Jinjun Xiong

PhD

JInjun Xiong.

Jinjun Xiong

PhD

Jinjun Xiong

PhD

Research Topics

Cognitive computing, big data analytics, deep learning, smarter energy, application of cognitive computing for industrial solutions

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Research Areas

  • Artificial Intelligence and Machine Learning and Data Mining
    1/26/23
    Artificial Intelligence (AI) researchers now predict that computers will be able to perform tasks that were once considered the prerogative of human beings.
  • Computer Architecture and Hardware
    1/17/23
    Hardware and software issues from the circuit to the system have three main foci: Very Large Scale Integration (VLSI) circuits and systems, computer architecture, and computer security.
  • Computer Vision
    1/17/23
    Algorithms for computer vision have a close relationship to methods of pattern recognition and machine learning.
  • Distributed Systems and Networks
    1/17/23
    Research in networking and distributed systems focuses on enabling communication of and orchestrating coordination of a large number of computing nodes.
  • Edge Computing and Embedded Systems and Robotics
    9/27/24
    Hardware and software co-design on embedded/ASIC computing performance optimization.
  • High-Performance Computing
    1/17/23
    Focuses on efficient experimental and theoretical solutions to problems on state-of-the-art computational systems consisting of large numbers of computational elements, including clouds, clusters, grids, networks-of-workstations, massively parallel supercomputers, and GPU-based systems.
  • Natural Language Processing
    1/17/23
    Focuses on developing fundamental techniques, prototype systems and applications in natural language processing and information retrieval.
  • Society and Computing
    1/17/23
    Computing is ubiquitous in society today. Computing touches all aspects of our lives and sometimes in ways that are not beneficial (even though the intent of the developer is not to cause harm). What has become clear is that we cannot develop systems for society without meaningful and deep collaborations with disciplines that have thought about society for much longer than computing. The challenge is to incorporate knowledge from humanistic studies from day one in the design of computing systems.