Abstracts and Workshop Articles
- Yurkovic-Harding, Julia Rose, Vignesh Narayanan, John Richards, and Jessica Bradshaw, "Social behaviors forecast physiological regulation for infants with ASD and TD infants," INSAR 2025.
- Bharath Muppasani, Protik Nag, Biplav Srivastava, and Vignesh Narayanan, "On generalized planning for controlling opinion networks: Interpreting human-AI dialog states and beliefs," Workshop on Generalization in Planning, AAAI, Philadelphia, 2025.
- Erik Connerty, Rae Jones, Protik Nag, Bharath Muppasani, Sai Teja Paladi, Vignesh Narayanan, Biplav Srivastava, and Michael Huhns, "Information competition simulator: A high-performance approach to modeling opinion dynamics in large populations," DiscoverUSC-2024.
- Diksha Srishyla, Erik Connerty, Vignesh Narayanan, and Christian O'Reilly, "Systematic comparison of brain connectivity metrics for EEG," DiscoverUSC-2024.
- Chathurangi Shyalika, Kaushik Roy, Renjith Prasad, Yuxin Zi, Priya Mittal, Fadi El Kalach, Vignesh Narayanan, Ramy Harik, and Amit Sheth, "RI2AP-Robust and interpretable 2D anomaly prediction in assembly pipelines," DiscoverUSC-2024 (Best poster award).
- Deepa Tilwani, Christian O'Reilly, Raxitkumar Goswami, Nicholas Riccardi, Xuan Yang, Valerie L. Shalin, Vignesh Narayanan, Svetlana Shinkareva, Amit P. Sheth, and Rutvik Harshad Desai, "Predicting language outcomes from MRI post-stroke: A machine learning approach," The Organization for Human Brain Mapping (OHBM), 29th Annual meeting, July 2023.
- Vignesh Narayanan, Bharath Muppasani, Sai Teja Paladi, Biplav Srivastava, and Michael Huhns, "Modeling and steering multi-dimensional opinion networks with aggregated measurements," SIAM Conference on Applications of Dynamical Systems (DS23), Portland, Oregon, May 2023.
- Vignesh Narayanan and Avimanyu Sahoo, "Optimal sampling, communication, and distributed control protocols via pseudo-spectral methods," SIAM Conference on Applications of Dynamical Systems (DS23), Portland, Oregon, May 2023.
- Avimanyu Sahoo, Geetika Vennam, and Vignesh Narayanan, "Neural network-based state estimation of lithium-ion batteries under internal faults," SIAM Conference on Applications of Dynamical Systems (DS23), Portland, Oregon, May 2023.
- "Event-driven approximate dynamic programming for feedback control," Seminar in Advances in Computing Series, University of South Carolina, April 2022.
- Jr-Shin Li, Wei Miao, and Vignesh Narayanan, "A scalable computational framework for solving large-scale linear regression problems," The Second Joint SIAM/CAIMS Annual Meeting (AN20), Toronto, Canada, July 2020 (Accepted contributed lecture).
- Vignesh Narayanan, Jr-Shin Li, and Shinung Ching, "Biophysically interpretable, model-free identification of neuronal dynamics," Computational and Systems Neuroscience (Cosyne), Denver, CO, 2018.
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