| An imbalance-aware BiLSTM for control chart patterns early detection M Derakhshi, T Razzaghi Expert Systems with Applications 249, 123682, 2024 | | 2024 |
| Fueling the Future: A Comprehensive Analysis and Forecast of Fuel Consumption Trends in US Electricity Generation MMH Bhuiyan, AN Sakib, SI Alawee, T Razzaghi Sustainability 16 (2388), 2024 | | 2024 |
| Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations E Jafarigol, T Trafalis, T Razzaghi, M Zamankhani arXiv preprint arXiv:2311.10832, 2023 | | 2023 |
| Predicting cesarean delivery among gravidas with morbid obesity–a machine learning approach R Kolli, T Razzaghi, S Pierce, RK Edwards, M Maxted, P Parikh AJOG Global Reports 3 (4), 100276, 2023 | | 2023 |
| Forecasting the Fuel Consumption and Price for Future Pandemic Outbreak: A case study in the USA under COVID-19 AN Sakib, T Razzaghi, MMH Bhuiyan Sustainability 15 (17), 12692, 2023 | | 2023 |
| Machine learning approaches to modeling interdependent network restoration time G Ramineni, N Ghorbani-Renani, K Barker, AD González, T Razzaghi, ... Environment Systems and Decisions 43 (1), 22-35, 2023 | 1 | 2023 |
| Monitoring and Forecasting the COVID-19 Pandemic in Peru J Unterbrink, C Nicholson, T Razzaghi, A González, Y Velazco, ... Proceedings of the IISE Annual Conference & Expo 2023, http …, 2023 | | 2023 |
| Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation EA Stahlberg, M Abdel-Rahman, B Aguilar, A Asadpoure, RA Beckman, ... Frontiers in Digital Health 4, 1007784, 2022 | 23 | 2022 |
| A machine learning and clustering-based approach for county-level COVID-19 analysis C Nicholson, L Beattie, M Beattie, T Razzaghi, S Chen Plos one 17 (4), e0267558, 2022 | 15 | 2022 |
| An imbalance-aware deep neural network for early prediction of preeclampsia R Bennett, ZD Mulla, P Parikh, A Hauspurg, T Razzaghi Plos one 17 (4), e0266042, 2022 | 10 | 2022 |
| Predicting cesarean amongst obese gravidas-a machine learning approach P Parikh, R Kolli, SL Pierce, R Edwards, M Maxted, T Razzaghi American Journal of Obstetrics & Gynecology 226 (1), S274-S275, 2022 | | 2022 |
| A cost-sensitive convolution neural network learning for control chart pattern recognition D Fuqua, T Razzaghi Expert Systems with Applications 150, 113275, 2020 | 79 | 2020 |
| Relaxed support vector regression OP Panagopoulos, P Xanthopoulos, T Razzaghi, O Şeref Annals of Operations Research 276, 191-210, 2019 | 16 | 2019 |
| Engineering fast multilevel support vector machines E Sadrfaridpour, T Razzaghi, I Safro Machine Learning, arXiv preprint arXiv:1707.07657, 2019 | 37 | 2019 |
| Predictive models for bariatric surgery risks with imbalanced medical datasets JS Talayeh Razzaghi, Ilya Safro, Joseph Ewing, Ehsan Sadrfaridpour Annals of Operations Research, 2019 | 44* | 2019 |
| Personalized Colorectal Cancer Survivability Prediction with Machine Learning Methods* S Li, T Razzaghi 2018 IEEE International Conference on Big Data (Big Data), 2554-2558, 2018 | 3 | 2018 |
| Engineering multilevel support vector machines E Sadrfaridpour, T Razzaghi, I Safro arXiv preprint arXiv:1707.07657, 2017 | 3 | 2017 |
| Constraint relaxation, cost-sensitive learning and bagging for imbalanced classification problems with outliers T Razzaghi, P Xanthopoulos, O Şeref Optimization Letters 11, 915-928, 2017 | 11 | 2017 |
| Weighted relaxed support vector machines O Şeref, T Razzaghi, P Xanthopoulos Annals of Operations Research 249, 235-271, 2017 | 22 | 2017 |
| Algebraic multigrid support vector machines I Sadrfaridpour, Ehsan and Jeereddy, Sandeep and Kennedy, Ken and Luckow ... ESANN, European Symposium on Artificial Neural Networks, Computational …, 2017 | 19* | 2017 |
Ilya SafroAssociate Professor of Computer Science, University of DelawareVerified email at udel.edu
