Melika Payvand

Position:
Research Fellow
Email:
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I received my masters and PhD degree in Electrical and Computer Engineering at University of California Santa Barbara in 2012 and 2016 respectively. During my years in Santa Barbara, I grew large interests in understanding how the brain works and with the background I had in VLSI, I was naturally attracted to the field of neuromorphic VLSI. During my PhD my main focus was to design configurable CMOS memory and neuromorphic platforms to enable memristor integration and utilize their nano-features as memory and artificial synapses.
I joined INI in March 2017 as a post-doc and then as a scientist in Neuromorphic Cognitive Systems group to continue pursuing my interests in the field by working on designing neuromorphic chips which exploit different characteristics of memristors to enable low power and highly dense solutions for biomedical and IoT edge applications.


Summary of Interests and Experience:Neuromorphic VLSI Design, Mixed-Signal IC Design, Neural Coding Algorithms, Spiking Neural Networks

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
  • Covi, Erika, Elisa Donati, Hadi Heidari, David Kappel, Xiangpeng Liang, Melika Payvand, and Wei Wang Adaptive Extreme Edge Computing for Wearable Devices, arXiv, 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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