Tarek Taha
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Publications

Book Chapter

  1. B. Walters, C. Lammie, J. Eshraghian, C. Yakopcic, T. Taha, R. Genov, M. V. Jacob, A. Amirsoleimani, M. R. Azghadi, “Chapter 26: Memristive Devices for Neuromorphic and Deep Learning Applications,” Advanced Memory Technology: Functional Materials and Devices, 2023.

  2. Z. Alom, V. R. Bontupalli, and T. M. Taha, “Intrusion Detection Using Deep Belief Network and Extreme Learning Machine,” Artificial Intelligence: Concepts, Methodologies, Tools, and Applications: Concepts, Methodologies, Tools, and Applications, 2017.

  3. T. M. Taha, R. Hasan, C. Yakopcic, and M. R. McLean, “Exploring the Design Space of Specialized Multicore Neural Processors,” Cybersecurity Systems for Human Cognition Augmentation, R. Pino, A. Kott, and M Shevenell (ed), Springer. July 2014.

  4. Invited book chapter: Tanvir Atahary, Tarek Taha, and Scott Douglass, “Hardware Accelerated Mining of Domain Knowledge,” Network Science and Cyber Security, R. Pino (ed), Springer. July 2013.

  5. C. Yakopcic, T. M. Taha, G. Subramanyam, R. Pino, and S. Rogers, “Memristor SPICE Modeling,” in Advances in Neuromorphic Memristor Science and Applications, by R. Kozma, R. Pino, and G. Pazienza (eds), Springer. July 2012.

Journal

  1. A Henderson, C Yakopcic, C Merkel, H Hazan, S Harbour, T Taha, “Memristor Based Liquid State Machine with Method for In-Situ Training,” IEEE Transactions on Nanotechnology, 2024.

  2. N Rahman, T Atahary, C Yakopcic, TM Taha, S Douglass, “Q-learning based Cognitive Domain Ontology Representation and Solving on Low Power Computing Platforms,” IEEE Access, 2023.

  3. Y Qi, S Zhang, TM Taha, “TRIM: A Design Space Exploration Model for Deep Neural Networks Inference and Training Accelerators,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022.

  4. Austin Shallcross, Krishnamurthy Mahalingam, Eunsung Shin, Guru Subramanyam, Md Shahanur Alam, Tarek Taha, Sabyasachi Ganguli, Cynthia Bowers, Benson Athey, Albert Hilton, Ajit Roy, Rohan Dhall, “Transmission Electron Microscopy Study on the Effect of Thermal and Electrical Stimuli on Ge2Te3 Based Memristor Devices,” Frontiers in Electronics, 2022.

  5. H Chen, TM Taha, VP Chodavarapu, “Towards Improved Inertial Navigation by Reducing Errors Using Deep Learning Methodology,” Applied Sciences, 2022.

  6. MZ Alom, VK Asari, A Parwani, TM Taha, “Microscopic Nuclei Classification, Segmentation, and Detection with improved Deep Convolutional Neural Networks (DCNN),” Diagnostic Pathology, arXiv:1811.03447, 2021.

  7. MZ Alom, M Hasan, C Yakopcic, TM Taha, VK Asari, “Inception recurrent convolutional neural network for object recognition,” Machine Vision and Applications, 32 (1), 1-14, 2021.

  8. Ayesha Zaman, Guru Subramanyam, Eunsung Shin, Chris Yakopcic, Tarek Taha, Ahmed Ehteshamul Islam, Sabyasachi Ganguli, Donald Dorsey, Ajit Roy, “Experimental Verification of Current Conduction Mechanism for a Lithium Niobate Based Memristor,” ECS Journal of Solid State Science and Technology, 2020.

  9. MZ Alom, T Aspiras, TM Taha, T Bowen, VK Asari, “MitosisNet: End-to-End Mitotic Cell Detection by Multi-Task Learning,” IEEE Access, 2020.

  10. Z. Alom, M. Hasan, C. Yakopcic, T. M. Taha, V. Asari, “Improved Inception-Residual Convolutional Neural Network for Object Recognition” Neural Computing and Applications, https:link.springer.comarticle10.1007/s00521-018-3627-6, 2020.

  11. C. Yakopcic, T. M. Taha, D. J. Mountain, T. Salter, M. J. Marinella, and M. McLean, “Memristor Model Optimization Based on Parameter Extraction from Device Characterization Data,” IEEE Transactions on Computer Aided Design, 2019.

  12. M. Z. Alom, M. Hasan, C. Yakopcic, T. M. Taha, V. Asari, “Recurrent Residual U-Net for Medical Image Segmentation,” Journal of Medical Imaging, 2019.

  13. M. Z. Alom, C. Yakopcic, M. S. Nasrin, T. M. Taha, and V. K. Asari, “Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network” Journal of Digital Imaging, arXiv:1811.04241, 2019.

  14. R. Hasan, C. Yakopcic, T. M. Taha, “Ex-situ training of large memristor crossbars for neural network applications,” Analog Integrated Circuits and Signal Processing, https:doi.org10.1007s10470-018-1303-5, 2019.

  15. MJ Edmonds, T Atahary, S Douglass, T Taha, “Hardware Accelerated Semantic Declarative Memory Systems through CUDA and MapReduce,” IEEE Transactions on Parallel and Distributed Systems, Volume: 30, Issue: 3, March 1, 2019.

  16. MZ Alom, C Yakopcic, M Hasan, TM Taha, VK Asari, “Recurrent residual U-Net for medical image segmentation,” Journal of Medical Imaging, 6 (1), 014006, 2019. arXiv preprint arXiv:1802.06955, 2018.

  17. M. Z. Alom, T. M. Taha, C. Yakopcic, S. Westberg, P. Sidike, M. S. Nasrin, M. Hasan, B. C. Van Essen, A. A. S. Awwal, and V. K. Asari, “A State-of-the-Art Survey on Deep Learning Theory and Architectures,” Electronics, 8(3), 292, 2019. arXiv preprint arXiv:1803.01164, 2018.

  18. V Bontupalli, C Yakopcic, R Hasan, TM Taha, “Efficient Memristor-Based Architecture for Intrusion Detection and High-Speed Packet Classification,” ACM Journal on Emerging Technologies in Computing Systems (JETC), 14 (4), 41, 2018.

