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Researcher

Shabab Bazrafkan

Research Expertise:Working on machine learning in general and Deep Learning in particular. Design and Training of Deep Neural Networks, Data Augmentation and Generative Models. Currently working on low dose CT reconstruction and Tomosynthesis using Deep Neural Networks.

Keywords:DEEP GENERATIVE MODELS, MACHINE LEARNING, DEEP NEURAL NETWORKS, DEEP LEARNING, TECHNOLOGY DEVELOPMENT, TECHNOLOGY, ARTIFICIAL INTELLIGENCE (AI), Physics (incl. astronomy)

Disciplines:Data mining, Artificial intelligence not elsewhere classified, Computational biomodelling and machine learning, Computer aided engineering, simulation and design, Biomedical image processing, Biomedical signal processing, Analogue and digital signal processing, Signal processing not elsewhere classified, Artificial intelligence, Knowledge representation and machine learning, Neurocognitive patterns and neural networks

Research techniques:In the case of the network design and training the techniques are mostly literature and coding based. Low level coding in CUDA and high level coding in frameworks such as MXNET or Tensorflow. Data preparation is also literature and coding based as far as there is no need of acquisition.

Users of research expertise:Technology based industries. Medical companies. Any market targeting Artificial Intelligence. Video and Image processing industries. IoT, Smart cities.