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Research Interests

Humanity's ambition of building Artificial General Intelligence intrigues me immensely. Although I am an engineer by training and primarily work on applied AI, I am deeply interested in the theory of deep learning to build accountable and ethically sound AI. I have cultivated a recent interest in Computational Neuroscience to understand the theoretical basis of cognition, memory and learning.

 

I have been involved in theoretical and applied interdisciplinary research in:

  • Learning (deep learning, spiking neural networks, reinforcement learning, self-supervised learning)

  • Vision (visual attention, structure from motion, visual odometry, SLAM, stereo disparity, OCR)

  • Robotics (human robot interaction, neuromorphic perception, motion and path planning)

  • Human Computer Interaction (assistive interfaces)

  • Image Processing (contrast enhancement, scratched image restoration)

  • Evolutionary Computing (differential evolution, particle swarm optimization)

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