  19. C. Yakopcic, S. Wang, W. Wang, E. Shin, J. Boeckl, G. Subramanyam, and T. M. Taha, “Filament Formation in Lithium Niobate Memristors Supports Neuromorphic Programming Capability,” Neural Computing and Applications, vol. 30, no. 12, pp. 3773-3779, Dec. 2018.

  20. C. Yakopcic, R. Hasan, and T. M. Taha, “Flexible Memristor Based Neuromorphic System for Implementing Multi-layer Neural Network Algorithms,” International Journal of Parallel, Emergent and Distributed Systems, vol. 33, no. 4, pp. 408-429, Aug. 2018.

  21. MZ Alom, P Sidike, M Hasan, TM Taha, VK Asari, “Handwritten Bangla Character Recognition Using the State-of-the-Art Deep Convolutional Neural Networks,” Computational Intelligence and Neuroscience, 2018.

  22. M. Z. Alom, M. Hasan, C. Yakopcic, T. M. Taha, V. K. Asari, “Improved inception-residual convolutional neural network for object recognition,” Journal of Neural Computing and Applications (NCAA), 2018. arXiv preprint arXiv:1712.09888, 2017.

  23. R. Hasan, T. M. Taha, ad C. Yakopcic, “A Fast Training Method for Memristor Crossbar Based Multi-layer Neural Networks”, Analog Integrated Circuits and Signal Processing, 93(3), 443-454, 2017.

  24. R. Hasan, T. M. Taha, and C. Yakopcic, “On-chip Training of Memristor Crossbar Based Multi-layer Neural Networks,” Microelectronics Journal, 66, 31-40, 2017.

  25. M. Z. Alom, P. Sidike, T. M. Taha, V. K. Asari, “State Preserving Extreme Learning Machine: A Monotonically Increasing Learning Approach,” Neural Processing Letters, 45(2), 703-725, 2017.

  26. P. Sidike, E. Krieger, M. Z. Alom, V. K. Asari, and T. Taha, “A fast single image super-resolution via directional edge guided regularized extreme learning regression,” Signal, Image and Video Processing, 11(5), 91-988, July 2017.

  27. P. Sidike, E. Krieger, M. Z. Alom, V. K. Asari, and T. Taha, “A fast single image super-resolution via directional edge guided regularized extreme learning regression,” Signal, Image and Video Processing, 11(5), 91-988, July 2017.

  28. C. Yakopcic, S. Wang, W. Wang, E. Shin, J. Boeckl, G. Subramanyam, and T. M. Taha, “Filament Formation in Lithium Niobate Memristors Supports Neuromorphic Programming Capability” Neural Computing and Applications, 1-7, 2017.

  29. C. Yakopcic, V. Bontupalli, R. Hasan, D. Mountain, and T. M. Taha, “Self-biasing memristor crossbar used for string matching and TCAM implementation,” Electronics Letters, vol. 53, no. 7, pp. 463-465, March, 2017.

  30. S. Wang, W. Wang, C. Yakopcic, E. Shin, G. Subramanyam and T. M. Taha, “Experimental study of LiNbO3 memristors for use in neuromorphic computing,” Microelectronic Engineering, vol. 168, pp. 37-40, Jan. 2017.

  31. C. Merkel, R. Hasan, N. Soures, D. Kudithipudi, T. Taha, S. Agarwal, and M. Marinella, “Neuromemristive Systems: Boosting Efficiency through Brain-Inspired Computing”, Computer, 49(10), 56-64, Oct. 2016.

  32. M. Z. Alom, P. Sidike, T. M. Taha, and V. K. Asari, “State Preserving Extreme Learning Machine: A Monotonically Increasing Learning Approach,” Neural Processing Letters, September 2016.

  33. S. Wang, W. Wang, C. Yakopcic, E. Shin, G. Subramanyam and T. M. Taha, “Reconfigurable Neuromorphic Crossbars Based on Titanium Oxide Memristors,” Electronics Letters, vol. 52, no. 20, pp. 1673-1675, September 2016.

  34. T. Atahary, T. M. Taha, and S. Douglass, “Parallelized mining of domain knowledge on GPGPU and Xeon Phi clusters,” The Journal of Supercomputing, Volume 72, Issue 6, pp 2132-2156, June 2016.

  35. C. Yakopcic and T. M. Taha, “Model for maximum crossbar size based on input driver impedance,” Electronics Letters, vol. 52 no. 1, pp. 25-27, 2016.

  36. C. Yakopcic, R. Hasan, and T. M. Taha, “Hybrid Crossbar Architecture for a Memristor Based Cache,” Microelectronics Journal, vol. 46, no. 11, pp. 1020-1032, November, 2015.

  37. C. Yakopcic and T. M. Taha, “Determining optimal switching speed for memristors in a neuromorphic system,” Electronics Letters, vol. 51 no. 21, pp. 1637-1639, 2015.

  38. Zahangir Alom, Venkata Ramesh Bontupalli, and Tarek M. Taha “Intrusion Detection Using Deep Belief Network and Extreme Learning Machine”, International Journal of Monitoring and Surveillance Technologies Research, 3(2), 36-56, April 2015.

  39. C. Yakopcic, T. M. Taha, M. R. McLean, “Method for ex-situ training in a memristor-based neuromorphic circuit using a robust weight programming method,” Electronics Letters, vol. 51, no. 12, pp. 899-900, 2015.

  40. K. Mohammad, A. Kabeer, T. M. Taha, “On-Chip power minimization using serialization-widening with frequent value encoding,” VLSI Design, 6, January 2014.

  41. C. Yakopcic, R. Hasan, T. M. Taha, M. McLean, and D. Palmer, “Memristor-based neuron circuit and method for applying a learning algorithm in SPICE,” IET Electronics Letters, 2014.

  42. C. Chen and T. M. Taha, “A Communication Reduction Approach to Iteratively Solve Large Sparse Linear Systems on a GPGPU Cluster,” Cluster Computing, Volume 17, Issue 2, pp 327-337, June 2014.

