MSRI / SLMath: 2023 Summer Graduate School Nominations
Nominations open on December 1, 2022
|
|
|
|
Every summer, SLMath organizes several summer graduate schools (usually two weeks each), held in Berkeley, California and at partner institutions worldwide. Attending one of these schools can be a very motivating and exciting experience for a student; participants have often said that it was the first experience where they felt like real mathematicians, interacting with other students and mathematicians in their field.
|
|
The nomination period for the 2023 Summer Graduate Schools will begin at 10:00 a.m. Pacific Time on December 1, 2022 and will continue until filled or no later than February 1, 2023.
We appreciate your help in identifying students who can benefit from attending these schools. (Download a PDF flyer to share)
|
|
|
ELIGIBILITY
Graduate students from SLMath Academic Sponsoring Institutions or from the mathematics department of any U.S. institution are eligible to apply. (Learn more)
Students from groups underrepresented in the mathematical sciences (including women and gender-expansive individuals) are particularly encouraged to apply.
HOW TO APPLY
Graduate students must be nominated by their Director of Graduate Studies. The Director of Graduate Studies submits a ranked list of nominations for their institution online during the enrollment period. Nominations will be accepted beginning at 10:00am Pacific Time on December 1, 2022.
ENROLLMENT PERIOD
December 1, 2022 - February 1, 2023
ADMISSION
Admission is on a first-come, first-served basis up to the limits of the capacity of the school. Early nominations are not accepted.
FINANCIAL SUPPORT
SLMath covers local expenses as well as partial travel expenses for accepted students.
|
|
|
California Summer Schools
|
|
|
June 5 - June 16, 2023 · MSRI/SLMath, Berkeley ★
Formalization of Mathematics
Computational proof assistants now make it possible to develop global, digital mathematical libraries with theorems that are fully checked by computer. This summer school will introduce students to the new technology and the ideas behind it, and will encourage them to think about the goals and benefits of formalized mathematics. Students will learn to use the Lean interactive proof assistant, and by the end of the session they will be in a position to formalize mathematics on their own, join the Lean community, and contribute to its mathematical library. (Learn more)
Organizers: Jeremy Avigad (Carnegie Mellon University), Heather Macbeth (Fordham University), Patrick Massot (Université Paris-Saclay)
|
|
|
June 12 - June 23, 2023 · University of California, San Diego
Machine Learning
The overarching goal of this summer school is to expose the students both to modern forms of unsupervised learning — in the form of geometrical and topological data analysis — and to supervised learning — in the form of (deep) neural networks applied to regression/classification problems. The organizers have opted for a lighter exposure to a broader range of topics: geometry and topology for data analysis, and theoretical and practical deep learning, with a goal to inspire the students to learn more. The expected learning outcomes for students attending the school are (1) an introduction to how concepts and tools from geometry and topology can be leveraged to perform data analysis in situations where the data are not labeled, and (2) an introduction to recent and ongoing theoretical and methodological/practical developments in the use of neural networks for data analysis (deep learning). (Learn more)
Organizers: Ery Arias-Castro (University of California, San Diego), Mikhail Belkin (University of California, San Diego), Yusu Wang (Univ. California, San Diego), Lily Weng (University of California, San Diego)
|
|
|
June 20 - June 30, 2023 · MSRI/SLMath, Berkeley ★
Mathematics and Computer Science of Market and Mechanism Design
This school is associated with an upcoming research program at SLMath under the same title. The goal of the school is to equip students unfamiliar with these topics with the mathematical and theoretical computer science toolbox that forms the foundation of market and mechanism design. (Learn more)
Organizers: Yannai Gonczarowski (Harvard University), Irene Yuan Lo (Stanford University), Ran Shorrer (Pennsylvania State University), Inbal Talgam-Cohen* (Technion - Israel Institute of Technology)
* indicates lead organizer(s)
|
|
|
June 20 - June 30, 2023 · St. Mary's College, Moraga
Topics in Geometric Flows and Minimal Surfaces
This graduate summer school will introduce students to two important and inter-related fields of differential geometry: geometric flows and minimal surfaces. The curriculum of this program will be accessible and will have a broad appeal to graduate students from a variety of mathematical areas, introducing some of the latest developments in each area and the remaining open problems therein, while simultaneously emphasizing their synergy. (Learn more)
Organizers: Ailana Fraser (University of British Columbia), Lan-Hsuan Huang (University of Connecticut), Catherine Searle (Wichita State University), Lu Wang (Yale University)
|
|
|
June 26 - July 7, 2023 · University of California, Berkeley
Introduction to Derived Algebraic Geometry
Derived algebraic geometry is an "update" of algebraic geometry using "derived" (roughly speaking, homological) techniques. This requires recasting the very foundations of the field: rings have to be replaced by differential graded algebras (or other forms of derived rings), categories by higher categories, and so on. The result is a powerful set of new tools, useful both within algebraic geometry and in related areas. The school serves as an introduction to these techniques, focusing on their applications. (Learn more)
Organizers: Benjamin Antieau (Northwestern University), Dmytro Arinkin (University of Wisconsin-Madison)
|
|
|
July 3 - July 14, 2023 · MSRI/SLMath, Berkeley ★
