Undergraduate Funded Research Opportunities
NSF REU SITE in DATA SCIENCE at WPI 2016 - 2022.
NSF REU SITE: DATA SCIENCE RESEARCH FOR HEALTHY COMMUNITIES IN THE DIGITAL AGE. CNS-1852498. 2019 - 2022.
NSF REU SITE: INTERDISCIPLINARY DATA SCIENCE RESEARCH FOR SAFE, SUSTAINABLE AND HEALTHY COMMUNITIES. CNS-1560229. 2016 - 2019.
The Data Science Program at WPI, sponsored by the National Science Foundation, offers a 10-week, all expenses paid Research Experience in Data Science for undergraduate students. The WPI Data Science program has successfully operated the site since 2016. This site offers students from geographically diverse institutions around the country access to vibrant scientific research projects and undergraduate mentorship.
The students, working with WPI faculty, graduate students, and peer students, learn state-of-the-art data science techniques and technologies including machine learning, artificial intelligence and big data technologies. They apply these new skills to research focused on solving societal challenges of high impact in our communities.
Research topics include digital health, sustainability, and mobility, all interlinked concerns of critical national importance. Students present the results of their research at an Open Poster Session during the final week of the program, and, where appropriate, at scholarly venues and conferences.
Student Stipends, Travel, Housing, and Meals
$5000.00 stipend over the 10-week program ($500/week)
- LEED Gold–certificated on-campus residence housing, paid for directly by the program
- $100.00 weekly meal allowance
- Up to $600.00 in travel expenses
Activities Include Industry Visits
The REU is enriched by symposia which are offered in job searching, applying to graduate school, writing a resume, and interview skills. Students also have the opportunity to network with data science professional alumni and industrial partners. Students also enjoy field trips to our industry partners engaged in data science, including, but not limited to, Google, MathWorks, Microsoft, MITRE Corporation, and National Grid. We can't thank them enough for hosting these bright young people.
Social activities are organized by the students and include the history, culture and sites of the greater New England area.
REU students are expected to work a full 40-hour work week for ten weeks, toward the completion of a research project. On the final day of the program, all research is placed on display for a Poster Presentation Symposium. This is a huge event combined with other REU sites and is attended by WPI faculty, guests and fellow students.
Research Project Areas
REU students have the opportunity to work on a research projects overseen by our WPI faculty. During the application process students describe their research interests in detail, including any prior research experience, and we work to match them to their area of interest.
Research areas relate to smart and healthy communities including Public Health, Personalized Mobile Wellness, Sustainability, Mobility, Economic Prosperity, and Social Good. Technical areas include data analytics, machine and deep learning, statistical learning, data visualization, artificial intelligence, big data infrastructures, web technologies, natural language processing, and cloud and mobile computing.
The NSF requires that ALL REU student participants demonstrate proof of being a United States Citizens or Lawful Permanent Residents. There are NO EXCEPTIONS. While we prefer sophomores and juniors who have a distinct interest in research, all U.S. students are eligible for the REU program. Those students who have succeeded in courses in programming, computer science, linear algebra, and statistics are of particular interest to our program. Women and underrepresented groups in STEM fields, as well as students from a community college who have transferred to a 4-year institution are encouraged to apply.
Students must fully complete the Online Application (below), and attach an unofficial transcript. We request two letters of recommendation, also submitted online via the Submit Faculty Recommendation button (below). The recommenders are preferably faculty members who know the student well and are at the student's home institution or another university.
All application materials, including letters, should be submitted by the application deadline to receive full consideration.
REU students work hard and play hard, as can be seen by the pyramid scheme they configured in the Data Science lab with Ph.D. mentor Ermal Toto. In jumbled order on the bottom row are a Ph.D. mentor, Luke Pelegrin, Cole Polychronis and Sean Tucci. Next up is Christian Huacon with Tran Khang and Kate Finnerty. Next to the top...we have Noori Apoorva and Jennifer Ha supporting our little Courtney Burns as the crown on the castle! Sarah Brownell is our left spotter with Ph.D. mentor Ermal Toto spotting on the right.