| Your Actions or Your Associates? Predicting Certification and Dropout in MOOCs with Behavioral and Social Features N Gitinabard, F Khoshnevisan, CF Lynch, EY Wang Educational Data Mining 2018, 2018 | 55 | 2018 |
| One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks Y Mao, R Zhi, F Khoshnevisan, T Price, T Barnes, M Chi Proceedings of The 12th International Conference on Educational Data Mining …, 2019 | 43 | 2019 |
| Recent Temporal Pattern Mining for Septic Shock Early Prediction F Khoshnevisan, J Ivy, M Capan, R Arnold, JM Huddleston, M Chi 2018 IEEE International Conference on Healthcare Informatics (ICHI) (2018 …, 2018 | 40 | 2018 |
| An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems F Khoshnevisan, M Chi 2020 IEEE International Conference on Big Data, 2020 | 12 | 2020 |
| Unifying Domain Adaptation and Domain Generalization for Robust Prediction across Minority Racial Groups F Khoshnevisan, M Chi | 10 | 2021 |
| Cross-Lingual Adversarial Domain Adaptation for Novice Programming Y Mao, F Khoshnevisan, T Price, T Barnes, M Chi Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7682-7690, 2022 | 6 | 2022 |
| Improving Robustness on Seasonality-Heavy Multivariate Time Series Anomaly Detection F Khoshnevisan, Z Fan, VR Carvalho The 6th KDD Workshop on Mining and Learning from Time Series, 2020 | 6 | 2020 |
| Convolutional recurrent generative adversarial network for anomaly detection FAN Zhewen, F Khoshnevisan US Patent App. 16/985,467, 2021 | 5 | 2021 |
| Missing data imputation for MIMIC-III using matrix decomposition X Yang, YJ Kim, F Khoshnevisan, Y Zhang, M Chi 2019 IEEE International Conference on Healthcare Informatics (ICHI), 1-3, 2019 | 5 | 2019 |
| Your actions or your associates? Predicting certification and dropout in MOOCs with behavioral and social features. arXiv 2018 N Gitinabard, F Khoshnevisan, CF Lynch, EY Wang arXiv preprint arXiv:1809.00052, 0 | 5 | |
| Rsm-gan: A convolutional recurrent gan for anomaly detection in contaminated seasonal multivariate time series F Khoshnevisan, Z Fan arXiv preprint arXiv:1911.07104, 2019 | 4 | 2019 |
| Network-Based Modeling of Sepsis: Quantification and Evaluation of Simultaneity of Organ Dysfunctions A Jazayeri, M Capan, C Yang, F Khoshnevisan, M Chi, R C. Arnold The 10th ACM Conference on Bioinformatics, Computational Biology, and Health …, 2019 | 4 | 2019 |
| Reconstructing missing ehrs using time-aware within-and cross-visit information for septic shock early prediction G Gao, F Khoshnevisan, M Chi 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI …, 2022 | 3 | 2022 |
| A Variational Recurrent Adversarial Multi-Source Domain Adaptation Framework for Septic Shock Early Prediction Across Medical Systems F Khoshnevisan North Carolina State University, 2021 | 2 | 2021 |
| Method and system of automatically predicting anomalies in online forms J Kalyanam, FAN Zhewen, K Byungkyu, KE Swift-spong, ... US Patent 11,620,274, 2023 | | 2023 |
| Calibrated risk scoring and sampling KE Swift-spong, S Narayanaswamy, CA Oliveira, K Byungkyu, ... US Patent App. 17/390,816, 2023 | | 2023 |
Min ChiDepartment of Computer Science, North Carolina State UniversityVerified email at ncsu.edu
