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Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

CCC Weekly Computing News: NCSA Gives Students Opportunities to Learn About Machine and Deep Learning

August 23rd, 2024 / in AI, CCC / by Petruce Jean-Charles

In this installment of CCC’s Weekly Computing News, we are sharing an exciting opportunity for undergraduate students across the country to work on cutting-edge research projects at the National Center for Supercomputing Applications (NCSA) at the University of Illinois Urbana-Champaign.

Students dive deep into machine learning and deep learning

The Research Experience for Undergraduates (REU) The Future of Discovery: Training Students to Build and Apply Open Source Machine Learning Models and Tools (FoDOMMaT) program offers an immersive 10-week experience every summer for undergraduates eager to develop practical skills and contribute to real-world projects.

Students are paired with two mentors, one focused on research and the other on machine learning expertise. The program starts with an intense, week-long crash course in AI and ML, aimed at students with basic programming and math skills. Following this foundational training, students spend several weeks on exploratory data analysis to deeply understand their research data.

Under the direction of Volodymyr Kindratenko, director of the Center for Artificial Intelligence Innovation, and with support from Dan Katz, chief scientist at NCSA, the FoDOMMaT program aims to open doors in STEM fields, particularly for students from underrepresented groups.

The program will continue to build foundational skills, foster research capabilities, and broaden career horizons, preparing students to tackle the challenges of the rapidly evolving field of machine learning.