábor Csányi\, University of Cambridge\nEkin Doğuş Çubuk\, Stanford University\nLeslie Greengard\, Courant Institute of Mathematical Sciences\, New York University\nPetros Koumoutsakos\, Radcliffe Institute for Advanced Study\, Harvard University\nGovind Menon\, Brown University\nEvan Reed\, Stanford University\nPatrick Riley\, Google\nMatthias Rupp\, Fitz Haber Institute of the Max Planck Society\nSadasivan Shankar\, Harvard University\nDennis Sheberla\, Harvard University\n\n\n\nOrganizers: \n\n\n\nMichael Brenner\, Efthimios Kaxiras \n\n\n\n* This event is sponsored by CMSA Harvard University. \n\nSchedule:\n\nMonday\, March 27 \n\n\n\nTime\nSpeaker\nTitle\n\n\n8:30am – 9:00am\nBreakfast\n\n\n9:00am – 10:00am\nKieron Burke\, University of California\, Irvine\nBackground in DFT and electronic structure calculations\n\n\n10:00am – 11:00am\nKieron Burke\, University of California\, Irvine\n\nThe density functionals machines can learn \n\n\n\n11:00am – 12:00pm\nSadasivan Shankar\, Harvard University\nA few key principles for applying Machine Learning to Materials (or Complex Systems) — Scientific and Engineering Perspectives\n\n\n\nTuesday\, March 28 \n\n\n\nTime\nSpeaker\nTitle\n\n\n8:30am – 9:00am\nBreakfast\n\n\n9:00am – 10:00am\nRyan Adams\, Harvard\nTBA\n\n\n10:00am – 11:00am\nGábor Csányi\, University of Cambridge\n\nInteratomic potentials using machine learning: accuracy\, transferability and chemical diversity \n\n\n\n11:00am – 1:00pm\nLunch Break\n\n\n1:00pm – 2:00pm\nEvan Reed\, Stanford University\nTBA\n\n\n\n Wednesday\, March 29  \n\n\n\nTime\nSpeaker\nTitle\n\n\n8:30am – 9:00am\nBreakfast\n\n\n9:00am – 10:00am\nPatrick Riley\, Google\nThe Message Passing Neural Network framework and its application to molecular property prediction\n\n\n10:00am – 11:00am\nJörg Behler\, University of Göttingen\nTBA\n\n\n11:00am – 12:00pm\nEkin Doğuş Çubuk\, Stanford Univers\nTBA\n\n\n4:00pm\nLeslie Greengard\, Courant Institute\nInverse problems in acoustic scattering and cryo-electron microscopy \nCMSA Colloquium\n\n\n\nThursday\, March 30 \n\n\n\nTime\nSpeaker\nTitle\n\n\n8:30am – 9:00am\nBreakfast\n\n\n9:00am – 10:00am\nMatthias Rupp\, Fitz Haber Institute of the Max Planck Society\nTBA\n\n\n10:00am – 11:00am\nPetros Koumoutsakos\, Radcliffe Institute for Advanced Study\, Harvard\nTBA\n\n\n11:00am – 1:00pm\nLunch Break\n\n\n1:00pm – 2:00pm\nDennis Sheberla\, Harvard University\nRapid discovery of functional molecules by a high-throughput virtual screening\n\n\n\n\n\n\n\nEvents\, Past Events
URL:https://cmsa.fas.harvard.edu/event/working-conference-on-materials-and-data-analysis-march-27-30-2017/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Conference,Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170109T090000
DTEND;TZID=America/New_York:20170113T170000
DTSTAMP:20260502T021524
CREATED:20250305T194842Z
LAST-MODIFIED:20250305T194842Z
UID:10003717-1483952400-1484326800@cmsa.fas.harvard.edu
SUMMARY:Working Conference on Applications of Random Matrix Theory to Data Analysis\, January 9-13\, 2017
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a working Conference on Applications of Random Matrix Theory to Data Analysis\, January 9-13\, 2017.  The conference will be hosted in Room G10 of the CMSA Building located at 20 Garden Street\, Cambridge\, MA 02138. \nParticipants:\nGerard Ben Arous\, Courant Institute of Mathematical Sciences \nAlex Bloemendal\, Broad Institute \nArup Chakraburty\, MIT \n\n\n\nZhou Fan\, Stanford University \nAlpha Lee\, Harvard University \nMatthew R. McKay\, Hong Kong University of Science and Technology (HKUST) \nDavid R. Nelson\, Harvard University \nNick Patterson\, Broad Institute \nMarc Potters\, Capital Fund management \n\n\n\nYasser Roudi\, IAS \nTom Trogdon\, UC Irvine \nOrganizers: \n\n\n\nMichael Brenner\, Lucy Colwell\, Govind Menon\, Horng-Tzer Yau \nPlease click Program for a downloadable schedule with talk abstracts.