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.
Current Programs
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...
This is the first part in a special, yearlong program on large language models and transformers that spans the 2024–2025 academic year. This program's overarching goal is to try to understand the ongoing revolution in transformers and large language...
Spring 2022
Fall 2021
This program aims to develop a geometric approach to various computational problems in sampling, optimization, and partial differential equations.
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.
Spring 2021
Focusing on new developments in logic, automata, probabilistic modeling, games, and cyber-physical systems, this program aims to develop the theoretical foundations of computer systems.
This program aims to foster interaction between theoreticians and practitioners to understand real-world efficient computation with a particular focus on the satisfiability problem for Boolean formulas.
Fall 2020
This program aims to advance our understanding of high-dimensional problems by focusing on the interplay between probability, geometry, and computation.
This program will bring together researchers in computer science, control theory, operations research and statistics to advance the theoretical foundations of reinforcement learning.
Spring 2020
This program will study fundamental questions on integer lattices and their important role in cryptography and quantum computation, bringing together researchers from number theory, algorithms, optimization, cryptography, and coding theory.
This program will bring together researchers from computer science, physics, chemistry and mathematics to focus on the two grand challenges of quantum computation: developing the most promising algorithmic applications for quantum computers, and developing methods to test quantum devices.
Fall 2019
This short-format program will focus on the design of markets for online platforms, exploiting advances in theoretical computer science, economics and operations research.
This program will bring together researchers from Computer Science and beyond, whose research is contributing to three subthemes: proof systems, decentralized consensus, and applications of these to society, economics, and cryptocurrencies.
Summer 2019
This program will bring together researchers from academia and industry to develop empirically-relevant theoretical foundations of deep learning, with the aim of guiding the real-world use of deep learning.
Spring 2019
This program aims to promote research on the theoretical foundations of data privacy, as well as on applications in technical, legal, social and ethical spheres.
This program will focus on emerging connections between the analytic theory of multivariate polynomials (sometimes called "the geometry of polynomials") and theoretical computer science as well as related fields such as combinatorics, probability, statistical physics, optimization and real algebraic geometry.
Fall 2018
This program will bring together leading researchers in computational complexity theory to tackle fundamental questions on the capabilities and limitations of various models of computation.
Taking inspiration from the areas of algorithms, statistics, and applied mathematics, this program aims to identify a set of core techniques and principles for modern Data Science.
