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TL;DR

I am currently working as a Research Scientist on Meta's Modern Recommender System Team.

Experience

Meta, Modern Recommender System Team (Current)
Research Scientist

  • Working on multi-modal recommender systems

Meta, Modern Recommender System Team (Summer 2024)
Machine Learning Engineer Intern

  • Worked on extending context length for large language models (LLM)

Amazon, Customer Trust and Partner Support Team (Summer 2022 and 2023)
Applied Scientist Intern

  • Developed a probability calibration method for imbalanced datasets
  • Developed multi-task deep learning models for detecting system abuse and fraud
  • Worked on deep learning for tabular data

Texas A&M University, Department of Statistics (2020 - present)
PhD Candidate

  • Advised by Prof. Gaynanova, Prof. Qian, and Prof. Carroll
  • Research on personalized probabilistic models for statistical inference and prediction

Education

PhD in Statistics at Texas A&M University (2020 - present)
BS in Mathematics at University of Oklahoma (2016 - 2020)
BS in Economics at University of Oklahoma (2016 - 2020)

Publications

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

In progress

📄 Sergazinov, R., Taeb, A., Gaynanova, I. (2024+). "JISEPS: Joint and Individual Subspace Exploration via Product-based Subsampling."

Peer-reviewed

📄 Sergazinov, R., Chen, R., Ji, C., Wu, J., Cociorva, D., Brunzell, B. (2025). "Improving Model Calibration by Integration of Large Data Sources with Biased Labels." AAAI

📄 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]