2017 Admissions

As of September 2017, Social Machines will be seeking graduate students who will join a cross-disciplinary team with the goal of using technology to help self-organizing human networks — “social machines” — effect positive change.

The new lab builds on the work of Deb Roy’s previous research into foundations of language and semantics, but will push off in significantly new directions that incorporate social network and media analysis.

Among the Lab’s current projects:

  • The “Electome” — A new form of election analysis (in this case the 2016 presidential election) that comprehensively maps the content and network connections among the campaign’s three core public sphere voices: the Candidates, the Media, and the Public.
  • The “Foodome” — Similar to the Electome, a mapping of the public, media and industry conversation about food-related topics using NLP, network analysis and data visualization.
  • “Playful Words” |Social Literacy Learning — Child-driven and machine-guided “social learning” technologies that empower human networks to promote literacy growth.
  • Visible Communities — Mapping, based on satellite analytics of household and road level data in rural areas, coupled with a mobile app with a navigation interface specifically designed to empower Community Health Workers.
Social Machines group students apply through the Media Lab’s graduate program application process, detailed here. Postdocs are also welcome to apply.

 

AREAS OF INTEREST:

 

  • Image Analysis / Computer Vision — Applicants should have experience with state of the art image analysis / computer vision techniques based on machine learning and applicable to large datasets. We will have a focus on satellite image analysis.
  • Spoken Language Processing — Applicants should have experience with state of the art spoken language and speech processing techniques including speech recognition, speech synthesis, and design of spoken language and audio interfaces. We will have a focus on Indian languages.
  • Network Analysis — Applicants should have experience with state of the art network analysis techniques (applied to social networks, and other networks derived from unstructured data) including design and analysis of randomized experiments on networks, and preferably software engineering skills and experience working with large heterogeneous datasets.
  • Mobile App Development — Applicants should have experience with UI/UX design skills, experience developing apps for mobile devices (especially on Android), experience developing web services, and preferably experience working with large heterogeneous datasets.
  • Game Design — Applicants should have experience in the design and implementation of games or “game-ification” for behavior change apps. Our focus will be on language and literacy learning.
  • Data Visualization — Applicants should have experience with state of the art data visualization and interaction techniques, and preferably software engineering skills and experience working with large heterogeneous datasets.
  • Machine Learning & Pattern Analysis — Applicants should have experience with modern statistical machine learning and pattern analysis techniques (applied to unstructured and structured data), and preferably software engineering skills and experience working with large datasets.