Maryam Parsa

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 43

Top Topics

Imitation Learning

Monte Carlo Sampling

Automated Design

Top Venues

ACM Great Lakes Symposium on VLSI

Publications

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 (2024)
Shay Snyder, Derek Gobin, Victoria Clerico, Sumedh R. Risbud, Maryam Parsa
Parallelized Multi-Agent Bayesian Optimization in Lava. CoRR (2024)
Hamed Poursiami, Ihsen Alouani, Maryam Parsa
Watermarking Neuromorphic Brains: Intellectual Property Protection in Spiking Neural Networks. CoRR (2024)
Shay Snyder, Sumedh R. Risbud, Maryam Parsa
Asynchronous Neuromorphic Optimization in Lava. ACM Great Lakes Symposium on VLSI (2024)
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)
Hamed Poursiami, Ihsen Alouani, Maryam Parsa
BrainLeaks: On the Privacy-Preserving Properties of Neuromorphic Architectures against Model Inversion Attacks. CoRR (2024)
Shay Snyder, Sumedh R. Risbud, Maryam Parsa
Asynchronous Neuromorphic Optimization with Lava. CoRR (2024)
Derek Gobin, Shay Snyder, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Maryam Parsa
Exploration of Novel Neuromorphic Methodologies for Materials Applications. CoRR (2024)
Ricardo Vega, Kevin Zhu, Sean Luke, Maryam Parsa, Cameron Nowzari
Simulate Less, Expect More: Bringing Robot Swarms to Life via Low-Fidelity Simulations. CoRR (2023)
Shay Snyder, Kevin Zhu, Ricardo Vega, Cameron Nowzari, Maryam Parsa
Zespol: A Lightweight Environment for Training Swarming Agents. ICONS (2023)
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)
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)
Shay Snyder, Sumedh R. Risbud, Maryam Parsa
Neuromorphic Bayesian Optimization in Lava. ICONS (2023)
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 (2023)
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)
Shay Snyder, Kevin Zhu, Ricardo Vega, Cameron Nowzari, Maryam Parsa
Zespol: A Lightweight Environment for Training Swarming Agents. CoRR (2023)
Shay Snyder, Sumedh R. Risbud, Maryam Parsa
Neuromorphic Bayesian Optimization in Lava. CoRR (2023)
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) (2022)
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) (2022)
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) (2022)
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) (2022)
Samuel Schmidgall, Catherine D. Schuman, Maryam Parsa
Biological connectomes as a representation for the architecture of artificial neural networks. CoRR (2022)
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)
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)
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)
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)
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)
Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman
Benchmarking the performance of neuromorphic and spiking neural network simulators. Neurocomputing 447 (2021)
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)
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)
Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman
Training Spiking Neural Networks with Synaptic Plasticity under Integer Representation. ICONS (2021)
Daniel Elbrecht, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman
Evolving Ensembles of Spiking Neural Networks for Neuromorphic Systems. SSCI (2020)
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 (2020)
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)
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)
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)
Daniel Elbrecht, Maryam Parsa, Shruti R. Kulkarni, J. Parker Mitchell, Catherine D. Schuman
Training Spiking Neural Networks Using Combined Learning Approaches. SSCI (2020)
Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. CoRR (2019)
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)
Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. ICCAD (2019)
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)
Maryam Parsa, Priyadarshini Panda, Shreyas Sen, Kaushik Roy
Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis. EMBC (2017)
Abhronil Sengupta, Maryam Parsa, Bing Han, Kaushik Roy
Probabilistic Deep Spiking Neural Systems Enabled by Magnetic Tunnel Junction. CoRR (2016)
Majed Rostamian, Maryam Parsa, Voicu Groza
Design and fabrication of a smart electronic guide for museums. SACI (2012)