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November 2020

MCAIM Colloquium

November 18, 2020 @ 4:00 pm - 5:00 pm

Gigliola Staffilani, Massachusetts Institute of Technology (MIT) Title: The many faces of dispersive equations. Abstract: In recent years great progress has been made in the study of dispersive and wave equations.  Over the years the toolbox used in order to attack highly nontrivial problems related to these equations has developed to include a variety of techniques from Fourier and harmonic analysis, analytic number theory, math physics, dynamical systems, probability and symplectic geometry. In this talk I will introduce a variety of problems connected…

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December 2020

MCAIM Colloquium

December 2, 2020 @ 4:00 pm - 5:00 pm

Josselin Garnier, Ecole Polytechnique, France Title: Passive imaging and communication Abstract: In this talk we consider the propagation of waves transmitted by ambient noise sources. We discuss a generalized Helmholtz-Kirchhoff identity that derives from Green’s identity and Sommerfeld radiation condition. The inspection of this identity makes it possible to design passive imaging methods, i.e., imaging methods using only passive receiver arrays and ambient noise illumination. More surprisingly, it is also possible to design an original passive communication scheme between two passive arrays that…

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January 2021

MCAIM Graduate Seminar

January 25 @ 4:00 pm - 5:00 pm
Online Via Zoom

Speaker: Saibal De   Title: Quantum Computing for Continuous Optimization Problems   Abstract: Optimization is one of the most common learning tasks in many scientific and industrial applications. However, in many cases, these problems are so large and complex that it takes days, if not weeks, to obtain an answer even with the fastest supercomputers. Quantum computing has recently attracted a lot of attention based on its potential for accelerating specific computational tasks well beyond classical means. For instance, last year Google AI…

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MCAIM Graduate Seminar

January 25 @ 4:00 pm - 5:00 pm
Online Via Zoom

Speaker: Saibal De Title: Quantum Computing for Continuous Optimization Problems Abstract: Optimization is one of the most common learning tasks in many scientific and industrial applications. However, in many cases, these problems are so large and complex that it takes days, if not weeks, to obtain an answer even with the fastest supercomputers. Quantum computing has recently attracted a lot of attention based on its potential for accelerating specific computational tasks well beyond classical means. For instance, last year Google…

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February 2021

Graduate Seminar – The Cauchy Problem for the Einstein Equations

February 15 @ 4:00 pm - 5:00 pm
Online Via Zoom

Speaker: Chris Stith Title; The Cauchy Problem for the Einstein Equations Abstract: The Einstein equations are a system of PDE governing the curvature of a pseudo-Riemannian manifold (spacetime). It is natural to ask if these equations have a formulation as an initial value problem, and if they can be solved in this context. The full answer to this question arose more than 30 years after Einstein first wrote down the equations; in this talk we will discuss Choquet-Bruhat's breakthrough work…

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March 2021

Corinna Ulcigrai, University of Zurich – MCAIM Colloquium

March 10 @ 4:00 pm - 5:00 pm
Online Via Zoom

Speaker: Corinna Ulcigrai, University of Zurich, Institute for Mathematics Title: Slowly Chaotic Behavior Abstract: How can we understand chaotic behavior mathematically? A well popularized feature of chaotic systems is the butterfly effect: a small variation of initial conditions may lead to a drastically different future evolution, a mechanism at the base of the so-called ‘deterministic chaos’. We will introduce and focus on ‘slowly chaotic’ dynamical systems’, for which the butterfly effect happens “slowly” (e.g. at polynomial speed). These include many fundamental examples…

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Bärbel Finkenstädt Rand, University of Warwick – MCAIM Colloquium

March 31 @ 4:00 pm - 5:00 pm
Online Via Zoom

Bärbel Finkenstädt Rand, University of Warwick, Department of Statistics Title: Inference for Circadian Pacemaking Abstract: Organisms have evolved an internal biological clock which allows them to temporally regulate and organize their physiological and behavioral responses to cope in an optimal way with the fundamentally periodic nature of the environment. It is now well established that the molecular genetics of such rhythms within the cell consist of interwoven transcriptional-translational feedback loops involving about 15 clock genes, which generate circa 24-h oscillations in many…

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April 2021

Mete Soner, Princeton University – MCAIM Colloquium

April 7 @ 4:00 pm - 5:00 pm
Online Via Zoom

Mete Soner, Princeton University, Department of Operations Research and Financial Engineering Title: Deep Neural Networks for High-dimensional Uncertain Decision Problems Abstract:  Stochastic optimal control has been an effective tool for many decision problems. Although, they provide the much needed quantitative modeling for such problems, until recently they have been numerically intractable in high-dimensional settings. However, several recent studies that use deep neural networks report impressive numerical results in high dimensions when the structure of the uncertainty is assumed to be…

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Sheperd S. Doeleman, Harvard University – MCAIM Colloquium

April 14 @ 4:00 pm - 5:00 pm
Online Via Zoom

Speaker: Sheperd S. Doeleman, Founding Director of the Event Horizon Telescope, Harvard University, Center for Astrophysics, Harvard and Smithsonian, Black Hole Initiative Title: Black Hole Imaging: First Results and Future Vision Abstract: In April 2017, the Event Horizon Telescope (EHT) carried out a global Very Long Baseline Interferometry (VLBI) observing campaign at a wavelength of 1mm that led to the first resolved image of a supermassive black hole. For the 6.5 billion solar mass black hole in the giant elliptical…

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September 2021

Gérard Ben Arous, The Courant Institute – MCAIM Colloquium

September 15 @ 4:00 pm - 5:00 pm
Online Via Zoom

Speaker: Gérard Ben Arous, The Courant Institute Title: Topological Complexity and Optimization of High Dimensional Random Functions Abstract: Smooth random functions of very many variables can be topologically very complex, and thus it can be terribly hard to find their minimum.One does not need to look very far for such an example: pick at random a homogeneous polynomial of degree p (with p larger than 3) of a large number of variables and restrict it to the (high-dimensional) unit sphere.…

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