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Mr Dovydas Joksas
Roberts Building
Torrington Place
Mr Dovydas Joksas profile picture
  • Postgraduate Teaching Assistant
  • Dept of Chemical Engineering
  • Faculty of Engineering Science
You can find more information on my personal website yoshke.org
Research Summary

Artificial neural networks (ANNs) have achieved spectacular results over the last decade, but at a cost of low efficiency. Our conventional computer hardware is not well suited to the computations that ANNs perform and so a lot of time and energy is wasted. One of the suggested alternatives is an emerging technology—memristor-based hardware. Although vastly more efficient, memristor-based implementations exhibit a greater degree of volatility and uncertainty than the digital computers that we use every day.

Using simulations, I investigate to what extent the accuracy of ANNs is affected when memristor-based hardware is used to implement them. I am also interested in whether the accuracy can be increased not by optimising device performance, but by using different software approaches. I explain the rationale behind the research in less technical terms here, here and here.

Teaching Summary


  • Mathematical Modelling and Analysis II (teaching)


  • Technical Communication (assessing)
  • Numerical Methods (assessing)

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