Agharazi, H., Kolacinski, R. M., Theeranaew, W. M., & Loparo, K. A.(2019).A swarm intelligence-based approach to anomaly detection of dynamic systems.Swarm and Evolutionary Computation,44, 806--827.
Xue, Z., Gong, L., Wang, G., Lu, C., Gilmore, H., Zhang, S., & Madabhushi, A.(2019).Convolutional neural network initialized active contour model with adaptive ellipse fitting for nuclear segmentation on breast histopathological images.Journal of Medical Imaging,6(1),017501.
Strezoski, L., VOJNOVIC, N., Strezoski, V., VIDOVIC, P., Prica, M., & Loparo, K. A.(2019).Modeling challenges and potential solutions for integration of emerging DERs in DMS applications: power flow and short-circuit analysis.Journal of Modern Power Systems and Clean Energy.
Janowczyk, A., Zuo, R., Gilmore, H., Feldman, M., & Madabhushi, A.(2019).HistoQC: An open-source quality control tool for digital pathology slides.JCO Clinical Cancer Informatics,3
Zhu, X., Ayday, E., & Vitenberg, R.(2019).A privacy-preserving framework for outsourcing location-based services to the cloud.IEEE Transactions on Dependable and Secure Computing.
Chen, H., Jia, H., Liao, W., Pashaei, V., Arutt, C., McCurdy, M., Zorman, C., Reed, R., Schrimpf, R., & Alles, M.(2019).Probing heavy ion radiation effects in silicon carbide (SiC) via 3D integrated multimode vibrating diaphragms.APPLIED PHYSICS LETTERS,114(10).
Kandhari, A., Mehringer, A., Chiel, H., Quinn, R. D., & Daltorio, K. A.(2019).Design and actuation of a fabric-based worm-like robot.Biomimetics,4(1),13.
Zhang, X., & Lin, W.(2018).Robust Stabilization of Uncertain Systems with Measurement Sensitivity Using Output Feedback.Proc. of the 57th IEEE Conference on Decision and Control (Dec. 17-19, 2018).
Zhang, X., & Lin, W.(2018).Universal Adaptive Control via Output Feedback for Nonlinear Systems with Parametric and Measurement Uncertainty.Proc. of the 57th IEEE Conference on Decision and Control (Dec. 17-19, 2018).
Leo, P., Elliott, R., Shih, N., Gupta, S., Feldman, M., & Madabhushi, A.(2018).Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study.Scientific Reports,8(1).
Chen, X., Ji, J., Luo, C., Liao, W., & Li, P.(2018).When Machine Learning Meets Blockchain: A Decentralized, Privacy-preserving, and Secure Design.IEEE International Conference on Big Data (BigData’18).
Shiradkar, R., Ghose, S., Jambor, I., Taimen, P., Ettala, O., Purysko, A., & Madabhushi, A.(2018).Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings.Journal of Magnetic Resonance Imaging,48(6),1626-1636.
