Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting. - Arash Hajisafi; Haowen Lin; Sina Shaham; Haoji Hu; Maria Despoina Siampou; Yao-Yi Chiang; Cyrus Shahabi (SIGSPATIAL/GIS, 2023)

An Evaluation of Time-Series Anomaly Detection in Computer Networks. - Hong Nguyen; Arash Hajisafi; Alireza Abdoli; Seon Ho Kim; Cyrus Shahabi (ICOIN, 2023)

Holistic Survey of Privacy and Fairness in Machine Learning. - Sina Shaham; Arash Hajisafi; Minh K. Quan; Dinh C. Nguyen; Bhaskar Krishnamachari; Charith Peris; Gabriel Ghinita; Cyrus Shahabi; Pubudu N. Pathirana (CoRR, 2023)

Wearables for Health (W4H) Toolkit for Acquisition, Storage, Analysis and Visualization of Data from Various Wearable Devices. - Arash Hajisafi; Maria Despoina Siampou; Jize Bi; Luciano Nocera; Cyrus Shahabi (ICDE, 2024)

Dynamic GNNs for Precise Seizure Detection and Classification from EEG Data. - Arash Hajisafi; Haowen Lin; Yao-Yi Chiang; Cyrus Shahabi (PKDD (4), 2024)

WaveGNN: Modeling Irregular Multivariate Time Series for Accurate Predictions. - Arash Hajisafi; Maria Despoina Siampou; Bita Azarijoo; Cyrus Shahabi (CoRR, 2024)

Small Graph Is All You Need: DeepStateGNN for Scalable Traffic Forecasting. - Yannick Wölker; Arash Hajisafi; Cyrus Shahabi; Matthias Renz (CoRR, 2025)

Privacy and Fairness in Machine Learning: A Survey. - Sina Shaham; Arash Hajisafi; Minh K. Quan; Dinh C. Nguyen; Bhaskar Krishnamachari; Charith Peris; Gabriel Ghinita; Cyrus Shahabi; Pubudu N. Pathirana (IEEE Trans. Artif. Intell., 2025)