\n\nSchedule: \n\n\n\nJanuary 9 – Day 1\n\n\n9:30am – 10:00am\nBreakfast & Opening remarks\n\n\n10:00am – 11:00am\nMarc Potters\, “Eigenvector overlaps and the estimation of large noisy matrices”\n\n\n11:00am – 12:00pm\nYasser Roudi\n\n\n12:00pm – 2:00pm\nLunch\n\n\n2:00pm\nAfternoon Discussion\n\n\nJanuary 10 – Day 2\n\n\n8:30am – 9:00am\nBreakfast\n\n\n9:00am – 10:00am\nArup Chakraburty\, “The mathematical analyses and biophysical reasons underlying why the prevalence of HIV strains and their relative fitness are simply correlated\, and pose the challenge of building a general theory that encompasses other viruses where this is not true.”\n\n\n10:00am – 11:00am\nTom Trogdon\, “On the average behavior of numerical algorithms”\n\n\n11:00am – 12:00pm\nDavid R. Nelson\, “Non-Hermitian Localization in Neural Networks”\n\n\n12:00pm – 2:00pm\nLunch\n\n\n2:00pm\nAfternoon Discussion\n\n\nJanuary 11 – Day 3\n\n\n8:30am – 9:00am\nBreakfast\n\n\n9:00am – 10:00am\nNick Patterson\n\n\n10:00am – 11:00am\nLucy Colwell\n\n\n11:00am – 12:00pm\nAlpha Lee\n\n\n12:00pm – 2:00pm\nLunch\n\n\n2:00pm-4:00pm\nAfternoon Discussion\n\n\n4:00pm\nGerard Ben Arous (Public Talk)\, “Complexity of random functions of many variables: from geometry to statistical physics and deep learning algorithms“\n\n\nJanuary 12 – Day 4\n\n\n8:30am – 9:00am\nBreakfast\n\n\n9:00am – 10:00am\nGovind Menon\n\n\n10:00am – 11:00am\nAlex Bloemendal\n\n\n11:00am – 12:00pm\nZhou Fan\, “Free probability\, random matrices\, and statistics”\n\n\n12:00pm – 2:00pm\nLunch\n\n\n2:00pm\nAfternoon Discussion\n\n\nJanuary 13 – Day 5\n\n\n8:30am – 9:00am\nBreakfast\n\n\n9:00am – 12:00pm\nFree for Working\n\n\n12:00pm – 2:00pm\nLunch\n\n\n2:00pm\nFree for Working\n\n\n\n\n* This event is sponsored by CMSA Harvard University.
URL:https://cmsa.fas.harvard.edu/event/working-conference-on-applications-of-random-matrix-theory-to-data-analysis-january-9-13-2017/
LOCATION:CMSA 20 Garden Street Cambridge\, Massachusetts 02138 United States
CATEGORIES:Conference,Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161203T090000
DTEND;TZID=America/New_York:20161204T170000
DTSTAMP:20260502T021524
CREATED:20230717T172404Z
LAST-MODIFIED:20250305T201523Z
UID:10000018-1480755600-1480870800@cmsa.fas.harvard.edu
SUMMARY:Mini-school on Nonlinear Equations\, December 3-4\, 2016
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a Mini-school on Nonlinear Equations on December 3-4\, 2016. The conference will have speakers and will be hosted at Harvard CMSA Building: Room G10 20 Garden Street\, Cambridge\, MA 02138. \nSpeakers:\n\nCliff Taubes (Harvard University)\nValentino Tosatti (Northwestern University)\nPengfei Guan (McGill University)\nJared Speck (MIT)\n\nSchedule:\n\n\n\nDecember 3rd – Day 1\n\n\n9:00am – 10:30am\nCliff Taubes\, “Compactness theorems in gauge theories”\n\n\n10:45am – 12:15pm\nValentino Tosatti\, “Complex Monge-Ampère Equations”\n\n\n\n\n\n12:15pm – 1:45pm\nLUNCH\n\n\n\n\n\n\n1:45pm – 3:15pm\nPengfei Guan\, “Monge-Ampère type equations and related geometric problems”\n\n\n3:30pm – 5:00pm\nJared Speck\, “Finite-time degeneration of hyperbolicity without blowup for solutions to quasilinear wave equations”\n\n\n\n\n\n\n\n\nDecember 4th – Day 2\n\n\n9:00am – 10:30am\nCliff Taubes\, “Compactness theorems in gauge theories”\n\n\n10:45am – 12:15pm\nValentino Tosatti\, “Complex Monge-Ampère Equations”\n\n\n\n\n\n12:15pm – 1:45pm\nLUNCH\n\n\n\n\n\n\n1:45pm – 3:15pm\nPengfei Guan\, “Monge-Ampère type equations and related geometric problems”\n\n\n3:30pm – 5:00pm\nJared Speck\, “Finite-time degeneration of hyperbolicity without blowup for solutions to quasilinear wave equations”\n\n\n\n\n  \n* This event is sponsored by National Science Foundation (NSF) and CMSA Harvard University.