  43. C. Yakopcic, T. M. Taha, G. Subramanyam, and R. E. Pino, “Generalized Memristive Device SPICE Model and its Application in Circuit Design,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 32:(8), 1201-1214, August 2013. This model has been incorporated into the parallel SPICE simulator, XYCE, from Sandia National Labs. See XYCE Dec 2015 release notes about Yakopcic memristor model.

  44. C. Yakopcic, T. M. Taha, G. Subramanyam, R. E. Pino, S. Rogers, “A Memristor Device Model,” IEEE Electron Device Letters, IEEE Electron Device Letters, 30(10), 1436-1438, October 2011.

  45. P. Yalamanchili, S. Mohan, R. Jalasutram, and T. M. Taha, “Acceleration of Hierarchical Bayesian Network Based Cortical Models on Multicore Architectures,” Parallel Computing, 36:(8), 449-468, August 2010.

  46. B. Han and T. M. Taha, “Acceleration of spiking neural network based pattern recognition on NVIDIA graphics processors,” Applied Optics, 49:(101), 83-91, April 2010.

  47. K. L. Rice, T. M. Taha, A. M. Chowdhury, and A. Awwal, “Design and Acceleration of Phase-only Filter Based Optical Pattern Recognition for Fingerprint Identification,” Optical Engineering, vol. 48, November 2009.

  48. A. Awwal, K. L. Rice, and T. M. Taha, “Hardware-Accelerated Optical Alignment of Lasers Using Beam-Specific Matched Filters,” Applied Optics, 48:(27), 5190-5196, September 2009.

  49. C. Vutsinas, K. L. Rice, and T. M. Taha, “A Context Switching Streaming Memory Architecture to Accelerate a Neocortex Model,” Microprocessors and Microsystems, 33:(2), 117-128, March 2009.

  50. A. Awwal, K. L. Rice, and T. M. Taha, “Fast Implementation of Matched Filter Based Automatic Alignment Image Processing,” Optics and Laser Technology, 41:(2), 193-197, March 2009.

  51. K. L. Rice, C. Vutsinas, and T. M. Taha, “A Scaling Analysis of a Neocortex Model Implementation on the Cray XD1,” Journal of Supercomputing, 47:(1), 21-43, January 2009.

  52. K. L. Rice, C. Vutsinas, and T. M. Taha, “Hardware Acceleration of Image Recognition through a Visual Cortex Model,” Optics & Laser Technology, 40:(6), 795-802, September 2008.

  53. T. M. Taha, and D. S. Wills, “An Analytical Model of Superscalar Processor Performance,” IEEE Transactions on Computers, 57:(3), 389-403, March 2008.

  54. S. M. Chai, T. M. Taha, D. S. Wills, and J. D. Meindl, “Heterogeneous Architecture Models for Interconnect Motivated System Design,” IEEE Transactions on VLSI Systems, Special Issue on System Level Interconnect Prediction, 8:(6), 660-670, 2000.

  55. D. S. Wills, J. M. Baker, H. H. Cat, S. M. Chai, L. Codrescu, J. Cruz-Rivera, J. Eble, A. Gentile, M. Hopper, W. S. Lacy, A. Lopez-Lagunas, P. May, S. Smith, and T. Taha, “Processing Architectures for Smart Pixel Systems,” IEEE Journal of Selected Topics in Quantum Electronics, 2:(1), 24-34, 1996.

Conference

  1. Rashedul Islam, Shahanur Alam, Chris Yakopcic, Nayim Rahman, Simon Khan, Tarek Taha, “Unsupervised Anomaly Detection for Automotive CAN Bus on the Intel Loihi,” International Joint Conference on Neural Networks (IJCNN), 2024.

  2. M Alam, C Yakopcic, TM Taha, “On-Chip Optimization and Deep Reinforcement Learning in Memristor Based Computing,” ACM International Symposium on Nanoscale Architectures (NanoArch), 2023.

  3. S Nasrin, MZ Alom, TM Taha, “Histopathological image classification with unsupervised approaches using deep convolutional autoencoder and k-nearest neighbors,” Applications of Machine Learning, 2023.

  4. S Nasrin, MZ Alom, TM Taha, “Batch effect detection and removal for human liver RNA-Seq with an unsupervised learning approach,” Applications of Machine Learning, 2023.

  5. A Henderson, C Yakopcic, J Colter, S Harbour, T Taha, “Blockchain-Enabled Federated Learning with Neuromorphic Edge Devices for Drone Identification and Flight Mode Detection,” IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC), 2023.

  6. MS Alam, S Zhang, C Yakopcic, T Taha, “Memristor Based Online Learning Neuromorphic Processor for Adaptive Modulation Spectrum Sensing in Communication Jammed Environments,” IEEE National Aerospace and Electronics Conference (NAECON), 2023.

  7. Nayim Rahman, Chris Yakopcic, Ricardo Lent, Janette C Briones, David Chelmins, Rachel Dudukovitch, Aaron Smith, Adam Gannon, Michael Lowry, Marcus S Murbach, Alejandro J Salas, Tarek M Taha, “Neuromorphic Hardware in Outer Space: Software Defined Networking Executed on an In-Orbit Loihi Spiking Processor,” IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW), 2023.

  8. S Zhang, C Yakopcic, TM Taha, “Neural Network Based Automatic Modulation Classification with Online Training,” IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW), 2023.

  9. A Henderson, S Harbour, C Yakopcic, T Taha, D Brown, J Tieman, G Hall, “Spiking Neural Networks for LPI Radar Waveform Recognition with Neuromorphic Computing,” IEEE Radar Conference (RadarConf23), 2023.

  10. A Henderson, C Yakopcic, S Harbour, T Taha, C Merkel, H Hazan, “Circuit Optimization Techniques for Efficient Ex-Situ Training of Robust Memristor Based Liquid State Machine,” Proceedings of the 17th ACM International Symposium on Nanoscale Architectures (NanoArch), 2022. Received BEST PAPER Award

  11. A Henderson, C Yakopcic, S Harbour, TM Taha, “Detection and Classification of Drones Through Acoustic Features Using a Spike-Based Reservoir Computer for Low Power Applications,” IEEE/AIAA 41st Digital Avionics Systems Conference (DASC), 2022. Received BEST OF TRACK Award

  12. A Henderson, C Yakopcic, S Harbour, TM Taha, “Memristor Based Circuit Design for Liquid State Machine Verified with Temporal Classification,” International Joint Conference on Neural Networks (IJCNN), 2022.

