805 Columbus Avenue
660 Interdisciplinary Science & Engineering Complex (ISEC)
Boston, MA 02120
ATTN: Piotr Sapiezynski, 435 ISEC
360 Huntington Avenue
Boston, MA 02115
- PhD, Technical University of Denmark
- MSc, Technical University of Denmark
- BSc in Engineering, Warsaw University of Technology – Poland
- Hometown: Warsaw, Poland
What are the specific areas of your graduate education?
I obtained my Master’s with honors from the Technical University of Denmark. I then continued my work on data science at the same university and obtained a PhD. After a short postdoc at DTU, I am now at Northeastern University, working with Prof. Alan Mislove and Prof. Christo Wilson on privacy as well as on fairness in machine learning.
What are your research interests?
My research is centered around the behavior of individuals, as well as the interactions people have with one another and with computer systems. I apply machine learning and other statistical approaches to model spreading of diseases and information, human mobility and interactions, as well as to infer relationships and life outcomes of study participants. I measure the impact of one’s actions and social network on their privacy. Finally, I investigate algorithmic black boxes and study ways of detecting, measuring, and eliminating biases from automated decision making systems.
What’s one problem you’d like to solve with your research / work?
I would like to make decision-making systems more transparent and understandable both for the people who operate them, and those affected by them.
What aspect of what you do is most interesting?
The bias in algorithms comes from many places: how the training data is collected and processed, the standards against which the algorithms are tested, optimizing for what we can measure, rather than for what the real goal of the systems is, etc. The field is maturing quickly, but there is so much more to discover.
What are your research or career goals, going forward?
I would like to do work that can be used to address real-life problems and shape policy.