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ORCIDTimothy D. Pennington
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2020 – today
- 2023
[j1]Chathurika S. Wickramasinghe
, Daniel L. Marino, Harindra S. Mavikumbure, Victor Cobilean, Timothy D. Pennington, Benny J. Varghese, Craig Rieger, Milos Manic:
RX-ADS: Interpretable Anomaly Detection Using Adversarial ML for Electric Vehicle CAN Data. IEEE Trans. Intell. Transp. Syst. 24(12): 14051-14063 (2023)- [c3]Victor Cobilean, Harindra S. Mavikumbure, Chathurika S. Wickramasinghe, Benny J. Varghese, Timothy D. Pennington, Milos Manic:
Anomaly Detection for In-Vehicle Communication Using Transformers. IECON 2023: 1-6 - [c2]Harindra S. Mavikumbure, Victor Cobilean, Chathurika S. Wickramasinghe, Benny J. Varghese, Timothy D. Pennington, Milos Manic:
DAdAE: Domain Adversarial Autoencoder Based In-Vehicle CAN Anomaly Detection. IECON 2023: 1-7 - [c1]Harindra S. Mavikumbure, Victor Cobilean, Chathurika S. Wickramasinghe, Tyler Phillips, Benny J. Varghese, Barney Carlson, Craig Rieger, Timothy D. Pennington, Milos Manic:
Physical Anomaly Detection in EV Charging Stations: Physics-based vs ResNet AE. ISIE 2023: 1-7 - 2022
- [i2]Don Scoffield, John Smart, Timothy D. Pennington, C. Birk Jones, Matthew S. Lave, Anudeep Medam, Bhaskar Mitra:
Strategies to Maintain Voltage on Long, Lightly Loaded Feeders with Widespread Residential Level 2 Plug-in Electric Vehicle Charging. CoRR abs/2206.05552 (2022) - [i1]Chathurika S. Wickramasinghe, Daniel L. Marino, Harindra S. Mavikumbure, Victor Cobilean, Timothy D. Pennington, Benny J. Varghese, Craig Rieger, Milos Manic:
RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data. CoRR abs/2209.02052 (2022)
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