DIMACS | Center for Discrete Mathematics and Theoretical Computer Science
The DIMACS Implementation Challenges help understand and improve the practical performance of algorithms for important problems, particularly those that are hard in the theoretical sense.
The Mathematics of Planet Earth project brings mathematicians together with other scientists to help humanity understand environmental impacts, manage limited resources, and prepare for future changes and disasters.
Reconnect is a long-running program at DIMACS that features summer workshops on a chosen topical theme.
The PS-Future project uses sustainability lessons for high school students to build STEM skills, introduce related careers, and encourage a diverse group of learners to take part in sustainability issues.
The DIMACS Leadership Program trained about 1,600 K–8 teachers to teach discrete mathematics. It also created workshops and classroom materials that help students build reasoning and problem-solving skills.
The CS Living-Learning Community offered first-year Rutgers women housing, mentoring, and computer science opportunities; its page is outdated, so check the STEM Living-Learning Communities website.
From 2016 to 2019, this DIMACS initiative brought researchers together to improve big data privacy and security.
From 2015 to 2020, the DIMACS Special Focus brought researchers together to develop secure, practical cryptography for modern computing.
From 2024 to 2027, this DIMACS program brings researchers and graduate students together to study how fast algorithms can solve large problems.
From 2019 to 2024, DIMACS brought researchers together to study the minimum resources computers need to solve problems.
From 2019 to 2025, this DIMACS program studied how to combine human judgment and machine predictions to make fairer decisions.
From 2018 to 2023, this DIMACS program brought researchers together to improve optimization methods for problems such as supply chains, traffic, and machine learning.
DATA-INSPIRE brings researchers together to improve how intelligent machines learn, work, and interact with people.