  13. S Alam, C Yakopcic, TM Taha, “Memristor Based Federated Learning for Network Security on the Edge using Processing in Memory (PIM) Computing,” International Joint Conference on Neural Networks (IJCNN), 2022.

  14. Marcus Murbach, Alejandro Salas, Michael Lowry, Eric Barszcz, Janette Briones, Peter Schemmel, Michael Mercury, Tarek Taha, “techedsat-13: the first flight of a neuromorphic processor,” CubeSat Developers Workshop, 2022.

  15. S Reynolds, D Fan, TM Taha, A DeMange, T Jenkins, “An Implementation of Simultaneous Localization and Mapping Using Dynamic Field Theory,” IEEE National Aerospace and Electronics Conference (NAECON), 2021.

  16. D Fan, A DeMange, T Jenkins, Y Adams, T Taha, “Symbolic Probabilistic Cognitive Reasoner on Neuromorphic Hardware,” IEEE National Aerospace and Electronics Conference (NAECON), 2021.

  17. C Yakopcic, TM Taha, SS Karri, G Subramanyam, AD Smith, JC Briones, “Design and Analysis of Convolutional Neural Network for RF Signal Modulation Classification for In-Orbit Deployment,” IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW), 2021.

  18. K Vassilo, T Taha, A Mehmood, “Infrared Image Super Resolution with Deep Neural Networks,” Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.

  19. Y Jaoudi, C Yakopcic, T Taha, “Conversion of an Unsupervised Anomaly Detection System to Spiking Neural Network for Car Hacking Identification,” International Green and Sustainable Computing Workshops (IGSC), 2020.

  20. MS Alam, C Yakopcic, G Subramanyam, TM Taha, “Memristor Based Neuromorphic Network Security System Capable of Online Incremental Learning and Anomaly Detection,” International Green and Sustainable Computing Workshops (IGSC), 2020.

  21. MZ Alom, L He, TM Taha, VK Asari, “Fast and accurate Magnetic Resonance Image (MRI) reconstruction with NABLA-N network,” Applications of Machine Learning, 2020.

  22. S Nasrin, MZ Alom, VK Asari, TM Taha, “PColorSeg_Net: Investigating the impact of different color spaces for pathological image segmentation,” Applications of Machine Learning, 2020.

  23. MS Alam, C Yakopcic, G Subramanyam, TM Taha, “Memristor Based Neuromorphic Adaptive Resonance Theory for One-Shot Online Learning and Network Intrusion Detection,” International Conference on Neuromorphic Systems, 2020.

  24. M Hampo, D Fan, T Jenkins, A DeMange, S Westberg, T Bihl, T Taha, “Associative Memory in Spiking Neural Network Form Implemented on Neuromorphic Hardware,” International Conference on Neuromorphic Systems, 2020.

  25. C Yakopcic, N Rahman, T Atahary, TM Taha, S Douglass, “Leveraging the Manycore Architecture of the Loihi Spiking Processor to Perform Quasi-Complete Constraint Satisfaction,” International Joint Conference on Neural Networks (IJCNN), 2020.

  26. BR Fernando, Y Qi, C Yakopcic, TM Taha, “3D Memristor Crossbar Architecture for a Multicore Neuromorphic System,” International Joint Conference on Neural Networks (IJCNN), 2020.

  27. Md Zahangir Alom, M M Shaifur Rahman, Mst Shamima Nasrin, Tarek M. Taha, Vijayan K. Asari, “COVID_MTNet: COVID-19 Detection with Multi-Task Deep Learning Approaches,” arXiv:2004.03747, 2020.

  28. TM Taha, C Yakopcic, N Rahman, T Atahary, S Douglass, “Cognitive Domain Ontologies: HPCs to Ultra Low Power Neuromorphic Platforms,” Proceedings of the Neuro-inspired Computational Elements Workshop, 2020.

  29. S Nasrin, MZ Alom, TM Taha, VK Asari, “PColorNet: investigating the impact of different color spaces for pathological image classification,” Medical Imaging 2020: Digital Pathology, 2020.

  30. C Yakopcic, N Rahman, T Atahary, TM Taha, S Douglass, “Solving Constraint Satisfaction Problems Using the Loihi Spiking Neuromorphic Processor,” Design, Automation & Test in Europe Conference & Exhibition (DATE), 2020.

  31. MZ Alom, T Aspiras, TM Taha, VK Asari, “Skin cancer segmentation and classification with improved deep convolutional neural network,” Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications, 2020

  32. K Chisholm, C Yakopcic, MS Alam, TM Taha, “Multilayer Perceptron Algorithms for Network Intrusion Detection on Portable Low Power Hardware,” Computing and Communication Workshop and Conference (CCWC), 2020.

  33. K Vassilo, C Heatwole, T Taha, A Mehmood, “Multi-Step Reinforcement Learning for Single Image Super-Resolution,” IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020.

  34. TM Taha, R Raiyan, S Akhtar, R Awwal, MZ Alom, “Non-invasive detection of breast cancer using deep learning,” Applications of Machine Learning, 2019.

  35. MZ Alom, T Aspiras, TM Taha, VK Asari, “Histopathological image classification with deep convolutional neural networks,” Applications of Machine Learning, 2019.

  36. Md Shahanur Alam, B Rasitha Fernando, Yassine Jaoudi, Chris Yakopcic, Raqibul Hasan, Tarek M Taha, Guru Subramanyam, “Memristor Based Autoencoder for Unsupervised Real-Time Network Intrusion and Anomaly Detection,” International Conference on Neuromorphic Systems, 2019.

  37. C Yakopcic, N Rahman, T Atahary, TM Taha, A Beigh, S Douglass, “High Speed Approximate Cognitive Domain Ontologies for Constrained Asset Allocation based on Spiking Neurons,” IEEE National Aerospace and Electronics Conference (NAECON), 2019.

  38. A Reiling, W Mitchell, S Westberg, E Balster, T Taha, “CNN Optimization with a Genetic Algorithm,” IEEE National Aerospace and Electronics Conference (NAECON), 2019.

