Electronic Materials

Symposium I

Brain Inspired Electronics – Materials, Devices and Systems

Artificial intelligence (AI) is the freight train headed our way which is already changing the way we live. The best electronic system to implement AI may not be based on CMOS circuitry as the von Neumann bottle neck and the way conventional silicon electronics work are too different compared to the way our brain performs human operation efficiently using an average power of just 20 Watts. Hence brain inspired electronics is the alternate approach to conventional Si CMOS and neuromorphic computing is the ultimate holy grail. The neuron and the neuronal network needs to be simulated and the research community has adopted a variety of materials and device based approaches ranging from memristors, oscillators to nano photonics making this the fore front of next generation electronics.

  • Resistance memory based memristors (oxide, organic);
  • Ferroelectric based artificial synapse and neurons;
  • Spintronics based artificial synapse and neurons;
  • Photonic approaches;
  • Novel network concepts involving spike neural networks and artificial neural networks;
  • Sensor technologies to simulate human senses.

~ Speakers’ list forthcoming ~

Chairs

Jingsheng Chen
National University of Singapore, Singapore

Benjamin Tee
National University of Singapore, Singapore

Co-Chair(s)

Thirumalai Venky Venkatesan
National University of Singapore, Singapore

R. Stanley Williams
Texas A&M University, USA

Ming Liu
Institute of Microelectronics, China

Correspondence

Jingsheng Chen
National University of Singapore, Singapore
Email: msecj@nus.edu.sg