Ph.D. Topics in Computer Science

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PhD Topics in Computer Science

While there are many topics, you should choose the research topic according to your personal interest. However, the topic should also be chosen on market demand. The topic must address the common people’s problems.

In this blog post, we are listing important and popular Ph.D. (Research) topics in Computer Science.

PhD in Computer Science 2023: Admission, Eligibility

The hottest topics in computer science

  1. Artificial Intelligence.
  2. Machine Learning Algorithms.
  3. Deep Learning.
  4. Computer Vision.
  5. Natural Language Processing.
  6. Blockchain.
  7. Various applications of ML range: Healthcare, Urban Transportation, Smart Environments, Social Networks, etc.
  8. Autonomous systems.
  9. Robotics.
  10. Data Privacy and Security.
  11. Big Data
  12. IoT
  13. Lightweight and Battery efficient Communication Protocols.
  14. Sensor Networks
  15. 5G and its protocols.
  16. Quantum Computing.
  17. Cryptography.
  18. Cybersecurity
  19. Big Data
  20. Bioinformatics/Biotechnology
  21. Computer Vision/Image Processing
  22. Cloud Computing

Other good research topics for Ph.D. in computer science

Bioinformatics

  • Modeling Biological systems.
  • Analysis of protein expressions.
  • computational evolutionary biology.
  • Genome annotation.
  • sequence Analysis.

Internet of things

  • adaptive systems and model at runtime.
  • machine-to-machine communications and IoT.
  • Routing and control protocols.
  • 5G Network and internet of things.
  • Body sensors networks, smart portable devices.

Cloud computing

  • How to negotiate service level platform.
  • backup options for the cloud.
  • Secure data management, within and across data centers.
  • Cloud access control and key management.
  • secure computation outsourcing.

Cybersecurity

  • most enormous data breach in the 21st century.
  • understanding authorization infrastructures.
  • cybersecurity while downloading files.
  • social engineering and its importance.

Big data

  • Big data adoption and analytics of a cloud computing platform.
  • Identify fake news in real-time.
  • neural machine translation to the local language.
  • lightweight big data analytics as a service.
  • automated deployment of spark clusters.

Machine learning

  • The classification technique for face spoof detection in an artificial neural network.
  • Neuromorphic computing computer vision.
  • online fraud detection.
  • the purpose technique for prediction analysis in data mining.
  • virtual personal assistant’s predictions.

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