Escalera Lab: Research Projects

My research explores the evolution and adaptation of RNA viruses at the interface of genomics, evolution, and epidemiology. I develop computational and machine learning frameworks to forecast viral immune escape and support vaccine design, integrating large-scale genomic, structural, and immunological data. Alongside, I lead a One Health research initiative in Mexico, seeking to strengthen and support virus genomic epidemiology surveillance and research, bridging academia into public health. By combining fundamental and translational approaches, I aim to generate actionable insights that advance infectious disease control and strengthen preparedness against emerging viral threats. I have worked wide range of virus–host systems, including influenza A (human and avian), SARS-CoV-2, DENV, ZIKV, CHIKV, paramyxoviruses, Lassa virus, and more recently, HIV.

PAVE (Predict Antigenic Viral Evolution)

PAVE integrates viral genomics, structural biology, immunology, and machine learning to forecast immune escape in rapidly evolving viruses (SARS-CoV-2, Influenza A).

REEED-Social

An international and cross-sectoral network that brings together researchers, public health, and communities to study viral epidemiology in dynamic ecological and social contexts, with applications in Mexico.