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ORCIDChathurika S. Wickramasinghe
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2020 – today
- 2024
[c17]Harindra S. Mavikumbure, Victor Cobilean, Chathurika S. Wickramasinghe, Devin Drake, Milos Manic:
Generative AI in Cyber Security of Cyber Physical Systems: Benefits and Threats. HSI 2024: 1-8- 2023
- [j7]Chathurika S. Wickramasinghe, Daniel L. Marino, Kasun Amarasinghe:
Editorial: Explainable artificial intelligence. Frontiers Comput. Sci. 5 (2023) - [j6]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) - [c16]Victor Cobilean, Harindra S. Mavikumbure, Chathurika S. Wickramasinghe, Daniel L. Marino, Milos Manic:
Informed Deep Learning for Anomaly Detection in Cyber-Physical Systems. ICIT 2023: 1-7 - [c15]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 - [c14]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 - [c13]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
- [c12]Harindra S. Mavikumbure, Chathurika S. Wickramasinghe, Daniel L. Marino, Victor Cobilean, Milos Manic:
Anomaly Detection in Critical-Infrastructures using Autoencoders: A Survey. IECON 2022: 1-7 - [i3]Daniel L. Marino, Chathurika S. Wickramasinghe, Craig Rieger, Milos Manic:
Self-Supervised and Interpretable Anomaly Detection using Network Transformers. CoRR abs/2202.12997 (2022) - [i2]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) - 2021
- [j5]Chathurika S. Wickramasinghe, Daniel L. Marino, Milos Manic:
ResNet Autoencoders for Unsupervised Feature Learning From High-Dimensional Data: Deep Models Resistant to Performance Degradation. IEEE Access 9: 40511-40520 (2021) - [j4]Chathurika S. Wickramasinghe, Kasun Amarasinghe, Daniel L. Marino, Craig Rieger, Milos Manic:
Explainable Unsupervised Machine Learning for Cyber-Physical Systems. IEEE Access 9: 131824-131843 (2021) - [j3]Daniel L. Marino, Chathurika S. Wickramasinghe, Vivek Kumar Singh, Jake Gentle, Craig Rieger, Milos Manic:
The Virtualized Cyber-Physical Testbed for Machine Learning Anomaly Detection: A Wind Powered Grid Case Study. IEEE Access 9: 159475-159494 (2021) - [j2]Daniel L. Marino, Chathurika S. Wickramasinghe, Billy Tsouvalas, Craig Rieger, Milos Manic:
Data-Driven Correlation of Cyber and Physical Anomalies for Holistic System Health Monitoring. IEEE Access 9: 163138-163150 (2021) - [c11]Chathurika S. Wickramasinghe, Daniel L. Marino, Milos Manic:
Deep Embedded Clustering with ResNets. HSI 2021: 1-6 - 2020
- [c10]Chathurika S. Wickramasinghe, Daniel L. Marino, Javier Grandio, Milos Manic:
Trustworthy AI Development Guidelines for Human System Interaction. HSI 2020: 130-136 - [c9]Daniel L. Marino, Javier Grandio, Chathurika S. Wickramasinghe, Kyle Schroeder, Keith Bourne, Afroditi V. Filippas, Milos Manic:
AI Augmentation for Trustworthy AI: Augmented Robot Teleoperation. HSI 2020: 155-161
2010 – 2019
- 2019
- [j1]Chathurika S. Wickramasinghe, Kasun Amarasinghe, Milos Manic:
Deep Self-Organizing Maps for Unsupervised Image Classification. IEEE Trans. Ind. Informatics 15(11): 5837-5845 (2019) - [c8]Chathurika S. Wickramasinghe, Kasun Amarasinghe, Daniel L. Marino, Zachary A. Spielman, Ira E. Pray, David Gertman, Milos Manic:
Intelligent Driver System for Improving Fuel Efficiency in Vehicle Fleets. HSI 2019: 34-40 - [c7]Morgan Stuart, Chathurika S. Wickramasinghe, Daniel L. Marino, Deepak Kumbhare, Kathryn Holloway, Milos Manic:
Machine Learning for Deep Brain Stimulation Efficacy using Dense Array EEG. HSI 2019: 143-150 - [c6]Chathurika S. Wickramasinghe, Daniel L. Marino, Fatih Yucel, Eyuphan Bulut, Milos Manic:
Data Driven Hourly Taxi Drop-offs Prediction using TLC Trip Record Data. HSI 2019: 168-173 - [c5]Daniel L. Marino, Chathurika S. Wickramasinghe, Craig Rieger, Milos Manic:
Data-driven Stochastic Anomaly Detection on Smart-Grid communications using Mixture Poisson Distributions. IECON 2019: 5855-5861 - 2018
- [c4]Chathurika S. Wickramasinghe, Kasun Amarasinghe, Daniel L. Marino, Milos Manic:
Deep Self-Organizing Maps for Visual Data Mining. HSI 2018: 304-310 - [c3]Chathurika S. Wickramasinghe, Daniel L. Marino, Kasun Amarasinghe, Milos Manic:
Generalization of Deep Learning for Cyber-Physical System Security: A Survey. IECON 2018: 745-751 - [c2]Daniel L. Marino, Chathurika S. Wickramasinghe, Milos Manic:
An Adversarial Approach for Explainable AI in Intrusion Detection Systems. IECON 2018: 3237-3243 - [i1]Daniel L. Marino, Chathurika S. Wickramasinghe, Milos Manic:
An Adversarial Approach for Explainable AI in Intrusion Detection Systems. CoRR abs/1811.11705 (2018) - 2017
- [c1]Chathurika S. Wickramasinghe, Kasun Amarasinghe, Milos Manic:
Parallalizable deep self-organizing maps for image classification. SSCI 2017: 1-7
Coauthor Index
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last updated on 2024-10-07 21:25 CEST by the dblp team
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