  39. Ayesha Zaman, Chris Yakopcic, Shu Wang, Eunsung Shin, Weisong Wang, Tarek M Taha, Guru Subramanyam, “Analysis of Lithium Niobate Memristor Devices for Neuromorphic Programability,” IEEE National Aerospace and Electronics Conference (NAECON), 2019. Received 1st place BEST POSTER Award

  40. S Nasrin, MZ Alom, R Burada, TM Taha, VK Asari, “Medical Image Denoising with Recurrent Residual U-Net (R2U-Net) base Auto-Encoder,” IEEE National Aerospace and Electronics Conference (NAECON), 2019. Received 2nd place BEST POSTER Award

  41. C Yakopcic, BR Fernando, TM Taha, “Design Space Evaluation of a Memristor Crossbar Based Multilayer Perceptron for Image Processing,” International Joint Conference on Neural Networks (IJCNN), 2019.

  42. C. Yakopcic, N. Rahman, T. Atahary, T. Taha, A. Beigh, and S. Douglass, “High Speed Cognitive Domain Ontologies for Asset Allocation Using Loihi Spiking Neurons,” IEEE/INNS International Joint Conference on Neural Networks (IJCNN), arXiv:1906.12338, 2019.

  43. C Yakopcic, J Freeman, TM Taha, S Douglass, Q Wu, “Cognitive Domain Ontologies Based on Loihi Spiking Neurons Implemented Using a Confabulation Inspired Network, ” IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW), 2019.

  44. Chris Yakopcic, Nayim Rahman, Tanvir Atahary, Md Zahangir Alom, Tarek M Taha, Alex Beigh, Scott Douglass, “Spiking Neural Network for Asset Allocation Implemented Using the TrueNorth System,” IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW), 2019.

  45. MZ Alom, T Aspiras, TM Taha, VK Asari, TJ Bowen, D Billiter, S Arkell, “Advanced Deep Convolutional Neural Network Approaches for Digital Pathology Image Analysis: a comprehensive evaluation with different use cases,” arXiv:1904.09075, 2019.

  46. M Zahangir Alom, T Aspiras, TM Taha, VK Asari, “Skin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks,” arXiv:1904.11126, 2019

  47. M. Z. Alom, T. Aspiras, T. M. Taha, V. K. Asari, and TJ Bowen, “Advanced deep convolutional neural network approaches for digital pathology image analysis: A comprehensive evaluation with different use cases,” Pathology Visions 2018,November 2018.

  48. W Mitchell, S Westberg, A Reiling, T Taha, E Balster, K Hill, “Generalized Power Modeling for Deep Learning,” IEEE National Aerospace and Electronics Conference (NAECON), 391-394, 2018.

  49. N Rahman, T Atahary, C Yakopcic, TM Taha, S Douglass, “Task Allocation Performance Comparison for Low Power Devices,” IEEE National Aerospace and Electronics Conference (NAECON), 247-253, 2018.

  50. MZ Alom, C Yakopcic, TM Taha, VK Asari, “Nuclei Segmentation with Recurrent Residual Convolutional Neural Networks based U-Net (R2U-Net),” IEEE National Aerospace and Electronics Conference (NAECON), 228-233, 2018

  51. MZ Alom, C Yakopcic, TM Taha, VK Asari, “Microscopic Blood Cell Classification Using Inception Recurrent Residual Convolutional Neural Networks,” IEEE National Aerospace and Electronics Conference (NAECON), 222-227, 2018.

  52. A Zaman, E Shin, C Yakopcic, TM Taha, G Subramanyam, “Experimental Study of Memristors for use in Neuromorphic Computing,” IEEE National Aerospace and Electronics Conference (NAECON), 370-374, 2018.

  53. C Yakopcic, T Atahary, TM Taha, A Beigh, S Douglass, “High Speed Approximate Cognitive Domain Ontologies for Asset Allocation based on Isolated Spiking Neurons,” IEEE National Aerospace and Electronics Conference (NAECON), 241-246, 2018.

  54. T Mealey, TM Taha, “Accelerating Inference In Long Short-Term Memory Neural Networks,” IEEE National Aerospace and Electronics Conference (NAECON), 382-390, 2018.

  55. C Yakopcic, MT Taha, “Analysis and Design of Memristor Crossbar Based Neuromorphic Intrusion Detection Hardware,” International Joint Conference on Neural Networks (IJCNN), 2018.

  56. BR Fernando, R Hasan, MT Taha, “Low Power Memristor Crossbar Based Winner Takes All Circuit,” International Joint Conference on Neural Networks (IJCNN), 2018.

  57. Y Qi, R Hasan, TM Taha, “Socrates-D 2.0: A Low Power High Throughput Architecture for Deep Network Training,” International Joint Conference on Neural Networks (IJCNN), 2018.

  58. MZ Alom, AT Moody, N Maruyama, BC Van Essen, TM Taha, “Effective Quantization Approaches for Recurrent Neural Networks,” International Joint Conference on Neural Networks (IJCNN), 2018. arXiv:1802.02615, 2018.

  59. MZ Alom, T Josue, MN Rahman, W Mitchell, C Yakopcic, TM Taha, “Deep Versus Wide Convolutional Neural Networks for Object Recognition on Neuromorphic System,” International Joint Conference on Neural Networks (IJCNN), 2018. arXiv:1802.02608, 2018

  60. Md Zahangir Alom, Abdul AS Awwal, Roger Lowe-Webb, and Tarek M. Taha. “Optical beam classification using deep learning: a comparison with rule-and feature-based classification.” In Optics and Photonics for Information Processing XI, vol. 10395, p. 103950O. International Society for Optics and Photonics, 2017.

  61. Y. Qi, R. Hasan, R. Fernando, T. Taha, “Socrates-D: Multicore Architecture for On-line Learning,” IEEE International Conference on Rebooting Computing, November 2017.

  62. Md. Zahangir Alom, Abdul A. S. Awwal, Roger R. Lowe-Webb, Tarek M. Taha, “Optical beam classification using deep learning: a comparison with rule and feature based classification,” Optics and Photonics for Information Processing XI, August 2017.

