This collection of MIT Theses in DSpace contains selected theses and dissertations from all MIT departments. Please note that this is NOT a complete collection of MIT theses. To search all MIT theses, use Barton, MIT Libraries' catalog.

MIT's DSpace contains more than 40,000 theses completed at MIT dating as far back as the mid 1800's. Theses in this collection have been scanned by Document Services or submitted in electronic format by thesis authors. Since 2004 all new Masters and Ph.D. theses will be scanned and will be added to this collection after degrees are awarded.

If you have questions about MIT theses in DSpace, contact Document Services. See also Access & Availability Questions or About MIT Theses in DSpace.

If you are a recent MIT graduate and would like to add your thesis to the theses in DSpace, see Add Your Thesis to MIT's DSpace for instructions. All theses scanned by the MIT Libraries are scanned in black and white mode. Color content, active links, and searchable text will only be preserved in the online version of your thesis if you have given an electronic copy (PDF) to the MIT Libraries.

MIT theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. To ask for permission, please contact:

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Recent Submissions

  • Eye tracking for cognition 

    Li, Stephen,M. Eng.Massachusetts Institute of Technology. (Massachusetts Institute of Technology, 2019)
    Early detection of neurodegenerative diseases can lead to slower disease progression, as well as possible symptom reduction. Existing research has studied how cognitively impaired subjects solve tests such as the clock-drawing ...
  • Understanding EV owners' preferences towards enrolling in smart charging programs 

    Rodriguez Jimenez, William A. Rodriguez. (Massachusetts Institute of Technology, 2019)
    Demand for electricity has been increasing in recent years, bolstered by growing adoption of electric vehicles (EVs). To smooth demand at peak periods, under demand response or "smart-charging" programs, power utilities ...
  • High-performance intent classification in sparse supervised data conditions 

    Galli, Keith(Keith R.) (Massachusetts Institute of Technology, 2019)
    Intent recognition is the process of taking short messages, called utterances, and automatically classifying them as a specific intent from a set of possible intents. A model is trained using a number of sample utterances ...

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