Publications

PUBLICATIONS IN REFEREED JOURNALS and ARTICLES:

  • Zyarah, Abdullah M., and Dhireesha Kudithipudi. “Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis.ACM Journal on Emerging Technologies in Computing Systems (JETC). xx (2019): xx (accepted).
  • Zyarah, Abdullah M., and Dhireesha Kudithipudi. “Neuromorphic Architecture for the Hierarchical Temporal Memory.IEEE Transactions on Emerging Topics in Computational Intelligence 3, no. 1 (2019): 4-14.
  • Zyarah, Abdullah M., and Dhireesha Kudithipudi. “Semi-Trained Memristive Crossbar Computing Engine with In Situ Learning Accelerator.ACM Journal on Emerging Technologies in Computing Systems (JETC) 14.4 (2018): 43.
  • Zyarah, Abdullah M.Design and Analysis of a Reconfigurable Hierarchical Temporal Memory Architecture.” (2015).

PUBLICATIONS IN CONFERENCES:

  • Zyarah, Abdullah M., Nicholas Soures, and Dhireesha Kudithipudi. “On-Device Learning in Memristor Spiking Neural Networks.” In Circuits and Systems (ISCAS), 2018 IEEE International Symposium on, pp. 1-5. IEEE, 2018.
  • Soures, Nicholas, Abdullah Zyarah, Kristofor David Carlson, James Bradley Aimone, and Dhireesha Kudithipudi. How Neural Plasticity Boosts Performance of Spiking Neural Networks. No. SAND2017-5569C. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2017.
  • Zyarah, Abdullah M., Nicholas Soures, Lydia Hays, Robin B. Jacobs-Gedrim, Sapan Agarwal, Matthew Marinella, and Dhireesha Kudithipudi. “Ziksa: On-chip learning accelerator with memristor crossbars for multilevel neural networks.” In Circuits and Systems (ISCAS), 2017 IEEE International Symposium on, pp. 1-4. IEEE, 2017.
  • Zyarah, Abdullah M., and Dhireesha Kudithipudi. “Resource Sharing in Feed Forward Neural Networks for Energy Efficiency.” Circuits and Systems (MWSCAS), 2017 IEEE 60th International Midwest Symposium on
  • Soures, Nicholas, Lydia Hays, Eric Bohannon, Abdullah M. Zyarah, and Dhireesha Kudithipudi. “On-Device STDP and Synaptic Normalization for Neuromemristive Spiking Neural Network.” Circuits and Systems (MWSCAS), 2017 IEEE 60th International Midwest Symposium on.
  • Abdullah M. Zyarah, and Dhireesha Kudithipudi. “Extreme learning machine as a generalizable classification engine.” In Neural Networks (IJCNN), 2017 International Joint Conference on, pp. 3371-3376. IEEE, 2017
  • Abdullah M. Zyarah, Abhishek Ramesh, Cory Merkel, Dhireesha Kudithipudi, “Optimized hardware framework of MLP with random hidden layers“, Proc. SPIE 9850, Machine Intelligence and Bio-inspired Computation: Theory and Applications X, 985007 (May 12, 2016); doi:10.1117/12.2225498.
  •  Abdullah M. Zyarah and Dhireesha Kudithipudi, “Reconfigurable Hardware Architecture of the Spatial Pooler of Hierarchical Temporal Memory“, 2015 28th IEEE International System-on-Chip Conference (SOCC) – Emerging and Evolutionary Design; 09/2015.

Posters:

  • Abdullah M. Zyarah and Dhireesha Kudithipudi “Memristive Crossbar Computing Engine with In-Situ Learning Accelerator“, 2nd AI Compute Symposium, IBM T.J. Watson Research Center Yorktown Heights, New York, 2018.
  • Abdullah M. Zyarah and Dhireesha Kudithipudi “Next-Generation Cognitive Hardware with Nonvolatile Neuromemristive SystemsR.I.T Graduate Showcase, Rochester, NY, 2017.