Date：2026/3/25 16:30-17:30
Location：R104, CSIE
Speakers：Dr. Taoyang Wu (University of East Anglia)
Host：巫芳璟教授
Abstract:
Trees and networks play a central role in representing and analysing evolutionary processes in both natural systems, such as proteins and species, and human languages. In this talk, I will present several algorithmic and mathematical challenges related to detecting evolutionary signals using evolutionary trees and networks. This includes recent results on a subclass of explicit evolutionary networks inspired by ideas from graph drawing. I will also highlight case studies illustrating the opportunities and limitations of applying deep learning to infer evolutionary forces, and discuss the open challenges that arise in bridging data-driven methods with classical evolutionary models.
Biography:
Taoyang Wu (https://research-portal.uea.ac.uk/en/persons/taoyang-wu/) is an Associate Professor in Computing Sciences at the University of East Anglia (UEA), Norwich, UK. He completed his PhD in 2009 at Queen Mary, University of London. His research focuses on the algorithmic and mathematical foundations of evolutionary analysis, with particular interests in evolutionary trees and networks, computational phylogenetics, and applications of deep learning and AI to evolutionary inference and ecology studies. He also works on graph algorithms and interdisciplinary problems at the interface of computer science, biology, and statistics. He has led and contributed to several international collaborations, including projects involving partners across Europe and Asia.