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  • 2022

    • Yumusak, S., Coban, M., Yilmaz, Y., and Altun, H.O., 2022. Detecting Dangerous Maritime Refugee Migration Paths through Cell Phone Activities. IEEE International Conference on Big Data (Big Data) [pdf]
    • Mozaffari, M., Doshi, K. and Yilmaz, Y., 2022. Online Multivariate Anomaly Detection and Localization for High-Dimensional Settings. Sensors, 22(21), p.8264. [pdf]
    • Mozaffari, M., Doshi, K. and Yilmaz, Y., 2022. Real-Time Detection and Classification of Power Quality Disturbances. Sensors, 22(20), p.7958. [pdf]
    • Haydari, A. and Yilmaz, Y., 2022. RSU-Based Online Intrusion Detection and Mitigation for VANET. Sensors, 22(19), p.7612. [pdf]
    • Meyers, S., Yilmaz, Y., and Luther, M., “Some Methods for Addressing Errors in Static AIS Data Records”, Ocean Engineering [pdf]
    • Shuvo, S.S., Islam, M., and Yilmaz, Y., “DROP: Deep Reinforcement Learning Based Optimal Perturbation for MPPT in Wind Energy”, The 54th North American Power Symposium (NAPS 2022) [pdf]
    • Shuvo, S.S., Symum, H., Ahmed, M.R., Yilmaz, Y., and Zayas-Castro, J.L., ”Multi- Objective Reinforcement Learning Based Healthcare Expansion Planning Considering Pandemic Events”, IEEE Journal of Biomedical and Health Informatics [pdf]
    • Doshi, K., Abudalou, S. and Yilmaz, Y., 2022. Reward Once, Penalize Once: Rectifying Times Series Anomaly Detection. International Joint Conference on Neural Networks (IJCNN) [pdf]
    • Shuvo, S.S. and Yilmaz, Y., 2022. Home Energy Recommendation System (HERS): A Deep Reinforcement Learning Method based on Residents’ Feedback and Activity. IEEE Transactions on Smart Grid [pdf]
    • Mumcu, F., Doshi, K. and Yilmaz, Y., 2022. Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) [pdf]
    • Doshi, K. and Yilmaz, Y., 2022. Federated Learning-based Driver Activity Recognition for Edge Devices. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)[pdf]
    • Doshi, K. and Yilmaz, Y., 2022. Multi-Task Learning for Video Surveillance with Limited Data. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) [pdf]
    • M. N. Kurt, Y. Yilmaz and X. Wang, 2022. “Online Privacy-Preserving Data- Driven Network Anomaly Detection”, IEEE Journal on Selected Areas in Communications [pdf]
    • Doshi, K. and Yilmaz, Y., 2022. Rethinking Video Anomaly Detection - A Continual Learning Approach. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)[pdf] [supplementary]
    • Doshi, K. and Yilmaz, Y., 2022. A Modular and Unified Framework for Detecting and Localizing Video Anomalies. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)[pdf] [supplementary]

  • 2021

    • S. Shuvo, Y. Yilmaz, A. Bush and M. Hafen, 2021. Modeling and Simulating Adaptation Strategies Against Sea-Level Rise Using Multiagent Deep Reinforcement Learning, IEEE Transactions on Computational Social Systems.[pdf]
    • Shuvo, S.S. and Yilmaz, Y., 2021. CIBECS: Consumer Input Based Electric Vehicle Charge Scheduling for a Residential Home. The 53rd North American Power Symposium (NAPS 2021) [pdf]
    • Shuvo, S.S., Gebremariam, H. and Yilmaz, Y., 2021. Deep Reinforcement Learning Based OptimalPerturbation for MPPT in Photovoltaics. The 53rd North American Power Symposium (NAPS 2021) [pdf]
    • Y. Yilmaz, M. Aktukmak and A. Hero, 2021. Multimodal Data Fusion in High-Dimensional Heterogeneous Datasets via Generative Models, IEEE Transactions on Signal Processing.[pdf]
    • Nassar, A. and Yilmaz, Y., 2021. Deep Reinforcement Learning for Adaptive Network Slicing in 5G for Intelligent Vehicular Systems and Smart Cities. IEEE Internet of Things Journal.[pdf]
    • Aktukmak, M., Yilmaz, Y. and Uysal, I., 2021. Sequential Attack Detection in Recommender Systems. IEEE Transactions on Information Forensics and Security. [pdf]
    • Doshi, K. and Yilmaz, Y., 2021. An Efficient Approach for Anomaly Detection in Traffic Videos. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. [pdf]
    • Shuvo, S.S., Ahmed, M.R., Symum, H. and Yilmaz, Y., 2021. Deep Reinforcement Learning Based Cost-Benefit Analysis for Hospital Capacity Planning. International Joint Conference on Neural Networks (IJCNN). [pdf]
    • Doshi, K. and Yilmaz, Y., 2021. Online anomaly detection in surveillance videos with asymptotic bound on false alarm rate. Pattern Recognition. [pdf]
    • Doshi, K., Yilmaz, Y. and Uludag, S., 2021. Timely Detection and Mitigation of Stealthy DDoS Attacks via IoT Networks. IEEE Transactions on Dependable and Secure Computing. [pdf][appendix]

