SMBE 2026: AI in Molecular Evolution and Phylogenetics

Abstract deadline is approaching (February 3) for oral and poster
presentations at SMBE 2026 on artificial intelligence (AI) and machine
learning (ML) in molecular evolution and phylogenetics.

The symposium title is "Powers and pitfalls of artificial intelligence
for molecular evolution and phylogenetics."
Specify symposium #S02 when submitting the abstract. 
SMBE annual meetings in Copenhagen (Jun 28-Jul 02, 2026)
https://smbe2026.org/programme

Invited Speakers are:
Anne-Florence Bitbol - EFPL (?cole Polytechnique F?d?rale de Lausanne),
Switzerland
Sudhir Kumar - Institute for Genomics and Evolutionary Medicine, Temple
University, USA

Symposium description
Artificial intelligence (AI) may reshape the landscape of molecular
evolution and phylogenetic analysis. A growing number of machine
learning and deep learning methods are being developed for tasks
ranging from inferring evolutionary trees and detecting selection to
modeling sequence evolution and predicting protein structures. Yet
many remain skeptical, as fundamental questions persist: What exactly
do these models learn from biological data? How do their internal
representations relate to established evolutionary principles? And
crucially, what are their blind spots? This symposium is a forum for
discussing the transformative potential and the critical limitations of
AI and ML in evolutionary research. Speakers will explore how AI models
capture patterns of evolutionary variation and divergence, and whether
their learned representations and models genuinely reflect underlying
evolutionary mechanisms. The session will also feature discussions
of new methodological advances, emerging interpretability frameworks,
and benchmark analyses testing the reliability and reproducibility of
AI-driven inferences.

Contact: s.kumar@temple.edu

s.kumar@temple.edu

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