| Network analysis for identifying and characterizing disease outbreak influence from voluminous epidemiology data N Shah, H Shah, M Malensek, SL Pallickara, S Pallickara 2016 IEEE International Conference on Big Data (Big Data), 1222-1231, 2016 | 12 | 2016 |
| Ml health: Fitness tracking for production models S Ghanta, S Subramanian, L Khermosh, S Sundararaman, H Shah, ... arXiv preprint arXiv:1902.02808, 2019 | 10 | 2019 |
| {MPP}: Model Performance Predictor S Ghanta, S Subramanian, L Khermosh, H Shah, Y Goldberg, ... 2019 USENIX Conference on Operational Machine Learning (OpML 19), 23-25, 2019 | 7 | 2019 |
| Scalable network analytics for characterization of outbreak influence in voluminous epidemiology datasets N Shah, M Malensek, H Shah, S Pallickara, SL Pallickara Concurrency and Computation: Practice and Experience 31 (7), e4998, 2019 | 6 | 2019 |
| The shape of view: an alert system for video viewership anomalies A Manousis, H Shah, H Milner, Y Li, H Zhang, V Sekar Proceedings of the 21st ACM Internet Measurement Conference, 245-260, 2021 | 4 | 2021 |
| ML health monitor: taking the pulse of machine learning algorithms in production S Ghanta, S Subramanian, L Khermosh, S Sundararaman, H Shah, ... Applications of Machine Learning 11139, 191-202, 2019 | 3 | 2019 |
| Identification and characterization of super-spreaders from voluminous epidemiology data H Shah Colorado State University, 2016 | 1 | 2016 |
