Iliomar Rodríguez Ramos

My research:

My current research includes modeling trigger efficiencies for emerging-jet searches and developing NMF-based anomaly-detection methods for offline detector data quality monitoring within the CMS experiment. I also work on using a flow matching model for pileup mitigation and realistic event generation in HEP.

My expertise is:

Still working on the “expert” part, but I know my way around machine learning for physics, scientific computing, and data analysis using Python.

A problem I’m grappling with:

Time management, sleep deprivation, and the ongoing challenge of balancing several research projects at the same time.

I’ve got my eyes on:

Autoencoder-based anomaly detection for offline detector data quality monitoring, and how large language models could help make physics analysis workflows more efficient.

I want to know more about:

Using Coffea and Dask for physics analysis, as well as parallel programming.