• May 16, 2023 09:00 AM
Speaker:
Title: GRAMSIA: Graphical Models, Statistical Inference, and Algorithms
Venue: CMSA Room G10

On May 16 – May 19, 2023 the CMSA hosted a four-day workshop on GRAMSIA: Graphical Models, Statistical Inference, and Algorithms. The workshop was held in room G10 of the CMSA, located at 20 Garden Street, Cambridge, MA. This workshop was organized by David Gamarnik (MIT), Kavita Ramanan (Brown), and Prasad Tetali  (Carnegie Mellon). The purpose of this workshop is to highlight various mathematical questions and issues associated with graphical models and message-passing algorithms, and to bring together a group of researchers for discussion of the latest progress and challenges ahead. In addition to the substantial impact of graphical models on applied areas, they are also connected to various branches of the mathematical sciences. Rather than focusing on…

  • May 07, 2023 09:00 AM
Speaker:
Title: Workshop on Global Categorical Symmetries
Venue: CMSA Room G10

The CMSA will be hosting a Workshop on Global Categorical Symmetries from May 7 – 12, 2023 Participation in the workshop is by invitation. Public Lectures There will be three lectures on Thursday, May 11, 2023, which are open to the public. Location:  Room G-10, CMSA, 20 Garden Street, Cambridge MA 02138 Note: The public lectures will be held in-person only. 2:00 – 2:50 pm Speaker: Kantaro Ohmori (U Tokyo ) Title: Fusion Surface Models: 2+1d Lattice Models from Higher Categories Abstract: Generalized symmetry in general dimensions is expected to be described by higher categories. Conversely, one might expect that, given a higher category with appropriate structures, there exist models that admit the category as its symmetry. In this talk I will explain a construction…

  • February 09, 2023 03:30 PM
Speaker: Nazim Bouatta
Title: Special Lectures on Machine Learning and Protein Folding
Venue: CMSA Room G10

The CMSA will host a series of three 90-minute lectures on the subject of machine learning for protein folding. Thursday Feb. 9, Thursday Feb. 16, & Thursday March 9, 2023, 3:30-5:00 pm ET Location: G10, CMSA, 20 Garden Street, Cambridge MA 02138 Directions and Recommended Lodging These special lectures will be hybrid:  they will be both in-person and online. Registration is required. In-person registration Zoom webinar registration form: Zoom Webinar.   Speaker: Nazim Bouatta, Harvard Medical School Abstract: AlphaFold2, a neural network-based model which predicts protein structures from amino acid sequences, is revolutionizing the field of structural biology. This lecture series, given by a leader of the OpenFold project which created an open-source version of AlphaFold2, will explain the…

  • November 28, 2022 09:00 AM
Speaker:
Title: Representation Theory, Calabi–Yau Manifolds, and Mirror Symmetry
Venue: CMSA Room G10

Videos are available on the CMSA Youtube Playlist. On November 28 – Dec 1, 2022, the CMSA hosted a Workshop on Representation Theory, Calabi-Yau Manifolds, and Mirror Symmetry. Organizers: An Huang (Brandeis University) | Siu-Cheong Lau (Boston University) | Tsung-Ju Lee (CMSA, Harvard) | Andrew Linshaw (University of Denver) Scientific Advisor: Shing-Tung Yau (Harvard, Tsinghua) Location: Room G10, CMSA, 20 Garden Street, Cambridge MA 02138 Directions and Recommended Lodging The conference was held in hybrid format, both in-person and online. The workshop was partially supported by Simons and NSF Grant DMS-2227199.   Speakers:  Tomoyuki Arakawa (Kyoto) Thomas Creutzig (Edmonton) Jonathan Mboyo Esole (Northeastern) Fei Han (National University of Singapore) Shinobu Hosono (Gakushuin University) Flor Orosz Hunziker (Colorado) Cuipo Jiang…

  • August 02, 2022 09:00 AM
Speaker:
Title: Phase Transitions and Topological Defects in the Early Universe
Venue: CMSA Room G10

