Using Candlestick Charting and Dynamic Time Warping for Data Behavior Modeling and Trend Prediction for MWSN in IoT. - Concepcion Sanchez Aleman; Niki Pissinou; Sheila Alemany; Georges A. Kamhoua (IEEE BigData, 2018)

Context-Aware Data Cleaning for Mobile Wireless Sensor Networks: A Diversified Trust Approach. - Concepcion Sanchez Aleman; Niki Pissinou; Sheila Alemany; Kianoosh G. Boroojeni; Jerry Miller; Ziqian Ding (ICNC, 2018)

A Dynamic Trust Weight Allocation Technique for Data Reconstruction in Mobile Wireless Sensor Networks. - Concepcion Sanchez Aleman; Niki Pissinou; Sheila Alemany; Georges A. Kamhoua (TrustCom/BigDataSE, 2018)

Predicting Hurricane Trajectories Using a Recurrent Neural Network. - Sheila Alemany; Jonathan Beltran; Adrián Pérez; Sam Ganzfried (AAAI, 2019)

Quantifying location privacy in permissioned blockchain-based internet of things (IoT). - Abdur Rahman Bin Shahid; Niki Pissinou; Laurent Njilla; Sheila Alemany; Ahmed Imteaj; Kia Makki; Edwin Aguilar (MobiQuitous, 2019)

The Dilemma Between Dimensionality Reduction and Adversarial Robustness. - Sheila Alemany; Niki Pissinou (CoRR, 2020)

Jespipe: A Plugin-Based, Open MPI Framework for Adversarial Machine Learning Analysis. - Sheila Alemany; Jason Nucciarone; Niki Pissinou (IEEE BigData, 2021)

The Dilemma Between Data Transformations and Adversarial Robustness for Time Series Application Systems. - Sheila Alemany; Niki Pissinou (SafeAI@AAAI, 2022)

Towards Parametric Robust Activation Functions in Adversarial Machine Learning. - Sheila Alemany; Alberto Luis Dominguez; Ilan Grapel; Niki Pissinou (Tiny Papers @ ICLR, 2023)

Increasing Adversarial Robustness Around Uncertain Boundary Regions with Amodal Segmentation. - Sheila Alemany; Niki Pissinou; Brian Yang (ICMLA, 2024)

Unifying Robust Activation Functions for Reduced Adversarial Vulnerability with the Parametric Generalized Gamma Function. - Sheila Alemany; Emma Worthington; Alberto Luis Dominguez; Ilan Grapel; Niki Pissinou (ICMLA, 2024)