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ORCIDMaryam Parsa
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- affiliation: George Mason University, Fairfax, VA, USA
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2020 – today
- 2024
[c24]Shay Snyder
, Victoria Clerico, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Sumedh R. Risbud, Maryam Parsa:
Transductive Spiking Graph Neural Networks for Loihi. ACM Great Lakes Symposium on VLSI 2024: 608-613- [c23]Shay Snyder, Sumedh R. Risbud, Maryam Parsa:
Asynchronous Neuromorphic Optimization in Lava. ACM Great Lakes Symposium on VLSI 2024: 776-778 - [i17]Hamed Poursiami, Ihsen Alouani, Maryam Parsa:
BrainLeaks: On the Privacy-Preserving Properties of Neuromorphic Architectures against Model Inversion Attacks. CoRR abs/2402.00906 (2024) - [i16]Shay Snyder, Victoria Clerico, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Sumedh R. Risbud, Maryam Parsa:
Transductive Spiking Graph Neural Networks for Loihi. CoRR abs/2404.17048 (2024) - [i15]Shay Snyder, Sumedh R. Risbud, Maryam Parsa:
Asynchronous Neuromorphic Optimization with Lava. CoRR abs/2404.17052 (2024) - [i14]Hamed Poursiami, Ihsen Alouani, Maryam Parsa:
Watermarking Neuromorphic Brains: Intellectual Property Protection in Spiking Neural Networks. CoRR abs/2405.04049 (2024) - [i13]Shay Snyder, Derek Gobin, Victoria Clerico, Sumedh R. Risbud, Maryam Parsa:
Parallelized Multi-Agent Bayesian Optimization in Lava. CoRR abs/2405.04387 (2024) - [i12]Derek Gobin, Shay Snyder, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Maryam Parsa:
Exploration of Novel Neuromorphic Methodologies for Materials Applications. CoRR abs/2405.04478 (2024) - [i11]Jason Sinaga, Victoria Clerico, Md. Abdullah-Al Kaiser, Shay Snyder, Arya Lohia, Gregory Schwartz, Maryam Parsa, Akhilesh Jaiswal:
Hardware-Algorithm Re-engineering of Retinal Circuit for Intelligent Object Motion Segmentation. CoRR abs/2408.08320 (2024) - [i10]Shay Snyder, Andrew Capodieci, David J. Gorsich, Maryam Parsa:
Brain Inspired Probabilistic Occupancy Grid Mapping with Hyperdimensional Computing. CoRR abs/2408.09066 (2024) - [i9]Victoria Clerico, Shay Snyder, Arya Lohia, Md. Abdullah-Al Kaiser, Gregory Schwartz, Akhilesh Jaiswal, Maryam Parsa:
Retina-inspired Object Motion Segmentation. CoRR abs/2408.09454 (2024) - 2023
- [j6]Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Chathika Gunaratne, Kenneth A. De Jong:
Avoiding excess computation in asynchronous evolutionary algorithms. Expert Syst. J. Knowl. Eng. 40(5) (2023) - [c22]Maryam Parsa, Khaled N. Khasawneh, Ihsen Alouani:
A Brain-inspired Approach for Malware Detection using Sub-semantic Hardware Features. ACM Great Lakes Symposium on VLSI 2023: 139-142 - [c21]Guojing Cong, Shruti R. Kulkarni, Seung-Hwan Lim, Prasanna Date, Shay Snyder, Maryam Parsa, Dominic Kennedy, Catherine D. Schuman:
Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation. ICMLA 2023: 1541-1546 - [c20]Shay Snyder, Sumedh R. Risbud, Maryam Parsa:
Neuromorphic Bayesian Optimization in Lava. ICONS 2023: 9:1-9:5 - [c19]Shay Snyder, Kevin Zhu, Ricardo Vega, Cameron Nowzari, Maryam Parsa:
Zespol: A Lightweight Environment for Training Swarming Agents. ICONS 2023: 24:1-24:5 - [e1]Catherine D. Schuman, Melika Payvand, Maryam Parsa:
Proceedings of the 2023 International Conference on Neuromorphic Systems, ICONS 2023, Santa Fe, NM, USA, August 1-3, 2023. ACM 2023 [contents] - [i8]Ricardo Vega, Kevin Zhu, Sean Luke, Maryam Parsa, Cameron Nowzari:
Simulate Less, Expect More: Bringing Robot Swarms to Life via Low-Fidelity Simulations. CoRR abs/2301.09018 (2023) - [i7]Shay Snyder, Hunter Thompson, Md. Abdullah-Al Kaiser, Gregory Schwartz, Akhilesh R. Jaiswal, Maryam Parsa:
Object Motion Sensitivity: A Bio-inspired Solution to the Ego-motion Problem for Event-based Cameras. CoRR abs/2303.14114 (2023) - [i6]Shay Snyder, Sumedh R. Risbud, Maryam Parsa:
Neuromorphic Bayesian Optimization in Lava. CoRR abs/2305.11060 (2023) - [i5]Shay Snyder, Kevin Zhu, Ricardo Vega, Cameron Nowzari, Maryam Parsa:
Zespol: A Lightweight Environment for Training Swarming Agents. CoRR abs/2306.17744 (2023) - 2022
- [j5]Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Prasanna Date, Bill Kay:
Opportunities for neuromorphic computing algorithms and applications. Nat. Comput. Sci. 2(1): 10-19 (2022) - [j4]Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Prasanna Date, Bill Kay:
Publisher Correction: Opportunities for neuromorphic computing algorithms and applications. Nat. Comput. Sci. 2(3): 205 (2022) - [j3]Catherine D. Schuman, Robert M. Patton, Shruti R. Kulkarni, Maryam Parsa, Christopher G. Stahl, Nicholas Quentin Haas, J. Parker Mitchell, Shay Snyder, Amelie Nagle, Alexandra Shanafield, Thomas E. Potok:
Evolutionary vs imitation learning for neuromorphic control at the edge. Neuromorph. Comput. Eng. 2(1): 14002 (2022) - [j2]James B. Aimone, Prasanna Date, Gabriel A. Fonseca Guerra, Kathleen E. Hamilton, Kyle Henke, Bill Kay, Garrett T. Kenyon, Shruti R. Kulkarni, Susan M. Mniszewski, Maryam Parsa, Sumedh R. Risbud, Catherine D. Schuman, William Severa, J. Darby Smith:
