For an up-to-date list, see my Google Scholar.

Peer-reviewed

Sergazinov, R., Chun, E., Rogovchenko, V., Fernandes, N., Kasman, N., Gaynanova, I. (2024).
“GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks.”
ICLR
[Code] [Slides]

Wu, J., Chen, S., Zhao, Q., Sergazinov, R., Li, C., Liu, S., Zhao, C., Xie, T., Guo, H., Ji, C., Cociorva, D., Brunzell, B. (2024).
“SwitchTab: Switched Autoencoders Are Effective Tabular Learners.”
AAAI
[arXiv]

Sergazinov, R., Armandpour, M., and Gaynanova, I. (2023).
“Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification.”
IEEE ICASSP.
[arXiv] [Code] [Materials]

Sergazinov, R., Leroux, A., Cui, E., Crainiceanu, C., Gaynanova, I. (2023).
“A case study of glucose levels during sleep using fast function on scalar regression inference.”
Biometrics.
[arXiv] [Code]

Sergazinov, R., and Kramar, M. (2021).
“Machine Learning Approach to Force Reconstruction in Photoelastic Materials.”
Machine Learning: Science and Technology.
[arXiv] [Code]

Talks

“Machine learning approach to force reconstruction in photoelastic materials,”
Undergraduate Research Day,
University of Oklahoma.
[OSF]