Data Science

E. A. RUNDENSTEINER, PROGRAM HEAD

PROFESSORS: E. A. Rundensteiner, C. Ruiz, D. M. Strong, S.A. Zekavat, A. Trapp

ASSOCIATE PROFESSORS: L. T. Harrison, X. Kong, K. Lee, Y. Li, X. Liu, R. Paffenroth, J. Zou

ASSISTANT PROFESSORS: N. Kordzadeh, O. Mangoubi, R. Shraga, R. Moraffah

TEACHING PROFESSOR: F. Emdad

ASSOCIATE TEACHING PROFESSOR: C. K. Ngan

ASSISTANT TEACHING PROFESSOR: T. Ghoshal 

Collaborative Faculty: E. O. Agu, A. Arnold, D. Brown, S. Djamasbi, L. Fichera, T. Guo, N. T. Heffernan, X. Huang, B. Islam, D. Korkin, R. Neamtu, E. Ottmar, D. Reichman, A. Sales, B. Tang, D. N. Treku, J. Whitehill, Z. Wu, Z. Zhang

Mission Statement

Data Science prepares WPI undergraduates with the skills to understand, apply and develop models, algorithms and statistical techniques to gather huge amounts of data, draw new insights from it, and formulate appropriate action plans. Through courses and hands-on project work, students in the Data Science program will master foundational and advanced topics, including state-of-the-art data analytic technologies like machine/deep learning, artificial intelligence, and big data. This prepares the student to tackle the most critical data challenges in interdisciplinary teams with diverse perspectives in this increasingly digital world from climate change, self-driving cars, digital healthcare, to social justice. In addition to being a discipline in and of itself, Data Science complements many of the existing undergraduate majors at WPI. Disciplines from the sciences to engineering increasingly grapple with large data sets using computational and statistical techniques and tools.

Students interested in Data Science, both majors and minors, should check with the Data Science program as early as possible in their academic career to develop a plan of study. Students will be assigned a Data Science advisor after completing a major/minor declaration form.

Program Educational Objectives

In support of its goals and mission, the WPI Data Science undergraduate program’s educational objectives are to graduate students who will: 

• Bring together a community of diverse disciplinary backgrounds and experiential perspectives to promote creative solutions to critical real-world problems and advance knowledge at the cutting edge
• Achieve professional success due to their mastery of Data Science theory and practice
• Conduct impactful research and project work in data science and artificial intelligence tackling the world’s most challenging problems
• Engage in discovery through purpose-driven project-based learning
• Collaborate with partners both internally and externally in interdisciplinary projects
• Become leaders in business, academia, and society due to a broad preparation in data science, computational thinking, mathematics, science & engineering, communication, and social issues 
• Pursue lifelong learning and continuing professional development
• Use their understanding of the impact of data science on society for the benefit of humankind

Theme:

“Gather Information, Form Insights, Impact the World”!

Program Outcomes

Students graduating with a Bachelor of Science degree in Data Science: 

• Have mastered foundational studies in business, computer science, and mathematical sciences 
• Have mastered advanced principles and techniques in at least one of the three disciplines 
• Can apply computational and mathematical knowledge to the solution of big data problems 
• Can communicate effectively across disciplines both verbally and in writing 
• Can locate, read, and interpret primary literature in data science 
• Can function effectively as members of an interdisciplinary team 
• Have an understanding of accepted standards of ethical and professional behavior 
• Have the ability to be a life-long independent learner