The IGERT program brings together departments and students to educate an interdisciplinary cohort of scientists.

IGERT is a PhD program with two key goals:

  • Education and Training: To produce a new generation of interdisciplinary scientists, versed in computer science, statistics and the domain sciences; capable of developing and using Big Data tools and models that will enable fundamental discoveries in a data intensive world.
  • Cyberinfrastructure Development: To develop and release open-source tools and Cloud services that can be deployed and utilized by researchers across many domains for managing, analyzing and visualizing Big Data.

Big Data is an evolving field, whose definition is fluid, and will continue to evolve over the years. Thus, the core of our educational approach is a comprehensive interdisciplinary, multifaceted practical training program, which connects students with mentors in other fields, other students, and industry and National Labs practitioners. Our overall approach for training students in Big Data consists of:

  • Multidisciplinary Supervision: Students are associated with a primary, PhD granting department, and an advisor in this department. The primary PhD granting department must be one of the IGERT participating departments. Students are also connected with a secondary advisor in a complementary field, who provides direction in the methods, models, or questions around Big Data. The secondary advisor need not be in a participating department.
  • Core Curriculum: An integrated, multidisciplinary set of courses that prepare the students in the algorithmic, statistical, systems, and scientific aspects of Big Data. Although each student is associated with a primary department, all students in the program follow the same Big Data curriculum defined below. This curriculum is an overlay on top of the requirements of the participating departments in a manner that is specific to each department. Please contact the faculty liaisons for detailed information.
  • Interdisciplinary Project: Students are recommended to do a two-quarter long research project with a secondary advisor with complementary skills, e.g., a computer science student may do the project in an astronomy lab. This project will culminate in a presentation and a written report of a quality that the secondary advisor would consider publishable in a top venue in the complementary field. The program strongly encourages all students to present this work in the form of a paper or at least a poster at a conference or workshop.
  • Big Data Tools: All IGERT students are expected to pursue a thesis in the area of Big Data / Data Science. In this context, the program expects all students to either contribute to the algorithmic, statistical or systems infrastructure for Big Data and release this work in the form of open-source software, or engage and utilize state-of-the-art Big Data tools to address a core scientific or engineering task.
  • Industrial Practical Training: Every student is recommended to do at least one internship in industry or National Labs during their PhD. These internships must cover practical work around Big Data.

The IGERT Program Curriculum will evolve over the lifetime of this program. For students entering the program in Fall 2013 or later, the requirements are as follows:

Three out of four of the following core courses:

Data Management: CSE 544.
Machine Learning, CSE 546 or STAT 535.
Data Visualization: CSE 512.
Statistics: STAT 509 or STAT 512-513.

Course descriptions and pre-requisites are listed here.

All students must also register each year for the Big Data Seminar Course, CHEM E 599F.

An IGERT course can be replaced by an equivalent or more advanced course in the same area UPON APPROVAL. A student must submit an email petition to the Steering Committee (bigdata-igert-steering (at) cs (dot) washington (dot) edu) to perform such a substitution.

FAQs: IGERT Frequently Asked Questions (PDF)

IGERT is accepting one final cohort!

Applications for the 2017-2018 Academic Year are due JULY 15, 2017.

The Big Data IGERT is a highly selective 2-year Fellowship for PhD students interested in research in Big Data. All students satisfying the following criteria are encouraged to apply:

  • Note: Applicants must be US Citizens or Permanent Residents (an NSF requirement).
  • First or second years in a PhD program in a participating department.
  • Committed to doing research in Big Data, releasing open-source software, willing to do at least one internship in industry or National Labs, and satisfy the other requirements of the IGERT (above).
  • Able to commit to two continuous years of IGERT funding – no other TA, RA, or Fellowship commitments (small amounts for travel or similar are ok).

Application process:

Each application must include:

  1. Student’s name, UW id, affiliation, current year of study, UW graduate transcript (if completed at least 1 quarter at UW).
  2. Student’s CV.
  3. Name and affiliation of primary and secondary advisors.
  4. Short letter of support from primary and secondary advisors.
  5. One page description of the PhD research and education plan. The student should work with his or her advisors in order to put that plan together for the application.

Please submit applications by email to bigdata-igert-applications [at] cs [dot] washington [dot] edu

FAQs: IGERT Frequently Asked Questions (PDF)

This project is partially supported by the following: