Toward a Framework in Cloudlet-Based Architecture for a Real-Time Predictional Model. - Olivera Kotevska; Ahmed Lbath; Samia Bouzefrane 001 (UIC/ATC/ScalCom, 2015)

Automatic Categorization of Social Sensor Data. - Olivera Kotevska; Sarala Padi; Ahmed Lbath (EUSPN/ICTH, 2016)

Event model to facilitate data sharing among services: Closing the gap between research and implementation. - Olivera Kotevska; Ahmed Lbath; J. Gelernter (WF-IoT, 2016)

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics. - Olivera Kotevska; A. Gilad Kusne; Daniel V. Samarov; Ahmed Lbath; Abdella Battou (IEEE Access, 2017)

Learning based event model for knowledge extraction and prediction system in the context of Smart City. (Un modèle de gestion d'évènements basé sur l'apprentissage pour un système d'extraction et de prédiction dans le contexte de Ville Intelligente). - Olivera Kotevska (2018)

Kensor: Coordinated Intelligence from Co-Located Sensors. - Olivera Kotevska; Kalyan S. Perumalla; Juan Lopez Jr. (IEEE BigData, 2019)

Increasing city safety awareness regarding disruptive traffic stream. - Olivera Kotevska (CoRR, 2019)

Methodology for Interpretable Reinforcement Learning Model for HVAC Energy Control. - Olivera Kotevska; Jeffrey Munk; Kuldeep R. Kurte; Yan Du; Kadir Amasyali; Robert W. Smith 004; Helia Zandi (IEEE BigData, 2020)

Activity Characterization for Modeling Behavioral-driven Human Mobility in Platial Networks. - Gautam S. Thakur; Olivera Kotevska (LocalRec@SIGSPATIAL, 2020)

Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics. - Suzanne Parete-Koon; Peter F. Peterson; Garrett E. Granroth; Wenduo Zhou; Pravallika Devineni; Nouamane Laanait; Junqi Yin; Albina Y. Borisevich; Ketan Maheshwari; Melissa R. Allen-Dumas; Srinath Ravulaparthy; Kuldeep R. Kurte; et al. (SMC, 2020)

Optimal Balance of Privacy and Utility with Differential Privacy Deep Learning Frameworks. - Olivera Kotevska; Folami Alamudun; Christopher B. Stanley (CSCI, 2021)

Effectiveness of Privacy Techniques in Smart Metering Systems. - Martin Peralta-Peterson; Olivera Kotevska (CSCI, 2021)

Double Deep Q-Networks for Optimizing Electricity Cost of a Water Heater. - Kadir Amasyali; Kuldeep R. Kurte; Helia Zandi; Jeffrey Munk; Olivera Kotevska; Robert W. Smith 004 (ISGT, 2021)

Measurement of Local Differential Privacy Techniques for IoT-based Streaming Data. - Sharmin Afrose; Danfeng Daphne Yao; Olivera Kotevska (PST, 2021)

Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. - Pravallika Devineni; Panchapakesan Ganesh; Nikhil Sivadas; Abhijeet Dhakane; Ketan Maheshwari; Drahomira Herrmannova; Ramakrishnan Kannan; Seung-Hwan Lim; Thomas E. Potok; Jordan B. Chipka; Priyantha Mudalige; Mark Coletti; et al. (SMC, 2021)

Privacy policy robustness to reverse engineering. - A. Gilad Kusne; Olivera Kotevska (CIKM Workshops, 2022)

Privacy Amplification for Episodic Training Methods. - Vandy Tombs; Olivera Kotevska; Steven Young (CIKM Workshops, 2022)

PAS: Privacy Algorithms in Systems. - Philip S. Yu; Olivera Kotevska; Tyler Derr (CIKM, 2022)

Analyzing Data Privacy for Edge Systems. - Olivera Kotevska; Jordan Johnson; A. Gilad Kusne (SMARTCOMP, 2022)

Whitepaper on Reusable Hybrid and Multi-Cloud Analytics Service Framework. - Gregor von Laszewski; Wo L. Chang; Russell Reinsch; Olivera Kotevska; Ali Karimi; Abdul Rahman Sattar; Garry Mazzaferro; Geoffrey C. Fox (CoRR, 2023)

Energy-efficient cooperative resource allocation and task scheduling for Internet of Things environments. - Eyhab Al-Masri; Alireza Souri; Habiba Mohamed; Wenjun Yang; James Olmsted; Olivera Kotevska (Internet Things, 2023)

Frequency Oracle for Sensitive Data Monitoring (Student Abstract). - Richard Sances; Olivera Kotevska; Paul Laiu (AAAI, 2024)

Privacy-Preserving Federated Learning for Science: Challenges and Research Directions. - Kibaek Kim; Krishnan Raghavan; Olivera Kotevska; Matthieu Dorier; Ravi K. Madduri; Minseok Ryu; Todd S. Munson; Robert Ross; Thomas Flynn 001; Ai Kagawa; Byung-Jun Yoon; Christian Engelmann; et al. (IEEE Big Data, 2024)

Assessing Membership Inference Attacks under Distribution Shifts. - Yichuan Shi; Olivera Kotevska; Viktor Reshniak; Amir Sadovnik (IEEE Big Data, 2024)

Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations. - Joel Brogan; Olivera Kotevska; Anibely Torres; Sumit Jha; Mark Adams (MLSP, 2024)

Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy. - Yichuan Shi; Olivera Kotevska; Viktor Reshniak; Abhishek Singh 005; Ramesh Raskar (CoRR, 2024)

A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications. - Yi Zhang; Yuying Zhao; Zhaoqing Li; Xueqi Cheng; Yu Wang 160; Olivera Kotevska; Philip S. Yu; Tyler Derr (IEEE Trans. Knowl. Data Eng., 2024)

Traceable Black-box Watermarks for Federated Learning. - Jiahao Xu; Rui Hu; Olivera Kotevska; Zikai Zhang (CoRR, 2025)

Optimal Client Sampling in Federated Learning with Client-Level Heterogeneous Differential Privacy. - Jiahao Xu; Rui Hu; Olivera Kotevska (CoRR, 2025)

Privacy Preservation from High-Performance Computing to Autonomous Science [Industrial and Governmental Activities]. - Olivera Kotevska (IEEE Comput. Intell. Mag., 2025)

Enhancing Smart Home Privacy: A Tutorial on Local Differential Privacy Techniques for Frequency and Mean Estimation. - Olivera Kotevska; Xi He; Eyhab Al-Masri (IEEE Commun. Mag., 2025)