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PHD Research Proposal in Artificial Intelligence

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In the past decades, the field of Artificial Intelligence (AI) has grown dramatically due to an increased demand for the automated system in day-to-day lives. AI [1] has the ability of decision-making, learning, and analytical skills similar to humans. It studies the intelligent entities from the perspective of engineering, psychological, and philosophical. AI enables the machine to perform the ‘cognitive’ operations such as ‘problem-solving’ and ‘learning’ to associate humans with other human minds.

The rapid proliferation of interdisciplinary science involving cybernetics, linguistics, computer science, philosophy, automation, neuroscience, psychology, and mathematical logic heavily relies on the concept of AI. The primary goals of the AI include natural language processing, learning, reasoning, planning, knowledge, perception, and manipulation. Nowadays, AI has been widely used in numerous industries and fields [2, 3] such as healthcare, transportation, education, electronic trading, finance, gaming, e-commerce, medical diagnosis, cyber defense, remote sensing, robot control and so on.

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Research Areas

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  • Natural language processing and Text analytics
  • Decision-making in enterprise applications
  • Speech recognition
  • Automated Machine learning and Deep learning platforms
  • Knowledge representation
  • Search and Information retrieval
  • Automated expert systems
  • Computer vision and Robotics
  • Neural networks
  • Preference handling
  • Computational Biology
  • Sentiment analysis
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Research Gap

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In recent years, the rapid advancement of the AI has created a dramatic revolution in both the techniques and theories. However, the fast-growing and multi-disciplinary features tend to the difficulty of understanding the context of the AI [4]. Also, the goals of the AI affects society during the verification, security, and control due to its intelligent behavior. The research on AI lacks on improving the face recognition, voice and video conferencing for the tremendously increasing amount of big data. In addition, AI research needs to provide the intelligent solutions towards the support of the fully automated systems and personal assistance, even when there is the existence of heavy workloads.

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Problem Statement

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The field of AI often meets the difficulty in learning and understanding the knowledge as a fundamental research problem. Owing to the existence of the imperfect and incomplete knowledge over the increasing amount of available data, inferencing the information leads to the scalability issue for the AI technique. In addition, the multi-disciplinary nature of the data necessitates the expert decision-making while extracting the hidden data from the diverse information sources using the AI. Most of the research works have focused on analyzing the features of the data based on intelligent behavior to provide better decision-making for scientific and business applications. However, there is an essential need for providing adaptive automation systems for real-time applications within a short period of decision-making. In the context of the machine learning algorithm, the size of training data creates the difficulty to process the large data to provide the fast and potential solutions due to the need of the large computational time and power to understand the context of the data.

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References

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  • [1]O’Leary, Daniel E, “Artificial intelligence and big data”, IEEE Intelligent Systems, Vol.28, No.2, pp.96-99, 2013

  • [2] Rudie, Jeffrey D., Andreas M. Rauschecker, R. Nick Bryan, Christos Davatzikos, and Suyash Mohan, “Emerging Applications of Artificial Intelligence in Neuro-Oncology”, Radiology, 2019.

  • [3] Dilek, Selma, Hüseyin Çakır, and Mustafa Aydın, “Applications of artificial intelligence techniques to combating cyber crimes: A review”, arXiv preprint arXiv:1502.03552, 2015.

  • [4] Cath, Corinne, “Governing artificial intelligence: ethical, legal and technical opportunities and challenges”, 20180080, 2018.

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