Your Actions or Your Associates? Predicting Certification and Dropout in MOOCs with Behavioral and Social Features. - Niki Gitinabard; Farzaneh Khoshnevisan; Collin F. Lynch; Elle Yuan Wang (EDM, 2018)

Recent Temporal Pattern Mining for Septic Shock Early Prediction. - Farzaneh Khoshnevisan; Julie S. Ivy; Muge Capan; Ryan Arnold; Jeanne Huddleston; Min Chi (ICHI, 2018)

Network-Based Modeling of Sepsis: Quantification and Evaluation of Simultaneity of Organ Dysfunctions. - Ali Jazayeri; Muge Capan; Christopher C. Yang; Farzaneh Khoshnevisan; Min Chi; Ryan Arnold (BCB, 2019)

One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks. - Ye Mao; Rui Zhi; Farzaneh Khoshnevisan; Thomas W. Price; Tiffany Barnes; Min Chi (EDM, 2019)

Missing Data Imputation for MIMIC-III using Matrix Decomposition. - Xi Yang 019; Yeo-Jin Kim; Farzaneh Khoshnevisan; Yuan Zhang 028; Min Chi (ICHI, 2019)

RSM-GAN: A Convolutional Recurrent GAN for Anomaly Detection in Contaminated Seasonal Multivariate Time Series. - Farzaneh Khoshnevisan; Zhewen Fan (CoRR, 2019)

An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems. - Farzaneh Khoshnevisan; Min Chi (IEEE BigData, 2020)

Improving Robustness on Seasonality-Heavy Multivariate Time Series Anomaly Detection. - Farzaneh Khoshnevisan; Zhewen Fan; Vitor R. Carvalho (CoRR, 2020)

Unifying Domain Adaptation and Domain Generalization for Robust Prediction Across Minority Racial Groups. - Farzaneh Khoshnevisan; Min Chi (ECML/PKDD (1), 2021)

Cross-Lingual Adversarial Domain Adaptation for Novice Programming. - Ye Mao; Farzaneh Khoshnevisan; Thomas W. Price; Tiffany Barnes; Min Chi (AAAI, 2022)

Reconstructing Missing EHRs Using Time-Aware Within- and Cross-Visit Information for Septic Shock Early Prediction. - Ge Gao; Farzaneh Khoshnevisan; Min Chi (ICHI, 2022)