Adaptive digital twins for personalized medicine

My current research develops adaptive digital twins for personalized medicine, combining mathematical modelling with adaptive estimation. We build iterative calibration methods for medical digital twins using adaptive estimators, so that treatment strategies can be personalized from individual patient data.

The work connects control theory to practical biomedical application, particularly for viral infections and immune system dynamics.

References

2025

Frontiers

Iterative calibration of medical digital twins via adaptive estimators

Juan E. Sereno, Havilah Neujahr, Miguel Hernandez-Gonzalez, and 1 more author

Frontiers in Applied Mathematics and Statistics, 2025

DOI Bib

@article{sereno2025iterative,
  title = {Iterative calibration of medical digital twins via adaptive estimators},
  author = {Sereno, Juan E. and Neujahr, Havilah and Hernandez-Gonzalez, Miguel and Hernandez-Vargas, Esteban A.},
  journal = {Frontiers in Applied Mathematics and Statistics},
  volume = {11},
  pages = {1699390},
  year = {2025},
  doi = {10.3389/fams.2025.1699390},
}

CDC

Adaptive Observers for Calibrating Immune Digital Twins in Viral Infections

Angel Rodriguez-Liñan, Juan E. Sereno, Griselda Quiroz-Compean, and 1 more author

In 64th IEEE Conference on Decision and Control (CDC), 2025

DOI Bib

@inproceedings{rodriguezlinan2025adaptive,
  title = {Adaptive Observers for Calibrating Immune Digital Twins in Viral Infections},
  author = {Rodriguez-Liñan, Angel and Sereno, Juan E. and Quiroz-Compean, Griselda and Hernandez-Vargas, Esteban A.},
  booktitle = {64th IEEE Conference on Decision and Control (CDC)},
  address = {Rio de Janeiro, Brazil},
  year = {2025},
  doi = {10.1109/CDC57313.2025.11312546},
}