  63. Raqibul Hasan and Tarek M. Taha, “Memristor Crossbar Based Winner Take All Circuit Design for Self-organization,” Neuromorphic Computing Symposium, 2017.

  64. T. Atahary, T. Taha, S. Douglass, “Parallelizing Knowledge Mining in a Cognitive Agent for Autonomous Decision Making”, IEEE Computing Conference 2017, July 2017.

  65. William Mitchell, Ted Josue, Ben Ausdenmoore, Jeff Clark, Tarek Taha, Nate Adams, Dan Krane, “Accelerated Pattern Matching on a Neuromorphic Processor with Application to Forensic DNA Profile Searches,” IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, June, 2017.

  66. Chris Yakopcic, Tarek M. Taha, “Memristor Crossbar Based Implementation of a Multilayer Perceptron,”IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, June, 2017.

  67. Yangjie Qi, Tarek Taha, “Sparse Connected Deep Neural Network for Multicore System,” IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, June, 2017.

  68. Raqibul Hasan, Yangjie Qi, Tarek Taha, “A Low Power High Throughput Architecture for Deep Network Training,” IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, June, 2017.

  69. Md Zahangir Alom, Tarek Taha “Robust Multi-view Pedestrian Tracking Using Neural Networks,”IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, June, 2017.

  70. Md Zahangir Alom, Tarek Taha, “Network Intrusion Detection for Cyber Security using Unsupervised Deep Learning Approaches,” IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, June, 2017.

  71. Chris Yakopcic, Nayim Rahman, Tanvir Atahary, and Tarek M. Taha Scott Douglass, “Cognitive Domain Ontologies in a Memristor Crossbar Architecture,” IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, June, 2017.

  72. Nayim Rahman, Tarek Taha, Tanvir Atahary, and Scott Douglass, “A Pattern Matching Approach to Map Cognitive Domain Ontologies to the IBM TrueNorth Processor,” IEEE Cognitive Communications for Aerospace Applications Workshop, June 2017.

  73. Nayim Rahman, Tanvir Atahary, Tarek Taha and Scott Douglass. “Cognitive Domain Ontologies on the TrueNorth Neurosynaptic System” IEEE International Joint Conference on Neural Networks, May 2017.

  74. R. Hasan, T. M. Taha, “On-chip Training of Memristor Based Deep Neural Networks,” IEEE International Joint Conference on Neural Networks, May 2017.

  75. C. Yakopcic, S. Wang, W. Wang, E. Shin, G. Subramanyam and T. Taha, “Methods for High Resolution Programming in Lithuim Niobate Memristors for Neuromorphic Hardware,” IEEE International Joint Conference on Neural Networks, May 2017.

  76. C. Yakopcic, Z. Alom and T. Taha, “Extremely Parallel Memristor Crossbar Architecture for Convolutional Neural Network Implementation,” IEEE International Joint Conference on Neural Networks, May 2017.

  77. Md Zahangir Alom, Tarek M. Taha, and Khan Iftekharuddin, “Object Recognition using Cellular Simultaneous Recurrent Networks and Convolutional Neural Network,” IEEE International Joint Conference on Neural Networks, May 2017.

  78. Md Zahangir Alom, Brian Van Essen, Adam T. Moody, David Peter Widemann, and Tarek M. Taha, “Convolutional Sparse Coding on Neurosynaptic Cognitive System,” IEEE International Joint Conference on Neural Networks, May 2017.

  79. Md Zahangir Alom, and Tarek M. Taha, “Network Intrusion Detection for Cyber Security on Neuromorphic Computing System,” IEEE International Joint Conference on Neural Networks, May 2017.

  80. Md Zahangir Alom, Brian Van Essen, Adam T. Moody, David Peter Widemann, and Tarek M. Taha, “Quadratic Unconstrained Binary Optimization (QUBO) on Neuromorphic Computing System,” IEEE International Joint Conference on Neural Networks, May 2017.

  81. R. Hasan, T. M. Taha, C. Yakopcic, and D. Mountain, “High throughput neural network based embedded streaming multicore processors,” IEEE International Conference on Rebooting Computing (ICRC), San Diego, CA, November 2016.

  82. F. Palenzuela, M. Shaffer, M. Ennis, J. Gorski, D. McGrew, D. Yowler, D. White, L. Holbrook, C. Yakopcic, and T. M. Taha, “Multilayer Perceptron Algorithms for Cyberattack Detection,” IEEE National Aerospace and Electronics Conference, July, 2016.

  83. S. Wang, W. Wang, C. Yakopcic, E. Shin, G. Subramanyam and T. M. Taha, “Memristor Devices for use in Neuromorphic Systems,” IEEE National Aerospace and Electronics Conference, July, 2016.

  84. C. Yakopcic, M. Z. Alom, and T. M. Taha, “Memristor Crossbar Deep Network Implementation Based on a Convolutional Neural Network,” IEEE International Joint Conference on Neural Networks (IJCNN), 2016.

  85. R. Hasan, T. M. Taha and C. Yakopcic, “Ex-situ Training of Dense Memristor Crossbar for Neuromorphic Applications,” in the proceedings of the IEEE International Symposium on Nanoscale Architectures, July, 2015.

  86. M. Z. Alom, P. Sidike, V. Asari, T. M. Taha, “State Preserving Extreme Learning Machine for Face Recognition,” IEEE International Joint Conference on Neural Networks (IJCNN), July 2015.

  87. C. Yakopcic and T. M. Taha, “Memristor Based Neuromorphic Circuit for Ex-Situ Training of Multi-Layer Neural Network Algorithms,” IEEE International Joint Conference on Neural Networks (IJCNN), July 2015.

  88. Md. Zahangir Alom, VenkataRamesh Bontupalli, Tarek M. Taha, “Intrusion Detection using Deep Belief Networks,” in the IEEE National Aerospace and Electronics Conference, 2015.

  89. R. Hasan, T. M. Taha, “Memristor Crossbar Based Unsupervised Training,” in the IEEE National Aerospace and Electronics Conference, 2015.