URL:https://cmsa.fas.harvard.edu/event/mini-school-on-nonlinear-equations-december-3-4-2016/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Conference,Event,Workshop
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/minischool.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160822T090000
DTEND;TZID=America/New_York:20160823T163000
DTSTAMP:20260502T021524
CREATED:20230717T171959Z
LAST-MODIFIED:20250328T144123Z
UID:10000017-1471856400-1471969800@cmsa.fas.harvard.edu
SUMMARY:2016 Big Data Conference & Workshop
DESCRIPTION:! LOCATION CHANGE: The conference will be in Science Center Hall C on Tuesday\, Aug.23\, 2016.\nThe Center of Mathematical Sciences and Applications will be hosting a workshop on Big Data from August 12 – 21\, 2016 followed by a two-day conference on Big Data from August 22 – 23\, 2016. \nBig Data Conference features many speakers from the Harvard Community as well as many scholars from across the globe\, with talks focusing on computer science\, statistics\, math and physics\, and economics. This is the second conference on Big Data the Center will host as part of our annual events. The 2015 conference was a huge success. \nThe conference will be hosted at Harvard Science Center Hall A (Monday\, Aug.22) & Hall C (Tuesday\, Aug.23): 1 Oxford Street\, Cambridge\, MA 02138. \nThe 2016 Big Data conference is sponsored by the Center of Mathematical Sciences and Applications at Harvard University and the Alfred P. Sloan Foundation. \nConference Speakers:\n\nJörn Boehnke\, Harvard CMSA\nJoan Bruna\, UC Berkeley [Video]\nTamara Broderick\, MIT [Video]\nJustin Chen\, MIT [Video]\nYiling Chen\, Harvard University [Video]\nAmir Farbin\, UT Arlington [Video]\nDoug Finkbeiner\, Harvard University [Video]\nAndrew Gelman\, Columbia University [Video]\nNina Holden\, MIT [Video]\nElchanan Mossel\, MIT\nAlex Peysakhovich\, Facebook\nAlexander Rakhlin\, University of Pennsylvania [Video]\nNeal Wadhwa\, MIT [Video]\nJun Yin\, University of Wisconsin\nHarry Zhou\, Yale University [Video]\n\nPlease click Conference Program for a downloadable schedule with talk abstracts.\nConference Schedule:\n\n\n\nAugust 22 – Day 1\n\n\n8:30am\nBreakfast\n\n\n8:55am\nOpening remarks\n\n\n9:00am – 9:50am\nYiling Chen\, “Machine Learning with Strategic Data Sources” [Video]\n\n\n9:50am – 10:40am\nAndrew Gelman\, “Taking Bayesian Inference Seriously” [Video]\n\n\n10:40am – 11:10am\nBreak\n\n\n11:10am – 12:00pm\nHarrison Zhou\, “A General Framework for Bayes Structured Linear Models” [Video]\n\n\n12:00pm – 1:30pm\nLunch\n\n\n1:30pm – 2:20pm\nDouglas Finkbeiner\, “Mapping the Milky Way in 3D with star colors” [Video]\n\n\n2:20pm – 3:10pm\nNina Holden\, “Sparse exchangeable graphs and their limits” [Video]\n\n\n3:10pm – 3:40pm\nBreak\n\n\n3:40pm – 4:30pm\nAlex Peysakhovich\, “How social science methods inform personalization on Facebook News Feed” [Video]\n\n\n4:30pm – 5:20pm\nAmir Farbin\, “Deep Learning in High Energy Physics” [Video]\n\n\n\n\n\nAugust 23 – Day 2\n\n\n8:45am\nBreakfast\n\n\n9:00am – 9:50am\nJoan