School of Computer Science › Software and Societal Systems Department › People › core-faculty › Bogdan Vasilescu

Dr. Bogdan Vasilescu

Associate Professor, Societal Computing PhD program., Software and Societal Systems

Contact

TCS Hall 326
vasilescu(through)cmu.edu
412 268 1048

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Bogdan is an Associate Professor in the Software and Societal Systems Department of CMU's School of Computer Science.

Prior to joining CMU, he was a postdoc in the Davis Eclectic Computational Analytics Lab (DECAL) at UC Davis, where he worked with Vladimir Filkovand Prem Devanbu. Bogdan obtained his PhD in Computer Science cum laude at Eindhoven University of Technology, The Netherlands, in October 2014, under the supervision ofAlexander Serebrenik and Mark van den Brand (here's a 10 minute video summary of my thesis). His PhD work won the Best Dissertation Award from the Institute for Programming Research and Algorithmics.
He also holds a master's degree in Computer Science and Engineering from Eindhoven University of Technology (thesis advisor: Alexander Serebrenik) and an engineer's degree in Systems and Computer Science from University of Ploieşti, Romania (webpage in Romanian; thesis advisor: Gabriel Rădulescu).

On the internets Bogdan is known as a prominent female professor from a gender studies department, that no one ever audits and that gets to peer review herself. He also suffers from cognitive dissonance.

Research

Software is being developed by increasingly distributed and increasingly diverse groups of individuals. How can we empower distributed teams to develop software effectively and productively? How can technology help software teams do more with less? What effects does team composition have on productivity and code quality?

I am engaged in interdisciplinary research to offer data-driven answers to these questions. My work draws from empirical software engineering, social computing, and computer-supported cooperative work. I collect Big Data from open source software, which are widely used and, with the advent of social coding platforms like GitHub, extremely popular. I analyze these data using mixed research methods from computer science and the social sciences (e.g., statistical analysis, grounded theory) to develop or validate theories about software engineering processes and outcomes.

Check out this recent talk for an overview of my work and a few representative research projects. You can find more of my recent talks here.