  90. C. Yakopcic, R. Hasan, T. M. Taha, and D. Palmer, “SPICE Analysis of Dense Memristor Crossbars for Low Power Neuromorphic Processor Designs” IEEE National Aerospace and Electronics Conference, June, 2015.

  91. S. Wang, W. Wang, E. Shin, C. Yakopcic, G. Subramanyam, T. M. Taha, “Lithium Based Memristive Devices” IEEE National Aerospace and Electronics Conference, June, 2015.

  92. C. Yakopcic, T. M. Taha, “Ex-Situ Programming in a Neuromorphic Memristor Based Crossbar Circuit” IEEE National Aerospace and Electronics Conference, June, 2015.

  93. R. Uppala, C. Yakopcic, T. M. Taha, “Methods for Reducing Memristor Crossbar Simulation Time” IEEE National Aerospace and Electronics Conference, June, 2015.

  94. C. Yakopcic, T. M. Taha, G. Subramanyam, and R. E. Pino, “Impact of Memristor Switching Noise in a Neuromorphic Crossbar” IEEE National Aerospace and Electronics Conference, June, 2015.

  95. M. Edmonds, T. Atahary, T. Taha, and S. Douglass, “High performance declarative memory systems through MapReduce,” In 16th IEEE ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2015.

  96. T. Atahary, T. Taha, F.Webber, S. Douglass, “Knowledge mining for cognitive agents through path based forward checking”. In 16th IEEE ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2015.

  97. R. Hasan, T. M. Taha, “Memristor Crossbar Based Low Power Intrusion Detection Systems” 17th Int'l Conf. on Computer and Information Technology, 2014.

  98. R. Hasan and T. M. Taha, “Memristor Crossbar Based Programmable Interconnects,” IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2014.

  99. T. M. Taha, R. Hasan, and C. Yakopcic, “Memristor Crossbar Based Multicore Neuromorphic Processors,” IEEE International System on Chip (SOC) Conference, 2014.

  100. R. Hasan, T. M. Taha, “Memristor Crossbar Based Low Cost Classifiers and Their Applications,” IEEE NAECON, 2014.

  101. Y. Qi, B. Zhang, T. M. Taha, H. Chen, and R. Hasan, “FPGA Design of a Multicore Neuromorphic Processing System,” IEEE NAECON, 2014.

  102. V. Bontupalli, R. Hasan, T. M. Taha, “Power Efficient Architecture for Network Intrusion Detection System,” IEEE NAECON, 2014.

  103. W. Wang, C. Yakopcic, E. Shin, K. Leedy, T. M. Taha, and G. Subramanyam, “Fabrication, Characterization, and Modeling of Memristor Devices,” IEEE NAECON, 2014.

  104. C. Yakopcic, T. M. Taha, and R. Hasan, “Hybrid Crossbar Architecture for a Memristor Based Memory,” IEEE NAECON, 2014.

  105. C. Yakopcic, R. Hasan, T. M. Taha, “Tolerance to Defective Memristors in a Neuromorphic Learning Circuit,” IEEE NAECON, 2014.

  106. Raqib Hasan and Tarek M. Taha, “Implementation of Polynomial Classifier Using Memristor Crossbar Circuits,” IEEE International Joint Conference on Neural Networks (IJCNN), 2014.

  107. Raqib Hasan and Tarek M. Taha, “Enabling Back Propagation Training of Memristor Crossbar Neuromorphic Processors,” IEEE International Joint Conference on Neural Networks (IJCNN), 2014.

  108. Chris Yakopcic, Raqib Hasan, Tarek M. Taha, Mark R. McLean, and Doug Palmer, “Memristor Neuron Circuits for Linearly and Non-Linearly Separable Functions,” IEEE International Joint Conference on Neural Networks (IJCNN), 2014.

  109. T. M. Taha, R. Hasan, C. Yakopcic, and M. R. McLean, “Exploring the Design Space of Specialized Multicore Neural Processors,” IEEE International Joint Conference on Neural Networks (IJCNN), 2013.

  110. R. Hasan and T. M. Taha, “On-Chip Routing for Neuromorphic Architectures,” IEEE International Joint Conference on Neural Networks (IJCNN), 2013.

  111. C. Yakopcic, T. M. Taha, G. Subramanyam, and R. E. Pino, “Memristor SPICE Model and Crossbar Simulation Based on Devices with Nanosecond Switching Time,” IEEE International Joint Conference on Neural Networks (IJCNN), 2013. Received BEST PAPER Award

  112. C. Yakopcic and T. M. Taha, “A Novel Memristor-Based Neural Architecture Capable of Perceptron Training Verified in SPICE,” IEEE International Joint Conference on Neural Networks (IJCNN), 2013.

  113. T. Atahary, T. M. Taha, S. Douglass, “Hardware Accelerated Cognitively Enhanced Complex Event Processing,” 14th IEEE ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2013), July, 2013.

  114. T. M. Taha, R. Hasan, C. Yakopcic, and M. R. McLean, “Memory Integrated Neural Network Accelerators,” Neuro-Inspired Computational Elements Workshop, Albuquerque, NM, February 26, 2013.

  115. C. Yakopcic, T. Taha, G. Subramanyam, and R. Pino, “A Generalized Memristor Device Model,” Network Science and Reconfigurable Systems for Cybersecurity Conference, 2012.

  116. T. Taha and S. Douglass, “Hardware Accelerated Mining of Domain Knowledge,” Network Science and Reconfigurable Systems for Cybersecurity Conference, 2012.

  117. C. Yakopcic, T. M. Taha, G. Subramanyam, and S. Rogers, “Memristor-based Readout Integrated Circuits,” SPIE Adaptive Coded Aperture Imaging and Non-Imaging Sensors V, August 2011.

  118. T. Taha and C. Chen, “Spiking Neural Networks on High Performance Compute Clusters,” SPIE Optics and Photonics for Information Processing V, August 2011.

  119. C. Yakopcic, T. M. Taha, G. Subramanyam, R. E. Pino, and S. Rogers, “Analysis of a Memristor based 1T1M Crossbar Achitecture,” IEEE International Joint Conference on Neural Networks (IJCNN), August 2011 (Invited paper).