Bruna Estrach\, “Addressing Computational and Statistical Gaps with Deep Networks” [Video]\n\n\n9:50am – 10:40am\nJustin Chen & Neal Wadhwa\, “Smaller Than the Eye Can See: Big Engineering from Tiny Motions in Video” [Video]\n\n\n10:40am – 11:10am\nBreak\n\n\n11:10am – 12:00pm\nAlexander Rakhlin\, “How to Predict When Estimation is Hard: Algorithms for Learning on Graphs” [Video]\n\n\n12:00pm – 1:30pm\nLunch\n\n\n1:30pm – 2:20pm\nTamara Broderick\, “Fast Quantification of Uncertainty and Robustness with Variational Bayes” [Video]\n\n\n2:20pm – 3:10pm\nElchanan Mossel\, “Phylogenetic Reconstruction – a Rigorous Model of Deep Learning”\n\n\n3:10pm – 3:40pm\nBreak\n\n\n3:40pm – 4:30pm\nJörn Boehnke\, “Amazon’s Price and Sales-rank Data: What can one billion prices on 150 thousand products tell us about the economy?”\n\n\n\nWorkshop Participants:\nRichard Freeman’s Group: \n\nSen Chai\, ESSEC\nBrock Mendel\, Harvard University\nRaviv Muriciano-Goroff\, Stanford University\nSifan Zhou\, CMSA\n\nScott Kominer’s Group: \n\nBradly Stadie\, UC Berkeley\nNeal Wadhwa\, MIT [Video]\nJustin Chen\n\nChristopher Rogan’s Group: \n\nAmir Farbin\, UT Arlington [Video]\nPaul Jackson\, University of Adelaide\n\nFor more information about the workshops\, please reach out directly to the individual group leaders. \n* This event is sponsored by CMSA Harvard University and the Alfred P. Sloan Foundation. \n 
URL:https://cmsa.fas.harvard.edu/event/2016-big-data-conference-workshop/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Big Data Conference,Conference,Event,Workshop
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Big-Data_2016_2-1-2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160408T083000
DTEND;TZID=America/New_York:20160410T180000
DTSTAMP:20260502T021524
CREATED:20230717T180554Z
LAST-MODIFIED:20240209T151732Z
UID:10000016-1460104200-1460311200@cmsa.fas.harvard.edu
SUMMARY:Concluding Conference of the Special Program on Nonlinear Equations\, April 8 – 10\, 2016
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a concluding conference on April 8-10\, 2016 to accompany the year-long program on nonlinear equations. The conference will have 15 speakers and will be hosted at Harvard CMSA Building: Room G10 20 Garden Street\, Cambridge\, MA 02138 \nSpeakers:\n\nLydia Bieri (University of Michigan)\nLuis Caffarelli (University of Texas at Austin)\nMihalis Dafermos (Princeton University)\nCamillo De Lellis (Universität Zürich)\nPengfei Guan (McGill University)\nSlawomir Kolodziej (Jagiellonian University)\nMelissa Liu (Columbia University)\nDuong H. Phong (Columbia University)\nRichard Schoen (UC Irvine)\nCliff Taubes (Harvard University)\nBlake Temple (UC Davis)\nValentino Tosatti (Northwestern University)\nTai-Peng Tsai (University of British Columbia)\nMu-Tao Wang (Columbia University)\nXu-jia Wang (Australian National University)\n\nPlease click NLE Conference Schedule with Abstracts for a downloadable schedule with talk abstracts.