  • 2020

    • Shuvo, S.S. and Yilmaz, Y., 2020. "Predictive Maintenance for Increasing EV Charging Load in Distribution Power System". IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm).[pdf]
    • Shuvo, S.S., Yilmaz, Y., Bush, A. and Hafen, M., 2020. "A Markov Decision Process Model for Socio-Economic Systems Impacted by Climate Change". International Conference on Machine Learning (ICML).[pdf]
    • Doshi, K. and Yilmaz, Y., 2020. "Fast unsupervised anomaly detection in traffic videos." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (pp. 624-625).[pdf]
    • Doshi, K. and Yilmaz, Y., 2020. "Continual Learning for Anomaly Detection in Surveillance Videos." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (pp. 254-255).[pdf]
    • Doshi, K. and Yilmaz, Y., 2020. Road Damage Detection using Deep Ensemble Learning. IEEE International Conference on Big Data (IEEE BigData) [pdf]
    • Doshi, K. and Yilmaz, Y., 2020. "Any-Shot Sequential Anomaly Detection in Surveillance Videos." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (pp. 934-935).[pdf]
    • Haydari, A. and Yilmaz, Y., 2020. "Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey." IEEE Transactions on Intelligent Transportation Systems. arXiv preprint arXiv:2005.00935 [pdf]
    • M. Kurt, Y. Yilmaz and X. Wang, "Real-Time Nonparametric Anomaly Detection in High-Dimensional Settings", IEEE Transactions on Pattern Analysis and Machine Intelligence [pdf]
  • 2019

    • M. Kurt, Y. Yilmaz and X. Wang, "Sequential Model-Free Anomaly Detection for Big Data Streams", 57th Annual Allerton Conference on Communication, Control, and Computing [pdf]
    • A. Nassar and Y. Yilmaz, "Reinforcement Learning for Adaptive Resource Allocation in Fog RAN for IoT With Heterogeneous Latency Requirements", IEEE Access [pdf]
    • S. Shuvo and Y. Yilmaz, "Scenario Planning for Sea Level Rise via Reinforcement Learning", IEEE Global Conference on Signal and Information Processing (GlobalSIP) [pdf]
    • A. Nassar and Y. Yilmaz, "Dynamic Network Slicing for Fog Radio Access Networks", IEEE Global Conference on Signal and Information Processing (GlobalSIP) [pdf]
    • M. Aktukmak, Y. Yilmaz and I. Uysal, "A Probabilistic Framework to Incorporate Mixed-Data Type Features: Matrix Factorization with Multimodal Side Information", Neurocomputing [pdf]
    • M. Mozaffari and Y. Yilmaz, "Online Anomaly Detection in Multivariate Settings", IEEE International Workshop on Machine Learning for Signal Processing (MLSP) [pdf]
    • M. Kurt, Y. Yilmaz and X. Wang, "Secure Distributed Dynamic State Estimation in Wide-Area Smart Grids", IEEE Transactions on Information Forensics and Security, [pdf]
    • M. Aktukmak, Y. Yilmaz and I. Uysal, "Quick and Accurate Attack Detection in Recommender Systems through User Attributes", ACM Conference on Recommender Systems, 2019 [pdf] *Best Paper Award Runner-up
    • K. Doshi, M. Mozaffari and Y. Yilmaz, "RAPID: Real-time Anomaly-based Preventive Intrusion Detection", ACM Workshop on Wireless Security and Machine Learning (WiseML), 2019 [pdf]
    • M. Kurt, Y. Yilmaz and X. Wang, "Real-Time Detection of Hybrid and Stealthy Cyber-Attacks in Smart Grid", IEEE Transactions on Information Forensics and Security, vol. 14, no. 2, pp. 498-513, Feb. 2019 [pdf]
    • E. Hou, Y. Yilmaz and A. Hero, "Anomaly Detection in Partially Observed Traffic Networks", IEEE Transactions on Signal Processing, 2019 [pdf]
    • H. Ali, S. Liu, Y. Yilmaz, A. Hero, R. Couillet and I. Rajapakse, "Latent Heterogeneous Multilayer Community Detection", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019 [pdf]
    • A. Nassar and Y. Yilmaz, "Resource Allocation in Fog RAN for Heterogeneous IoT Environments based on Reinforcement Learning", IEEE International Conference on Communications (ICC), 2019 [pdf]
    • Y. Yilmaz and S. Uludag, "Timely Detection and Mitigation of IoT-based Cyberattacks in the Smart Grid", Journal of the Franklin Institute, Elsevier, 2019 [pdf]
    • M. Schlafly, Y. Yilmaz and K. Reed, "Feature Selection in Gait Classiffication of Leg Length and Distal Mass", Informatics in Medicine Unlocked, Elsevier, 2019 [link]
  • 2018

    • Y. Yilmaz, M. Kurt and X. Wang, "Distributed Dynamic State Estimation and LQG Control in Resource-Constrained Networks", IEEE Transactions on Signal and Information Processing over Networks, vol. 4, no. 3, pp. 599-612, Sep. 2018 [pdf]
    • M. Kurt, Y. Yilmaz and X. Wang, "Distributed Quickest Detection of Cyber-Attacks in Smart Grid", IEEE Transactions on Information Forensics and Security, vol. 13, no. 8, pp. 2015-2030, Aug. 2018 [pdf]
    • Y. Yilmaz and A. Hero, "Multimodal Event Detection in Twitter Hashtag Networks", Journal of Signal Processing Systems, vol. 90, no. 2, pp. 185-200, Feb. 2018 [pdf]
    • A. Haydari and Y. Yilmaz, "Real-Time Detection and Mitigation of DDoS Attacks in Intelligent Transportation Systems", IEEE International Conference on Intelligent Transportation Systems (ITSC), 2018 [pdf]
  • 2017

    • Y. Yilmaz and S. Uludag, "Mitigating IoT-based Cyberattacks on the Smart Grid", IEEE International Conference on Machine Learning and Applications (ICMLA), 2017 [pdf]
    • Y. Yilmaz, "Online Nonparametric Anomaly Detection based on Geometric Entropy Minimization", IEEE International Symposium on Information Theory (ISIT), 2017 [pdf]