Special Quarters

The primary activity of the institute are thematically focused quarters which will coordinate graduate course work, visiting predoctoral fellows, workshops, and external visitors.

Are you either a current participant or someone looking to participate in the special quarters? Find out more about joining in on the participate page.

Spring 2020

Inference and Data Science on Networks

March 30 – June 6, 2020

Over the past decade or so, many diverse communities have become increasingly interested in networks as a way of understanding the role of interconnections between various entities.

Learn More About the Spring 2020 Special Quarter >>

Fall 2020

Theory of Deep Learning

September 15  – December 12, 2020

Deep learning plays a central role in the recent revolution of artificial intelligence and data science. In a wide range of applications, such as computer vision, natural language processing, and robotics, deep learning achieves dramatic performance improvements over existing baselines and even human.

Learn More About the Fall 2020 Special Quarter >>

Spring 2021

Algorithms for Partially Identified Models

Empirical analysis in economics most often involves a model that describes how agents behave in a market, data on their actions and characteristics, and a set of assumptions. The partial identification approach to econometrics recognizes that some assumptions are plausible – e.g., based on economic principles that respect optimizing behavior – while some are made out of convenience.

Learn More About the Spring 2021 Special Quarter >>

Fall 2021

Robustness in High-dimensional Statistics

Today’s data pose unprecedented challenges to statisticians and data analysts. It may be incomplete, corrupted, or exposed to some unknown source of contamination. We need new methods and theories to grapple with these challenges.

Learn More About the Fall 2021 Special Quarter >>

Spring 2022

High Dimensional Data Analysis

Today, machine learning and data science deal with tremendous amounts of high-dimensional data. Processing these data requires extensive computational resources (these often include large CPU and GPU clusters). It is expected that the amount of collected and analyzed data will grow significantly in the coming years.

Learn More About the Spring 2022 Special Quarter >>

Fall 2022

Incentives in Shared Data Infrastructure

Data analysis is playing an increasingly central role in many scientific disciplines, engineering advances, commercial enterprises, and processes with societal implications. In many of these applications, data is becoming a precious resource that is generated, shared, stored and analyzed by multiple individuals with differing motivations, interests, coordination and levels of trust in each other.

Learn More About the Fall 2022 Special Quarter >>