\nPlease note that lunch will not be provided during the conference\, but a map of Harvard Square with a list of local restaurants can be found by clicking Map & Resturants.\nSchedule:\n\n\n\nApril 8 – Day 1\n\n\n8:30am\nBreakfast\n\n\n8:45am\nOpening remarks\n\n\n9:00am – 10:00am\nCamillo De Lellis\, “A Nash Kuiper theorem for $C^{1\,1:5}$ isometric immersions of disks“\n\n\n10:00am – 10:15am\nBreak\n\n\n10:15am – 11:15am\nXu-Jia Wang\, “Monge’s mass transport problem“\n\n\n11:15am – 11:30am\nBreak\n\n\n11:30am – 12:30pm\nPeng-Fei Guan\, “The Weyl isometric embedding problem in general $3$ d Riemannian manifolds“\n\n\n12:30pm – 2:00pm\nLunch\n\n\n2:00pm – 3:00pm\nBlake Temple\, “An instability in the Standard Model of Cosmology“\n\n\n3:00pm – 3:15pm\nBreak\n\n\n3:15pm – 4:15pm\nLydia Bieri\, “The Einstein Equations and Gravitational Radiation“\n\n\n4:15pm – 4:30pm\nBreak\n\n\n4:30pm – 5:30pm\nValentino Tosatti\, “Adiabatic limits of Ricci flat Kahler metrics“\n\n\n\n\n\nApril 9 – Day 2\n\n\n8:45am\nBreakfast\n\n\n9:00am – 10:00am\nD.H. Phong\, “On Strominger systems and Fu-Yau equations”\n\n\n10:00am – 10:15am\nBreak\n\n\n10:15am – 11:15am\nSlawomir Kolodziej\, “Stability of weak solutions of the complex Monge-Ampère equation on compact Hermitian manifolds”\n\n\n11:15am – 11:30am\nBreak\n\n\n11:30am – 12:30pm\nLuis Caffarelli\, “Non local minimal surfaces and their interactions”\n\n\n12:30pm – 2:00pm\nLunch\n\n\n2:00pm – 3:00pm\nMihalis Dafermos\, “The interior of dynamical vacuum black holes and the strong cosmic censorship conjecture in general relativity”\n\n\n3:00pm – 3:15pm\nBreak\n\n\n3:15pm – 4:15pm\nMu-Tao Wang\, “The stability of Lagrangian curvature flows”\n\n\n4:15pm – 4:30pm\nBreak\n\n\n4:30pm – 5:30pm\nMelissa Liu\, “Counting curves in a quintic threefold”\n\n\n\n\n\nApril 10 – Day 3\n\n\n8:45am\nBreakfast\n\n\n9:00am – 10:00am\nRick Schoen\, “Metrics of fixed area on high genus surfaces with largest first eigenvalue”\n\n\n10:00am – 10:15am\nBreak\n\n\n10:15am – 11:15am\nCliff Taubes\, “The zero loci of Z/2 harmonic spinors in dimensions 2\, 3 and 4”\n\n\n11:15am – 11:30am\nBreak\n\n\n11:30am – 12:30pm\nTai-Peng Tsai\, “Forward Self-Similar and Discretely Self-Similar Solutions of the 3D incompressible Navier-Stokes Equations”\n\n\n\n* This event is sponsored by National Science Foundation (NSF) and CMSA Harvard University.
URL:https://cmsa.fas.harvard.edu/event/concluding-conference-of-the-special-program-on-nonlinear-equations-april-8-10-2016-2/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Conference,Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20151029T090000
DTEND;TZID=America/New_York:20151030T170000
DTSTAMP:20260502T021524
CREATED:20230717T180326Z
LAST-MODIFIED:20250304T180538Z
UID:10000014-1446109200-1446224400@cmsa.fas.harvard.edu
SUMMARY:Second Annual STAR Lab Conference
DESCRIPTION:The second annual STAR Lab conference is running 10/29/-10/30/2015 at the Harvard Business School.  This event is co-sponsored by the Center of Mathematical Sciences and Applications. \nFor more information\, please consult the event’s website.
