Publications

Accepted Refereed Journal Articles

  • Bennett, R., Razzaghi, T., Mulla, Z. (2022). “Early Prediction of Preeclampsia Using Machine Learning Methods“. Plos one, 17(4), e0266042.
  • Bennett, R., Pierce S., Razzaghi T., “Interpretable Machine Learning Models for Predicting Ce- sarean Delivery in Class III Obese Cohorts.”. IEEE Access, 13, 41230-41247.

Working papers/Submitted

  • Bennett, R., Razzaghi T.,“A Scalable Multilevel Deep Neural Network” under preparation to be sub- mitted to INFORMS Journal on Data Science.

Book Chapters

  • Bennett, R., Razzaghi, T., Hemmati, M. (2024). “A Gentle Survey of Artificial Intelligence/Machine Learning in Precision Health.“ Accepted in Springer

Presentations

Invited Talks

  • Scalable and Trustworthy Deep Neural Networks for Imbalanced Data; 2024 INFORMS Annual Conference; Seattle, WA.
  • Multilevel Neural Networks for Robust Learning; 2024 IISE Annual Conference; Montréal, Canada.
  • An Adaptive Multilevel Neural Network for Early Detection of Preeclampsia; 2023 INFORMS Annual Conference; Phoenix, AZ.
  • Early Detection of Preeclampsia using a Scalable Deep Neural Network Algorithm; 2022 INFORMS Annual Conference; Indianapolis, IN.
  • Machine Learning Methods and Applications in Materials; 2022 ASME Central Oklahoma Section Lightning Talks; Norman, OK.
  • An Imbalance Aware Deep Neural Network for Early Detection of Preeclampsia; 2021 INFORMS Annual Conference; Anaheim, CA.
  • A Cost-sensitive Deep Neural Network Model for Preeclampsia Prediction; 2021 IISE Annual, Virtual Conference.
  • Predicting the Development of Preeclampsia using Cost-Sensitive Deep Neural Networks; 2021 ASME Central Oklahoma Section Lightning Talks; Norman, OK.
  • Machine Learning: A Brief Demo of Supervised Learning; University of Oklahoma Tutorial: INFORMS student organization; April 2023; Norman, OK.

Poster Presentations

  • Fair Multilevel Neural Networks; INFORMS: Minority Issues Forum, 2024 INFORMS Annual Conference; Seattle, WA.
  • Fast Multilevel Neural Networks to Overcome Bias in Healthcare Applications; INFORMS: Minority Issues Forum, 2023 INFORMS Annual Conference; Phoenix, AZ.
  • Early Detection of Preeclampsia using a Scalable Deep Neural Network Algorithm; 2023 Oklahoma Conference for Statistics, Biostatistics, and Data Science; Oklahoma City, OK.
  • An Imbalance-Aware Deep Neural Network for Early Prediction of Preeclampsia; 2023 INFORMS Business Analytics; San Antonio, TX.
  • Predicting Preeclampsia Using Cost-Sensitive Deep Neural Networks; 2020 Graduate College of Engineering Grad Student Poster Fair; Norman, OK.
  • Determining the Volume of a Surface Defined by Tomographic Scattering Points; 2015 Mathematical Association of America MathFest; Washington, D.C.