A review of non-cognitive applications for neuromorphic computing. Neuromorph. Comput. Eng. 2(2): 32003 (2022) - [c18]Guojing Cong, Seung-Hwan Lim, Shruti R. Kulkarni, Prasanna Date, Thomas E. Potok, Shay Snyder, Maryam Parsa, Catherine D. Schuman:
Semi-Supervised Graph Structure Learning on Neuromorphic Computers. ICONS 2022: 28:1-28:4 - [i4]Samuel Schmidgall, Catherine D. Schuman, Maryam Parsa:
Biological connectomes as a representation for the architecture of artificial neural networks. CoRR abs/2209.14406 (2022) - 2021
- [j1]Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman:
Benchmarking the performance of neuromorphic and spiking neural network simulators. Neurocomputing 447: 145-160 (2021) - [c17]Maryam Parsa, Shruti R. Kulkarni, Mark Coletti, Jeffrey K. Bassett, J. Parker Mitchell, Catherine D. Schuman:
Multi-Objective Hyperparameter Optimization for Spiking Neural Network Neuroevolution. CEC 2021: 1225-1232 - [c16]Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman:
Training Spiking Neural Networks with Synaptic Plasticity under Integer Representation. ICONS 2021: 6:1-6:7 - [c15]Maryam Parsa, Catherine D. Schuman, Nitin Rathi, Amirkoushyar Ziabari, Derek C. Rose, J. Parker Mitchell, J. Travis Johnston, Bill Kay, Steven R. Young, Kaushik Roy:
Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach. ICONS 2021: 14:1-14:8 - [c14]Robert M. Patton, Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Nicholas Quentin Haas, Christopher G. Stahl, Spencer Paulissen, Prasanna Date, Thomas E. Potok, Shay Sneider:
Neuromorphic Computing for Autonomous Racing. ICONS 2021: 23:1-23:5 - [c13]Catherine D. Schuman, James S. Plank, Maryam Parsa, Shruti R. Kulkarni, Nicholas D. Skuda, J. Parker Mitchell:
A Software Framework for Comparing Training Approaches for Spiking Neuromorphic Systems. IJCNN 2021: 1-10 - [c12]Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa:
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC 2021: 361-382 - [c11]Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Kenneth A. De Jong:
Avoiding Excess Computation in Asynchronous Evolutionary Algorithms. UKCI 2021: 71-82 - 2020
- [c10]Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose, Bill Kay, J. Parker Mitchell, Steven R. Young, Ryan Dellana, William Severa, Thomas E. Potok, Kaushik Roy:
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. IJCNN 2020: 1-9 - [c9]Catherine D. Schuman, J. Parker Mitchell, J. Travis Johnston, Maryam Parsa, Bill Kay, Prasanna Date, Robert M. Patton:
Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems. IJCNN 2020: 1-10 - [c8]Catherine D. Schuman, J. Parker Mitchell, Maryam Parsa, James S. Plank, Samuel D. Brown, Garrett S. Rose, Robert M. Patton, Thomas E. Potok:
Automated Design of Neuromorphic Networks for Scientific Applications at the Edge. IJCNN 2020: 1-7 - [c7]Daniel Elbrecht, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman:
Evolving Ensembles of Spiking Neural Networks for Neuromorphic Systems. SSCI 2020: 1989-1994 - [c6]Daniel Elbrecht, Maryam Parsa, Shruti R. Kulkarni, J. Parker Mitchell, Catherine D. Schuman:
Training Spiking Neural Networks Using Combined Learning Approaches. SSCI 2020: 1995-2001 - [i3]Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose, Bill Kay, J. Parker Mitchell, Steven R. Young, Ryan Dellana, William Severa, Thomas E. Potok, Kaushik Roy:
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. CoRR abs/2005.04171 (2020)
2010 – 2019
- 2019
- [c5]Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok, Kaushik Roy:
Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems. IEEE BigData 2019: 4472-4478 - [c4]Steven R. Young, Pravallika Devineni, Maryam Parsa, J. Travis Johnston, Bill Kay, Robert M. Patton, Catherine D. Schuman, Derek C. Rose, Thomas E. Potok:
Evolving Energy Efficient Convolutional Neural Networks. IEEE BigData 2019: 4479-4485 - [c3]Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy:
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. ICCAD 2019: 1-8 - [i2]Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy:
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. CoRR abs/1906.08167 (2019) - 2017
- [c2]Maryam Parsa, Priyadarshini Panda, Shreyas Sen, Kaushik Roy:
Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis. EMBC 2017: 78-81 - 2016
- [i1]Abhronil Sengupta, Maryam Parsa, Bing Han, Kaushik Roy:
Probabilistic Deep Spiking Neural Systems Enabled by Magnetic Tunnel Junction. CoRR abs/1605.04494 (2016) - 2012
- [c1]Majed Rostamian, Maryam Parsa, Voicu Groza:
Design and fabrication of a smart electronic guide for museums. SACI 2012: 439-444
Coauthor Index
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last updated on 2024-10-07 22:12 CEST by the dblp team
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