URL:https://cmsa.fas.harvard.edu/event/second-annual-star-lab-conference-2/
LOCATION:20 Garden Street\, Cambridge\, MA 02138\, MA\, MA\, 02138\, United States
CATEGORIES:Conference,Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20150824T084500
DTEND;TZID=America/New_York:20150826T160000
DTSTAMP:20260502T021524
CREATED:20230717T180044Z
LAST-MODIFIED:20250304T180628Z
UID:10000013-1440405900-1440604800@cmsa.fas.harvard.edu
SUMMARY:2015 Conference on Big Data
DESCRIPTION:The Center of Mathematical Sciences and Applications will be having a conference on Big Data August 24-26\, 2015\, in Science Center Hall B at Harvard University.  This conference will feature many speakers from the Harvard Community as well as many scholars from across the globe\, with talks focusing on computer science\, statistics\, math and physics\, and economics.\n\n \nMonday\, August 24 \n\n\n\nTime\nSpeaker\nTitle\n\n\n8:45am\nMeet and Greet\n\n\n\n9:00am\nSendhil Mullainathan\nPrediction Problems in Social Science: Applications of Machine Learning to Policy and Behavioral Economics\n\n\n9:45am\nMike Luca\nDesigning Disclosure for the Digital Age\n\n\n10:30\nBreak\n\n\n\n10:45\nJianqing Fan\nBig Data Big Assumption: Spurious discoveries and endogeneity\n\n\n11:30am\nDaniel Goroff\nPrivacy and Reproducibility in Data Science\n\n\n12:15pm\nBreak for Lunch\n\n\n\n2:00pm\nRyan Adams\nExact Markov Chain Monte Carlo with Large Data\n\n\n2:45pm\nDavid Dunson\nScalable Bayes: Simple algorithms with guarantees\n\n\n3:30pm\nBreak\n\n\n\n3:45pm\nMichael Jordan\nComputational thinking\, inferential thinking and Big Data\n\n\n4:30pm\nJoel Tropp\nApplied Random Matrix Theory\n\n\n5:15pm\nDavid Woodruff\nInput Sparsity and Hardness for Robust Subspace Approximation\n\n\n\nTuesday\, August 25 \n\n\n\nTime\nSpeaker\nTitle\n\n\n8:45am\nMeet and Greet\n\n\n\n9:00am\nGunnar Carlsson\nPersistent homology for qualitative analysis and feature generation\n\n\n9:45am\nAndrea Montanari\nSemidefinite Programming Relaxations for Graph and Matrix Estimation: Algorithms and Phase Transitions\n\n\n10:30am\nBreak\n\n\n\n10:45am\nSusan Athey\nMachine Learning and Causal Inference for Policy Evaluation\n\n\n11:30am\nDenis Nekipelov\nRobust Empirical Evaluation of Large Competitive Markets\n\n\n12:15pm\nBreak for Lunch\n\n\n\n2:00pm\nLucy Colwell\nUsing evolutionary sequence variation to make inferences about protein structure and function: Modeling with Random Matrix Theory\n\n\n2:45pm\nSimona Cocco\nInverse Statistical Physics approaches for the modeling of protein families\n\n\n3:30pm\nBreak\n\n\n\n3:45pm\nRemi Monasson\nInference of top components of correlation matrices with prior informations\n\n\n4:30pm\nSayan Mukherjee\nRandom walks on simplicial complexes and higher order notions of spectral clustering\n\n\n\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \nA Banquet from 7:00 – 8:30pm will follow Tuesday’s talks. This event is by invitation only. \n Wednesday\, August 26  \n\n\n\nTime\nSpeaker\nTitle\n\n\n8:45am\nMeet and Greet\n\n\n\n9:00am\nAnkur Moitra\nBeyond Matrix Completion\n\n\n9:45am\nFlorent Krzakala\nOptimal compressed sensing with spatial coupling and message passing\n\n\n10:30am\nBreak\n\n\n\n10:45am\nPiotr Indyk\nFast Algorithms for Structured Sparsity\n\n\n11:30am\nGuido Imbens\nExact p-values for network inference\n\n\n12:15pm\nBreak for lunch\n\n\n\n2:00pm\nEdo Airoldi\nSome fundamental ideas for causal inference on large networks\n\n\n2:45pm\nRonitt Rubinfeld\nSomething for almost nothing: sublinear time approximation algorithms\n\n\n3:30pm\nBreak\n\n\n\n3:45pm\nLenka Zdeborova\nClustering of sparse networks:  Phase transitions and optimal algorithms\n\n\n4:30pm\nJelani Nelson\nDimensionality reductions via sparse matrices
URL:https://cmsa.fas.harvard.edu/event/conference-on-big-data-august-24-26-2015/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Big Data Conference,Conference,Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20140915T140000
DTEND;TZID=America/New_York:20140915T190000
DTSTAMP:20260502T021524
CREATED:20230717T180624Z
LAST-MODIFIED:20240209T214309Z
UID:10000011-1410789600-1410807600@cmsa.fas.harvard.edu
SUMMARY:Topological Insulators and Mathematical Science – Conference and Program
DESCRIPTION:The CMSA will be hosting a conference on the subject of topological insulators and mathematical science on September 15-17.  Seminars will take place each day from 2:00-7:00pm in Science Center Hall D\, 1 Oxford Street\, Cambridge\, MA.
URL:https://cmsa.fas.harvard.edu/event/topological-insulators-and-mathematical-science-conference-and-program/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Conference,Event
END:VEVENT
END:VCALENDAR