Research Opportunities

Northeastern University’s College of Computer and Information Science (CCIS) has a growinging number of researchers in data science. In the DATA Lab, we focus on research problems in data management, data mining and machine learning with particular emphasis on scalability of algorithms to large data and inventing novel ways of interactions with data. In addition to our existing faculty Profs. Mirek Riedewald and Wolfgang Gatterbauer, a third senior faculty is joining us in Fall 2018, and the college plans to continue hiring.

Our growing group is part of a strong team of more than 60 tenured and tenure-track CCIS faculty with several related groups in areas such as network science, information retrieval, probabilistic AI, applied data science, distributed machine learning, NLP, theory, pattern recognition, visualization, and applied and interdisciplinary mathematics. The college is expanding rapidly and is now also highly ranked among top computer science schools in terms of publications at selective venues (see e.g., or

PhD program (yearly deadline: Dec 15)

The DATA Lab currently has multiple open and funded PhD positions focused on scalable approaches for managing uncertain, inconsistent, distributed and network data. We are particularly interested in students with strong foundations in one or more of the following: algorithms, data structures, logic, theory, statistics, optimization, probabilistic AI, and machine learning. Solid English speaking and writing skills are very important (TOEFL > 100). Three letters of reference and good GRE scores (Verbal > 150, Quant > 160, AW > 3.5) are required. Familiarity with the process of performing research is helpful. The yearly deadline for our PhD program in computer science is Dec 15th. To make sure we will see your application in the graduate school application system, make sure you (1) mention faculty names in your statement of purpose and (2) enter “databases” as one of your areas of interest. Our friendly and supportive community openly welcomes women and minority students.

If you are a strong applicant, don’t wait for the official application deadline of Dec 15: contact us any time to start a conversation about joining our team! To explore such PhD research opportunities in our group please email us at with:

  • Your CV
  • A couple of paragraphs describing your research interests. Why do you want to pursue a PhD? What do you hope to achieve? How does your interest match the interests in our group?
  • If you have any research experience, tell us about it. What was your role? Why does that research matter? How do your results improve over the state-of-the-art? Just write a couple of short paragraphs, don’t go into details.
  • If you already published your work in a peer-reviewed venue, include a link for us to be able to take a look at it. Sending us a link to an impressive GitHub profile is a big asset. If you have none of these, include an example independent project report or thesis. This will help us gauge your ability to coherently formulate problems and explain solutions.

Pursuing a PhD: Working with us on your PhD will prepare you for independent and collaborative research. The research process is very different from attending class and writing exams. We found that students who are familiar with the research process before starting their PhDs are far more likely to be happy and successful PhD students. Here are a few helpful links:

  • Everything I wanted to know about C.S. graduate school at the beginning but didn’t learn until later. Azuma. 1997-2017 (website)
  • Applying to Ph.D. Programs in Computer Science. Harchol-Balter (pdf)

Research opportunities for current Northeastern students

If you are already enrolled at Northeastern, just stop by or contact us at

  • PhD students looking for an advisor or who want to explore new research opportunities.
  • Master students interested in project courses or a thesis (unpaid).
  • Undergraduate students interested in project courses (unpaid), co-op (paid), or summer research.

For project and reading courses, the typical workload is equivalent to 4 credits. We usually have a variety of project options, ranging from implementation of distributed algorithms to algorithm design and more theoretical studies.

Career Counselors and Faculty

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