Concentration Inequalities and Localization Techniques in High Dimensional Probability and Geometry
The goal of the summer school is for the students to first become familiar with the concept of concentration of measure in different settings (Euclidean, Riemannian and discrete), and the main open problems surrounding it. The students will later become familiar with the proof techniques that involve the different types of localization and obtain expertise on the ways to apply the localization techniques. After attending the graduate school, the students are expected to have the necessary background that would give them a chance to both conduct research around open problems in concentration of measure, find new applications to existing localization techniques and perhaps also develop new localization techniques. (Learn more)
Organizers: Max Fathi (Université Paris Cité), Dan Mikulincer (Massachusetts Institute of Technology)
|
|
|
July 10 - July 21, 2023 · IBM Research - Almaden, San Jose
Mathematics of Big Data: Sketching and (Multi-) Linear Algebra
This summer school will introduce graduate students to sketching-based approaches to computational linear and multi-linear algebra. Sketching here refers to a set of techniques for compressing a matrix, to one with fewer rows, or columns, or entries, usually via various kinds of random linear maps. We will discuss matrix computations, tensor algebras, and such sketching techniques, together with their applications and analysis. (Learn more)
Organizers: Kenneth Clarkson (IBM Research Division), Lior Horesh (IBM Thomas J. Watson Research Center), Misha Kilmer (Tufts University), Tamara Kolda (MathSci.ai), Shashanka Ubaru (IBM Thomas J. Watson Research Center)
|
|
Other Locations (USA & Worldwide)
|
|
|
May 22 - June 2, 2023 · Indiana, USA: University of Notre Dame
Commutative Algebra and Its Interaction with Algebraic Geometry
Commutative Algebra has seen an extraordinary development in the last few years. Long standing conjectures have been proven and new connections to different areas of mathematics have been built.This summer graduate school will consist of three mini-courses (5 lectures each) on fundamental topics in commutative algebra that are not covered in the standard courses. Each course will be accompanied by problem sessions focused on research. Five general colloquium-style lectures will be given by invited scholars who will also attend the school and help with afternoon research activities. (Learn more)
Organizers: Steven Cutkosky (University of Missouri), Claudia Polini* (University of Notre Dame), Claudiu Raicu (University of Notre Dame), Steven Sam (University of California, San Diego), Kevin Tucker (University of Illinois at Chicago)
|
|
|
June 12 - June 23, 2023 · Leipzig, Germany: Max Planck Institute for Mathematics in the Sciences
Algebraic Methods for Biochemical Reaction Networks
The aim of the course is to learn how tools from algebraic geometry (in particular, from computational and real algebraic geometry) can be used to analyze standard models in molecular biology. We will focus on the mathematical aspects of the methods, and exemplify and apply the theory to real networks, thereby introducing the participants to relevant problems and mechanisms in molecular biology. As a counterpart, however, the participants will also see how this field has in the past challenged current methods, mainly in the realm of real algebraic geometry, and has given rise to new general and purely theoretical results on polynomial equations. We will end with an overview of open questions in both fields. (Learn more)
Organizers: Timo de Wolff (TU Berlin), Alicia Dickenstein* (University of Buenos Aires), Elisenda Feliu (University of Copenhagen)
|
|
|
June 19 - June 30, 2023 · Montréal, Canada: Université de Montréal
Séminaire de Mathématiques Supérieures 2023: Periodic and Ergodic Spectral Problems
This two week school will focus on spectral theory of periodic, almost-periodic, and random operators. The main aim of this school is to teach the students who work in one of these areas, methods used in parallel problems, explain the similarities between all these areas and show them the "big picture". (Learn more)
Organizers: Alexander Elgart (Virginia Polytechnic Institute and State University), Vojkan Jaksic (McGill University), Svetlana Jitomirskaya (University of California, Irvine), Ilya Kachkovskiy (Michigan State University), Jean Lagacé (King's College London), Leonid Parnovski (University College London)
|
|
|
Dates TBA · Zürich, Switzerland
Foundations and Frontiers of Probabilistic Proofs
Proofs are at the foundations of mathematics. Viewed through the lens of theoretical computer science, verifying the correctness of a mathematical proof is a fundamental computational task. Indeed, the P versus NP problem, which deals precisely with the complexity of proof verification, is one of the most important open problems in all of mathematics.The complexity-theoretic study of proof verification has led to exciting reenvisionings of mathematical proofs. In recent years, probabilistic proofs have received much attention due to a new motivation, delegation of computation, which is the emphasis of this summer school. This paradigm admits ultra-fast protocols that allow one party to check the correctness of the computation performed by another, untrusted, party. This summer school will provide an introduction to the field of probabilistic proofs and the beautiful mathematics behind it, as well as prepare students for conducting cutting-edge research in this area. (Learn more)
Organizer: Alessandro Chiesa (University of California, Berkeley))
|
|
|
MSRI / SLMath has been supported from its origins by the National Science Foundation, now joined by the National Security Agency, over 100 Academic Sponsor departments, by a range of private foundations, and by generous and farsighted individuals.
|
|
|
|
|
|