On August 2–5, the CMSA hosted a workshop on Phase Transitions and Topological Defects in the Early Universe. The workshop was held in room G10 of the CMSA, located at 20 Garden Street, Cambridge, MA and online via Zoom webinar. The next decade will see a wealth of new cosmological data, which can lead to new insights into fundamental physics. Upcoming facilities (such as LISA) will be able to probe signals of fascinating phenomena in the early universe. These include signals from “Phase Transitions and Topological Defects,” which are ubiquitously given rise to in well-motivated UV models. In-depth studies of such signals requires cross-talks between experts from a wide spectrum of fields. The workshop aims to provide a platform for efficient exchange of…

  • May 06, 2022 10:00 AM
Speaker:
Title: 2022 NSF FRG Workshop on Discrete Shapes
Venue: Virtual

On May 6–8, 2022, the CMSA  hosted a second NSF FRG Workshop. This project brings together a community of researchers who develop theoretical and computational models to characterize shapes. Their combined interests span Mathematics (Geometry and Topology), Computer Science (Scientific Computing and Complexity Theory), and domain sciences, from Data Sciences to Computational Biology. Scientific research benefits from the development of an ever-growing number of sensors that are able to capture details of the world at increasingly fine resolutions. The seemingly unlimited breadth and depth of these sources provide the means to study complex systems in a more comprehensive way. At the same time, however, these sensors are generating a huge amount of data that comes with a high…

  • May 02, 2022 09:00 AM
Speaker:
Title: General Relativity Workshop
Venue: Virtual

General Relativity Workshop on scalar curvature, minimal surfaces, and initial data sets Dates: May 2–5, 2022 Location: Room G10, CMSA, 20 Garden Street, Cambridge MA 02138 and via Zoom webinar. Advanced registration for in-person components is required. Organizers: Dan Lee (CMSA/CUNY), Martin Lesourd (CMSA/BHI), and Lan-Hsuan Huang (University of Connecticut). Speakers: Zhongshan An, University of Connecticut Paula Burkhardt-Guim, NYU Hyun Chul Jang, University of Miami Chao Li, NYU Christos Mantoulidis, Rice University Robin Neumayer, Carnegie Mellon University Andre Neves, University of Chicago Tristan Ozuch, MIT Annachiara Piubello, University of Miami Antoine Song, UC Berkeley Tin-Yau Tsang, UC Irvine Ryan Unger, Princeton Zhizhang Xie, Texas A & M Xin Zhou, Cornell University Jonathan Zhu, Princeton University Schedule Download PDF Monday,…

  • April 27, 2022 09:00 AM
Speaker:
Title: Workshop on Nonlinear Algebra and Combinatorics from Physics
Venue: Virtual

On April 27–29, 2022, the CMSA hosted a workshop on Nonlinear Algebra and Combinatorics. Organizers: Bernd Sturmfels (MPI Leipzig) and Lauren Williams (Harvard). In recent years, ideas from integrable systems and scattering amplitudes have led to advances in nonlinear algebra and combinatorics. In this short workshop, aimed at younger participants in the field, we will explore some of the interactions between the above topics. Speakers: Federico Ardila (San Francisco State) Nima Arkani-Hamed (IAS) Madeline Brandt (Brown) Nick Early (Max Planck Institute) Chris Eur (Harvard) Claudia Fevola (Max Planck Institute) Christian Gaetz (Harvard) Yuji Kodama (Ohio State University) Yelena Mandelshtam (Berkeley) Sebastian Mizera (IAS) Matteo Parisi (Harvard CMSA) Emma Previato (Boston University) Anna Seigal (Harvard) Melissa Sherman-Bennett (University of Michigan)…

  • April 15, 2022 09:00 AM
Speaker:
Title: Workshop on Machine Learning and Mathematical Conjecture
Venue: CMSA Room G10

On April 15, 2022, the CMSA will hold a one-day workshop, Machine Learning and Mathematical Conjecture, related to the New Technologies in Mathematics Seminar Series. Location: Room G10, 20 Garden Street, Cambridge, MA 02138. Organizers: Michael R. Douglas (CMSA/Stony Brook/IAIFI) and Peter Chin (CMSA/BU). Machine learning has driven many exciting recent scientific advances. It has enabled progress on long-standing challenges such as protein folding, and it has helped mathematicians and mathematical physicists create new conjectures and theorems in knot theory, algebraic geometry, and representation theory. At this workshop, we will bring together mathematicians, theoretical physicists, and machine learning researchers to review the state of the art in machine learning, discuss how ML results can be used to inspire, test…