  120. K. L. Rice, T. M. Taha, K. M. Iftekharuddin, K. Anderson, and T. Salan, “GPGPU Acceleration of Cellular Simultaneous Recurrent Networks Adapted for Maze Traversals,” IEEE International Joint Conference on Neural Networks (IJCNN), August 2011.

  121. C. Yakopcic, T. M. Taha, G. Subramanyam, and S. Rogers, “Multiple Memristor Read and Write Circuit for Neuromorphic Applications,” IEEE International Joint Conference on Neural Networks (IJCNN), August 2011 (Invited paper).

  122. C. Yakopcic, A. Sarangan, J. Gao, T. M. Taha, G. Subramanyam, and S. Rogers, “TiO2 Memristor Devices,” IEEE National Aerospace & Electronics Conference, July 2011.

  123. T. Messay, C. Chen, R. Ordonez and T. M. Taha, “GPGPU Acceleration of a Novel Calibration Method for Industrial Robots,” IEEE National Aerospace & Electronics Conference, July 2011.

  124. K. Rice, T. M. Taha, R. Miller, K. M. Iftekharuddin, K. Anderson, and T. Salan, “Accelerating CSRN based face recognition on an NVIDIA GPGPU,” Infotech@Aerospace Conference, March 2011 (Invited paper).

  125. C. Yakopcic, T. M. Taha, G. Subramanyam, E. Shin, P. T. Murray, and S. Rogers, “Memristor-based pattern recognition for image processing: an adaptive coded aperture imaging and sensing opportunity,” Proc. SPIE, Vol. 7818, 78180J, August 2010.

  126. C. Yakopcic, T. M. Taha, G. Subramanyam, E. Shin, P. T. Murray, and S. Rogers, “Memristor Fabrication and Characterization; An Adaptive Coded Aperture Imaging & Sensing Opportunity,” Proc. SPIE, Vol. 7818, 78180J, August 2010.

  127. B. Han and T. M. Taha, “Neuromorphic Models on a GPGPU Cluster,” International Joint Conference on Neural Networks, July 2010.

  128. T. M. Taha, P. Yalamanchili, M. Bhuiyan, R. Jalasutram, C. Chen, and R. Linderman, “Neuromorphic Algorithms on Clusters of PlayStation 3s,” International Joint Conference on Neural Networks, July 2010.

  129. C. Yakopcic, E. Shin, T. M. Taha, G. Subramanyam, P. T. Murray, S. Rogers, “Fabrication and Testing of Memristive Devices,” International Joint Conference on Neural Networks, Barcelona, Spain, July 2010.

  130. M. A. Bhuiyan, V. K. Pallipuram, M. C. Smith, T. M. Taha, R. Jalasutram, “Acceleration of spiking neural networks in emerging multi-core and GPU architectures,” IEEE International Symposium on Parallel & Distributed Processing, April 2010.

  131. P. Yalamanchili and T. M. Taha, “Multicore Cluster Implementations of Hierarchical Bayesian Cortical Models,” International Conference on Computer and Information Technology (ICCIT), December 2009.

  132. K. L. Rice, M. A. Bhuiyan, T. M. Taha, and C. N. Vutsinas, “FPGA Implementation of Izhikevich Spiking Neural Networks for Character Recognition,” International Conference on ReConFigurable Computing and FPGAs (ReConFig), Cancun, Mexico, December 2009.

  133. T. M. Taha, P. Yalamanchili, M. A. Bhuiyan, R. Jalasutram, and S. K. Mohan, “Parallelizing Two Classes of Neuromorphic Models on the Cell Multicore Architecture,” IEEE International Joint Conference on Neural Networks (IJCNN), Atlanta, GA, June 2009.

  134. M. A. Bhuiyan, R. Jalasutram, and T. M. Taha, “Character Recognition with Two Spiking Neural Network Models on Multicore Architectures,” IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing (CIMSVP), Nashville, TN, April 2009.

  135. P. Yalamanchili, S. Mohan, and T. Taha, “Implementing a Hierarchical Bayesian Visual Cortex Model on Multi-core Processors,” Proceedings of the 47th Annual Southeast Regional Conference (ACM-SE), Clemson, SC, March 2009.

  136. A. Awwal, K. L. Rice, R. Leach, R., and T. M. Taha, “Higher Accuracy Template for Corner Cube Reflected Image,” Optics and Photonics for Information processing II, San Diego, CA, August 2008.

  137. C. Vutsinas, K. L. Rice, and T. M. Taha “A neocortex model implementation on reconfigurable logic with streaming memory,” Reconfigurable Architectures Workshop (RAW), Miami, FL, April 2008.

  138. K. L. Rice, C. N. Vutsinas, and T. M. Taha, “A Preliminary Investigation of a Neocortex Model Implementation on the Cray XD1,” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (Supercomputing 2007), Reno, NV, November 2007.

  139. S. Lafontant, and T. M. Taha, “Feasibility of Hardware Acceleration of a Neocortex Model,” Proceedings of the International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA), Las Vegas, NV, June 2007.

  140. C. Smullen, and T. M. Taha, “PSATSim: An Interactive Graphical Superscalar Architecture Simulator for Power and Performance Analysis,” Proceedings of the Workshop on Computer Architecture Education (WCAE), Boston, MA, June 2006.

  141. K. Selvamani, and T. M. Taha, “Estimating Critical Region Parallelism to Guide Platform Retargeting,” Proceedings of the 43rd Annual Southeast Regional Conference (ACM-SE), Atlanta, GA, March 2005.

  142. T. M. Taha, and D. S. Wills, “An Instruction Throughput Model of Superscalar Processors,” Proceedings of the 14th IEEE International Workshop on Rapid System Prototyping (RSP), San Diego, CA, June 2003.

  143. L. Wills, T. Taha, L. Baumstark, and D. S. Wills, “Estimating Potential Parallelism for Platform Retargeting,” Proceedings of the 9th Working Conference on Reverse Engineering (WCRE), Richmond, VA, October 2002.

  144. L. Codrescu, M. Deb-Pant, T. Taha, J. Eble, D. S. Wills, and J. Meindl, “Exploring Microprocessor Architectures for Gigascale Integration,” Proceedings of the 20th Anniversary Conference on Advanced Research in VLSI (ARVLSI), Atlanta, GA, March 1999.