Programs and Clusters
Programs and Clusters
The Institute typically hosts two concurrent research programs per semester, and one per summer. Programs are selected with a view toward maximizing impact and engagement across the theoretical computer science community, as well as impact on neighboring scientific fields. A typical program is led by a small group of organizers who are recognized experts in their fields, and involves about 60–70 long-term participants (a mix of senior and junior researchers) who spend a month or longer at the Institute. A program usually includes three week-long topical workshops, each of which attracts an additional group of invited speakers and focuses on a different aspect of the program's scientific scope, as well as an initial boot camp designed to put long-term participants on the same page. Summer clusters are somewhat smaller in scale than research programs, and are designed to offer a platform for focused research on fast-moving or emerging topics.
This program studies the interaction between logic and the algorithms that they inspire, with applications to databases, complexity theory, and knowledge representation.
This program will bring together researchers in dynamic graphs, sketching, and optimization towards the common goals of obtaining provably faster algorithms, finding new connections between the areas, and making new advances at their intersection....
This program will bring together researchers in dynamic graphs, sketching, and optimization towards the common goals of obtaining provably faster algorithms, finding new connections between the areas, and making new advances at their intersection.
This program will bring together researchers from computer science, physics, chemistry, and mathematics to address current challenges in quantum computing, such as the efficiency of protocols for fault-tolerant quantum computation, scalable proofs of quantumness, demonstrations of quantum advantage, and the development of quantum algorithms.
This cluster brings together AI, Psychology, and Neuroscience researchers dedicated to discovering the pillars of intelligence. The goal is twofold: to understand and model natural forms of intelligence using tools from AI and to build AI grounded in the real world.
This extended month-long reunion is for long-term participants from the program on the Theoretical Foundations of Computer Systems, held in the spring 2021 semester.
This program will taxonomize and analyze areas of contemporary machine learning where methods generalize well — meaning they perform eerily well on new inputs, rather than merely performing well on old inputs they were trained on — but for no known mathematical reason.
The Simons Institute for the Theory of Computing offers numerous ways for scientists to participate in the life of the Institute.
- Applications for the Simons Quantum Postdoctoral Fellowships.
- Applications for Science Communicators in Residence for Summer 2022, Fall 2022, and Spring 2023.
This extended reunion is for long-term participants in the program Satisfiability: Theory, Practice, and Beyond, held in the Spring 2021 semester. It will provide an opportunity to meet old and new friends. Moreover, we hope that it will give everyone a chance to reflect on the progress made during the semester and since, and sketch in which directions the field should go in the future.
This program will bring together researchers in computational complexity, proof complexity, cryptography, and learning theory to make progress on fundamental problems in those areas using the framework of "meta-complexity" — i.e., complexity of computational tasks that are themselves about complexity.
This program will bring together experts from various fields to study networks, from graph limits, to modeling and estimation, to processes on networks. Application areas include epidemics, spread of information and other economic and social processes.
This program brings together researchers in complexity theory, algorithms, statistics, learning theory, probability, and information theory to advance the methodology for reasoning about the computational complexity of statistical estimation problems.
This program aims to advance our understanding of high-dimensional problems by focusing on the interplay between probability, geometry, and computation.