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Choosing The Best Postgraduate Thesis Topics In Computer Science

Every postgraduate thesis begins with a smartly chosen topic. It’s a stage of writing that requires a lot of attention and care. The topic determines not only if further development of the research will be successful, but whether it will be accepted as novel, useful not only for the candidate but for the society and development of computer science as a whole. While it’s hard to choose a thesis topic for practically all candidates, it’s necessary to choose a subject that will not limit candidates’ researching abilities, development of skills, intellectual growth, etc.

When choosing a topic, you should not do it blindly. Do some analysis of the area of your specialization in computer science and determine what needs more attention and further development. This analysis will help you in:

  • defining the topic and title;
  • evaluating topicality of the chosen direction;
  • excluding topics that are “dead-end” (the problem cannot be solved at the today’s stage of scientific development in the sphere of computer science), or “deaf” (the problem can be researched only after there are results of research in related branches);
  • determining the time that is required to complete the project.

Besides that, such profound analysis of available topics will help you avoid certain common mistakes candidates make when they search for good thesis topics:

  • lack of preciseness in the topic and title;
  • the topic does not define the problem and which positive outcomes can be reached with further researching;
  • the topic is phrased as the name of a stage of a research project;
  • the topic and title are overloaded with specific terminology, jargon, or abbreviations that are unclear for common readers.

If you want a good topic, turn to your supervisor and ask for help. You can also try searching on the Internet. You can find a number of interesting topics that will let you show all your professional abilities and skills, in lists similar to the one below.

  1. Improvement of methods of semantic relations.
  2. Computer-supported observation of reactions caused by music in human brains.
  3. Statistical machine translation and segmentation of speech.
  4. Computerized speech recognition for rare languages.
  5. Cloud computing as a new dimension in storage and processing of documents.
  6. Computerized recognition of landscape and items for blind navigation.
  7. Eye-tracking applications for mobile phones and laptops.
  8. Computerized education as a factor of regional development.
  9. The role of machine learning in prediction of human brain activities.
  10. Routing for emergency vehicles: dynamic navigation and coordination of traffic signals.

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