Dan Calacci

Human Dynamics
  • Research Assistant

Dan is a PhD student in the Human Dynamics group. Their work currently revolves around studying the relationship between inequality, segregation, and human behavior. Their most recent work involves measuring how people's daily mobility patterns contribute to income segregation in cities. Dan is also active in advocating for data and platform co-operatives & other structures that help individuals take an active role in how their data is collected and used. He is interested in how principles from participatory design can be used to create a more ethical, engaged, and subject-centered social science.

In the past, they  were an active contributor to and founder of the Rhythm initiative to create open-source tools to measure human face-to-face social interaction. Dan is a co-founder of a spin-off company, Riff Learning, that is based in part on work that they did while a Master's student at the lab.

Other work Dan has been involved in includes: mapping corporate surveillance in cities, building massively scalable distributed deep reinforcement learning systems, behavioral health monitoring systems, and healthcare pub… View full description

Dan is a PhD student in the Human Dynamics group. Their work currently revolves around studying the relationship between inequality, segregation, and human behavior. Their most recent work involves measuring how people's daily mobility patterns contribute to income segregation in cities. Dan is also active in advocating for data and platform co-operatives & other structures that help individuals take an active role in how their data is collected and used. He is interested in how principles from participatory design can be used to create a more ethical, engaged, and subject-centered social science.

In the past, they  were an active contributor to and founder of the Rhythm initiative to create open-source tools to measure human face-to-face social interaction. Dan is a co-founder of a spin-off company, Riff Learning, that is based in part on work that they did while a Master's student at the lab.

Other work Dan has been involved in includes: mapping corporate surveillance in cities, building massively scalable distributed deep reinforcement learning systems, behavioral health monitoring systems, and healthcare public policy.

Before joining the lab, Dan nabbed a B.S. in Computer Science from Northeastern University, with minors in Political Science and Sociology. While at Northeastern, they published work on inferring political influence networks using natural language processing techniques.