Prospective PhD Students

I am always looking for strong PhD students. Students interested in working with me can apply to BU's PhD program in Computing & Data Sciences (CDS). Another option is applying through BU's PhD program in Computer Science (CS). All applications must be received this way. Questions may be directed to the CDS Academic Programs Manager at msieber@bu.edu. Please note that PhD admissions are done centrally by committee at the department level, and not by specific faculty members.

Funding: BU CDS and CS students do not pay tuition and when funded, get paid a stipend for their work in the PhD programs. All CDS and CS PhD students are guaranteed funding via either research assistantships (RAs) or Teaching Assistantships (TAs) for 5 years. CDS students receive departmental funding for their first two years to have the freedom to take courses and rotate with advisors if they would like. For more information about CDS, see my blog post here.

Academic background: I enjoy working with people from diverse academic backgrounds. An undergraduate degree in math or computer science is useful but is not necessary. Rather than specific coursework or degrees, I believe the most important attributes in prospective students are mathematical maturity, initiative, and the ability to self-teach oneself material as needed—with these traits, a student of any background can succeed in working with me. Resources for learning relevant background can be found on my resources page.

Resources for applying:

Mor Harchol-Balter's guide to applying to CS PhD programs (last updated 2014)
A number of programs were initiated last year giving feedback on applications, e.g., Stanford Student-Applicant Support Program, Columbia Pre-submission Application Review Program, UW Pre-Application Mentoring Service—take a look around for these.

My research interests: I am generally interested in algorithmic approaches and how they intersect with strategic behavior and incentives, as in the paradigm of mechanism design. My two major research thrusts are in mechanism design for social good (see a high-level talk or a more technical talk) and in rethinking standard behavioral and informational assumptions as they pertain to mechanism design (e.g., robustness to informational interdependence, complementarities, and risk-aversion). I also have extensive prior work in multi-item revenue maximization, as in the interdimensional setting.

Research projects: I do not hire graduate students to work on existing research projects. I find research projects that are of mutual interest to myself and the graduate student to work on, such as in the areas of described above. I am also very excited to work with students who have their own questions if the area intersects with my interests.