Melika Payvand

Position:
Research Fellow
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The question that drives me is to understand how intelligence emerges from the structure of its underlying substrate which will help me build intelligent systems. I combine the understandings from neuroscience, machine learning, electrical engineering and device physics in a co-design fashion towards building low-power and high-density intelligent systems. These systems have applications in a variety of autonomous sensory-motor systems/agents on the edge, capable of real-time inference and online learning.

Supervisor

Giacomo Indiveri

Publications

2021

2020

  • Arianna Rubino; Can Livanelioglu; Ning Qiao; Melika Payvand; Giacomo Indiveri Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence, IEEE Transactions on Circuits and Systems I: Regular Papers, Volume: 68:(Issue: 1) 45 - 56, 2020
  • Enea Ceolini, Charlotte Frenkel, Sumit Bam Shrestha, Gemma Taverni, Lyes Khacef, Melika Payvand, Elisa Donati Hand-gesture recognition based on EMG and event-based camera sensor fusion: a benchmark in neuromorphic computing, Frontiers in Neuroscience, 2020 pdf
  • Hajar Asgari, Babak Mazloom-Nezhad Maybodi, Melika Payvand, Mostafa Rahimi Azghadi Low-Energy and Fast Spiking Neural Network For Context-Dependent Learning on FPGA, IEEE Transactions on Circuits and Systems II: Express Briefs, 67:(11) 2697 - 2701, 2020
  • Melika Payvand, Mohammed E. Fouda, Fadi Kurdahi, Ahmed Eltawil, Emre O. Neftci Error-triggered three-factor learning dynamics for crossbar arrays, 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2020 pdf
  • Melika Payvand, Mohammed E Fouda, Fadi Kurdahi, Ahmed M Eltawil, Emre O Neftci On-Chip Error-triggered Learning of Multi-layer Memristive Spiking Neural Networks, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2020
  • Melika Payvand, Yigit Demirag, Thomas Dalgathy, Elisa Vianello, Giacomo Indiveri Analog weight updates with compliance current modulation of binary ReRAMs for on-chip learning, ISCAS, 2020 pdf
  • Mostafa Rahimiazghadi, Corey Lammie, Jason Kamran Eshraghian, Melika Payvand, Elisa Donati, Bernabe Linares-Barranco, Giacomo Indiveri Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications, IEEE Transactions on Biomedical Circuits and Systems, 2020
  • Tobi Delbruck, Ibrahim Abe M Elfadel, Shahzad Muzaffar, Germain Haessig, Bo Wang, Amine Bermak, Rui Graca, Luis Camuńas-Mesa, Bathiya Senevirathna, Pamela Abshire, Bernabe Linares-Barranco, Saeed Afshar, Shih-Chii Liu, Runchun Mark Wang, Piotr Dudek, Stephen Carey, Jose de la Rosa, Marc Dandin, Sheung Lu, Vincent Frick, Teresa Serrano-Gotarredona, Paula Lopez, Melika Payvand, Advait Madhavan, Eric Fossum, J Camilo Vasquez Tieck, Ian Williams, Yan Liu, Timothy Constandinou, Alexander Serb, Ricardo Carmona-Galan, Robert Nawrocki, Walter D Leon-Salas Lessons Learned the Hard Way, 2020 IEEE International Symposium on Circuits and Systems (ISCAS), 2020
  • Giacomo Indiveri, Bernabe Linares Barranco, Melika Payvand System-level integration in neuromorphic co-processors, Memristive Devices for Brain-Inspired Computing, 2020 pdf

2019

2018

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