For Massachusetts Space Week... Be a planetary explorer!Join EAPS Professor Post-Tenure Richard Binzel as your guide for a tour of our Solar System, from the Sun to Pluto, precisely scaled to the length of MIT’s Infinite Corridor!Please register for tickets for one of the following times — Space is limited!Friday, April 25 — 11:00 a.m.Friday, April 25 — 3:00 p.m.Saturday, April 26 — 9:00 a.m.Saturday, April 26 — 12:30 p.m.Saturday, April 26 — 3:00 p.m.Sunday, April 27 — 11:00 a.m.Sunday, April 27 — 12:30 p.m.Learn more and follow the tour with the Infinite Solar System Online Guide — mobile phone and tablet-friendly! Starting point of the tour is the third floor lobby of MIT’s Building 7.Can’t join us for a guided tour? No problem! You can take a self-guided tour anytime during MIT visiting hours.Questions about the tours? Contact Allison DrovairosWhat is Massachusetts Space Week, organized by the Space Consortium?Massachusetts Space Week is an annual, week-long celebration that seeks to bridge the gap between academia and the broader community and to foster a shared enthusiasm for space science, through engaging events such as a Space Film Festival, a Space Career Fair, and more than 80 space events statewide.Launched in 2017, The Space Consortium is an MA-based 501(c)(3) non-profit led by academics and researchers working in space-related fields which organizes a series of space education & outreach initiatives, including Massachusetts Space Week and The Space Consortium (SC) Space Days, to help democratize space knowledge and connect MA-based space experts and enthusiasts with each other and with the public. Supported by the Massachusetts Space Grant, Massachusetts Space Week and The SC Space Days stand as testaments to grassroots collaboration & community effort among space experts across the state, aiming to make space science accessible to all.

Presented by the Emerson/Harris Program for Private Study Solo Recital SeriesProgramTBDLivestream: https://mta.mit.edu/viewlisten/live-killian-hallAbout the PerformersAbout the Emerson/Harris Program for Private StudySupport for private musical study is available for students through the Emerson/Harris Program (E/HP), which offers merit-based financial awards for outstanding achievement on instruments or voice in classical, jazz, or world music. Each academic year, the program awards Scholarships and Fellowships to nearly seventy students who commit to a full year’s study and participate in the musical life of MIT.Auditions for the program are held at the beginning of each academic year. Private teacher selections, made in consultation with the E/HP jury heads, may include instructors from MIT staff and throughout Greater Boston. The Emerson/Harris Program is funded by the late Mr. Cherry L. Emerson, Jr. (SM, 1941), in response to an appeal from AssociateProvost Ellen T. Harris (Class of 1949 Professor Emeritus of Music). The Emerson/Harris Masterclass Series is supported, in part, by the Robert L. Malster (1956) Fund.This project is presented as part of Artfinity, an Institute-sponsored event celebrating creativity and community at MIT. Artfinity is organized by the Office of the Arts.

Speaker: Fedor Nazarov (Kent State University)Title: The quasi-monotonicity property for eigenfunctions of the Laplacian on smooth Riemannian manifolds.Abstract:We'll discuss a very simple but quite powerful idea that allows one to recover several classical results about the behavior of the eigenfunctions and to obtain a couple of new ones. This is a work in progress with Eugenia Malinnikova and Stefano Decio.--*Note the unique day and location*

Time: 3:00 PMLocation: Cambridge, MA

Title: The Insecurity of Machine LearningAbstract: The development of deep neural networks in the last decade had revolutionized machine learning and led to major improvements in our ability to perform many computational and cognitive tasks. However, this was accompanied by the discovery that deep neural networks are extremely fragile, and it is very easy to fool any neural network by making tiny changes in its inputs. These adversarial examples make it difficult to trust the results of such computations when the input can be manipulated by an adversary, and this problem has many applications and implications in object recognition, autonomous driving, cyber security, etc.In this talk I will describe a simple conceptual framework which enables us to think about this surprising phenomena from a fresh perspective, turning the existence of adversarial examples in deep neural networks from a baffling mystery into an unavoidable consequence of the geometry of the high dimensional input space. Time permitting, I will then describe several other surprising results on the security of deep neural networks, including how one can backdoor state of the art facial recognition systems by mathematically modifying a small fraction of their weights, and how one can efficiently extract all the weights of a network by analyzing its answers for a small number of chosen queries.

Time: 4:00 PMLocation: Cambridge, MA