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REU for Data-Driven Discovery

March 3, 2016

ECE Professor David Kaeli was awarded a $360K NSF grant to develop an REU site to provide students exploring big data problems access to state-of-the-art high performance computing resources. The program is working with 8 partner schools to target rising sophomores woking in data-oriented problem domains. The REU-D3 website includes the research descriptions of the contributed projects. Students select their top 3 projects and then the team will work with the applicant and faculty on making the best matches of students and mentors. 

The REU-D3 administrative team includes the following individuals:

  • Melanie Smith - Program Director
  • Claire Duggan - Program Evaluation and Advisory Board
  • Kristin Hicks - Advisory Board
  • Richard Harris - Advisory Board
  • Rachelle Reisberg - Advisory Board
  • Audrey Rorrer (UNCC) - CISE Toolkit Liaison
  • Jack Magrath - Web Design

Abstract Source: NSF


This REU site will help support NSF's mission to promote the progress of science by providing multi-disciplinary research experience for undergraduates with exciting 10-week summer-based experiences in computer science/engineering laboratories, enabling work on both fundamental and applied data-driven problems, focused on applying machine learning techniques, data analytics, and parallel computing technologies, and preparing them for future scientific career. The REU students will have the opportunity to utilize state-of-the-art high performance computing resources to tackle big data problems present in a number of problem domains, including Bioengineering, Environmental Engineering and Biomedical Engineering. PI's will leverage the Massachusetts Green High Performance Computing Center located in Holyoke, MA to provide a backdrop for this multi-disciplinary REU Site. The program will provide students with extensive cyber-infrastructure training, equipping program participants with the skillsets to explore the boundaries between math, science, engineering and parallel computing that are truly multi-disciplinary. The REU Site is located at Northeastern University in the heart of Boston.


The REU projects span a wide range of technical fields in Computer Science and Engineering. Example projects include: applying machine learning to cluster Chronic Obstructive Pulmonary Disease (COPD) data, data mining Twitter feeds to identify trends in climate change, utilizing hardware accelerators to detect cancerous tumors in 4-D Computed Tomography images, and utilizing regression analysis on gene expressions to understand patterns in retina regeneration. One novelty of this site is its focus on recruiting efforts, tailoring their research experiences for students that have only completed their freshmen year of their undergraduate education, engaging them early in research on their academic pathway. The REU site works to create a mentoring eco-system at both Northeastern University and the partnering institutions, developing a model that is transferrable to other institutions. The program builds relationships with six urban community colleges/universities to build a pipeline of students, creating a diverse pool of REU candidates, showing students potential pathways to graduate education and research. The program leverages the CISE REU Toolkit for pre- and post-program surveys, as well as for recruiting. The REU-D3 Site is focused on effecting changes in mentoring attitudes and practices at the host and partnering academic institutions.